Inhibitory Endophenotypes Help Classify Schizophrenia and Bipolar Patients

Clinicians often misdiagnose mania as schizophrenia while schizophrenia is usually mistaken for schizoaffective disorder. According to a study by Laura F. Martin, MD, of the University of Colorado, and colleagues, physiologic inhibitory endophenotypes may be able to differentiate patients with schizophrenia from patients with bipolar disorder.

The study involved 29 patients with schizophrenia, 40 patients with bipolar disorder, and 18 patients with schizoaffective disorder. The study evaluated suppression of the three biologic indicators of sensory response inhibition, ie, P50 auditory evoked response, leading saccades during smooth pursuit eye movements, and inhibition of saccades during antisaccade tasks. Despite group differences in the electrophysiologic tests, there is a large degree of overlap among individuals from the groups. After logistic regression analysis, results found that P50 ratio and frequency of leading saccades distinguished schizophrenia patients from bipolar patients with a sensitivity of 95% and a specificity of 83%. Participants in the schizoaffective group were split with six patients characterized as schizophrenia-like and 12 patients characterized as bipolar-like.

“I was surprised at how well a combination of only three tests correctly identified so many individuals,” Dr. Martin said.

The biggest limitation to this study was the lack of variety within the sample. The results need to be cross-validated among a different sample of individuals. In addition, it would be helpful to complete the same study in an inpatient group as this study was only completed in an outpatient group with clinically stable disease.

“I would have liked to see if the electrophysiology continued to support the clinical nosology,” Dr. Martin said. “With the increasingly complex task of differentiating acute psychotic mania from shizophrenia, would the area under the receiver operating characteristic curve also decrease?”

While identifying endophenotypes may help clinicians understand genetic studies and the neurobiology of these disorders, this study’s results do not have direct clinical applicability. However, this knowledge may help determine how affective features associated with schizophrenia and psychotic features associated with bipolar disorder make them clearly distinguishable disorders.

Funding for this research was provided by the Veterans Affairs Research Service and the National Institute of Mental Health. (Am J Psychiatry. 2007;164(12):1900-1906.) —ML


Increased Risk of PTSD Symptoms in Combat-Exposed Military Personnel

Soldiers returning from war have long been reported to exhibit symptoms of posttraumatic stress disorder (PTSD). Historically, the prevalence rate of PTSD in military cohorts seems to have corresponded with the level of “boots on the ground” combat. According to previous reports, for example, as many as 30% of returning United States soldiers who fought in the Vietnam War, and 10% of soldiers in the 1991 Gulf War, exhibited PTSD symptoms.

Past studies of PTSD in this population have been retrospective. However, a recent study by Tyler C. Smith, MS, of the Department of Defense Center for Deployment Health Research at the Naval Health Research Center in San Diego, California, and colleagues, includes pre-deployment baseline data on PTSD symptoms in military personnel along with a comprehensive follow-up analyses.

Baseline data were compiled between July 2001 and June 2003 from a cohort of 70,047 active US military personnel; 50,184 personnel participated in follow up questionnaires administered between June 2004 and February 2006. Using follow up data, the investigators determined the incidence of new-onset PTSD in both deployed and non-deployed military personnel. Outcome measures were based on two levels of data collection, including “sensitive” and “specific” definitions. The “sensitive” definition of PTSD symptoms was based on Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), criteria alone; the “specific” definition included DSM-IV criteria along with a required sum of 50, on a scale of 17–85, on the PTSD checklist–civilian version, a 17-item self-report PTSD measure.

Exposure to combat was a significant incidental factor in this study. During follow up, one survey asked participants whether they had ever been exposed to or witnessed “a person’s death due to war, disaster, or tragic event,” “instances of physical abuse (torture, beating, rape),” or “maimed soldiers or civilians.”

New instances of self-reported PTSD were found in 7.6% to 8.7% of deployed personnel who reported combat exposure, 1.4% to 2.1% of deployers with no combat exposure, and 2.3% to 3.0% of non-deployed personnel. Overall, these data indicate a threefold increase in new-onset PTSD cases from baseline. Subjects who reported PTSD symptoms at baseline were excluded from these analyses.

By the “sensitive” criteria, new-onset PTSD symptoms were reported in 4.9% of Army personnel (the highest reported percentage) and 1.8% in the Air Force (the lowest reported percentage). Deployed personnel across all military branches were more likely to be male, born between 1970–1979, less educated (high school/equivalent or less), and combat specialists. However, new-onset PTSD symptoms were proportionately higher in those who were younger, female, never married or divorced, enlisted, black non-Hispanics, and less education (high school/equivalent or less). The researchers note, however, that higher-educated, older members of this cohort, such as officers or Marines, were more likely to report persisting symptoms at follow up, suggesting a reason for this group’s lower odds of new-onset PTSD symptoms.

Another significant finding of this study includes the data that were collected on problem drinking and smoking status across all military branches and occupations. Those who reported current smoking and problem drinking at baseline also had an increased risk of new-onset PTSD, although smoking and problem drinking were also tied to persistent PTSD symptoms.
Funding for this research was provided by the Department of Defense. (BMJ. 2008;336:366-371.) —LS


Symptom Changes in ADHD Found as Children Grow into Adolescence

Affecting approximately 5% to 10% of children and adolescents worldwide, attention-deficit/hyperactivity disorder (ADHD) is a common, chronic behavioral condition associated with cognitive deficits and diminished academic performance, which is characterized by inattention, impulsivity, and hyperactivity. Although children with ADHD may present more often with symptoms of impulsivity and hyperactivity, adolescents with the disorder may have more cognitive deficits, such as impairments with working memory and inhibition. While ADHD is often studied in children and adolescents separately, there have been few large, longitudinal studies of the prevalence of ADHD in adolescents.

Susan L. Smalley, PhD, of the Semel Institute at the University of California at Los Angeles, and colleagues, evaluated adolescents who participated in the Northern Finland Birth Cohort 1986, which studied 9,432 children from the early fetal period to adolescence (16–18 years of age) for ADHD prevalence. The authors also sought to assess the clinical characteristics of ADHD in the adolescent population as compared to the course of the disorder in childhood.

Among the children studied in the Northern Finland Birth Cohort 1986, 6,622 participants responded to a survey about adolescence and ADHD. Smalley and colleagues identified a subset of 457 adolescents among those who responded; this subset included adolescents who may have ADHD and other psychiatric conditions as well as those who did not have the disorder and could act as controls. The authors used a standard screening survey and diagnostic criteria to identify adolescents with ADHD and comorbid disorders.

Smalley and colleagues found that the estimated prevalence of ADHD among adolescents in the birth cohort was 8.5%. They also found that as children with ADHD age, hyperactivity and impulsivity related to the disorder decrease while inattention increases. Most adolescents with ADHD exhibited the inattentive subtype (64%), while the hyperactive-impulsive (8%) and combined (28%) subtypes were found in fewer adolescents.

The study also found that ADHD in adolescence is significantly associated with increased rates of other psychiatric conditions including depression and anxiety disorders. In addition, conduct disorders, such as vandalism and truancy, oppositional behavior, and posttraumatic stress disorder were elevated in adolescents with ADHD as compared to those without the disorder. A lifetime diagnosis of ADHD had a prevalence of 18.2%, and a lifetime diagnosis was also significantly associated with the presence of anxiety and disruptive behavioral disorders.

The authors concluded that although cognitive deficits are present in adolescents with ADHD, they are often not used as an indicator for the disorder in childhood as children with cognitive deficits typically do not show increased symptoms of hyperactivity or inattention, which are symptoms used to identify the disorder in children. Thus, Smalley and colleagues suggest that researchers examine more closely what environmental conditions lead to impairment in children and adolescents with ADHD. 

Regarding medication use to treat the disorder, the authors conclude that researchers should also examine the efficacy of stimulant use in the United States as medication use in Finland was limited and the presentation of ADHD in adolescence was similar to the presentation of the disorder among patients in the US. Although medications are beneficial in the short term, the authors suggest that further study into the long-term course of ADHD and its overall effects is needed.

Funding for this research was provided by the National Institute of Mental Health, the Juselius Foundation, and the Academy of Finland. (J Am Acad Child Adolesc Psychiatry. 2007;46(12):1575-1583.) —CP


Cognitive and Genotypic Predictors of Impulsive Behavior in Alcoholism

The etiology and development of addictive disorders might imply a more serious neurobiologic effect than previously believed, according to a recent study that analyzed the immediate reward bias in the human brain. Using a combination of imaging and genotyping analyses, Charlotte A. Boettiger, PhD, and colleagues at the University of California, San Francisco’s Gallo Clinic and Research Center examined the reaction of several brain regions in recovering, abstinent alcoholics and in subjects with no history of substance abuse.
“Our data suggest possible brain mechanisms for decision-making impairment among alcoholics, which provides an endophenotype and thus an intermediate therapeutic target for testing clinical interventions prior to clinical trials,” Dr. Boettiger said. 

A pronounced bias toward immediate gratification, compared to choosing greater benefits derived over a longer term, is characteristic of people with alcoholism and addictive disorder. Nine recovering, abstinent alcoholics and 10 subjects with no history of substance abuse underwent functional magnetic resonance imaging (fMRI) bold oxygen level-dependent (BOLD) analysis. Subjects were asked to consider hypothetical scenarios in which a lesser award, or a greater, long-term award, was available. fMRI BOLD was conducted during the decision-making process at sites within the posterior parietal cortex, the dorsal prefrontal cortex, and the rostral parahippocampal gyrus regions.

The recovering alcoholic subgroup chose the immediate gratification option three times more often than the control group, and they showed diminished orbital frontal cortex activity—a region of the brain that Dr. Boettiger suggests may be associated with the long-term award. High activity in the dorsal prefrontal cortex and the parietal cortex was associated with a bias toward immediately gratification, which, as Dr. Boettiger explains, “runs counter to the belief that addicts make such choices due to heightened reward sensitivity and suggests that abnormalities in cognitive processing contribute to immediate reward bias.”

This investigation also included a genotyping aspect. Genotype at the Val158Met polymorphism of the catechol-O-methyltransferase (COMT) gene predicted impulsive behavior and correlated with high activity in the posterior parietal cortex and the dorsal prefrontal cortex. Boettiger and colleagues noted that the data indicate that COMT genotype confers behavioral differences which may be relevant for therapeutic response to specific treatments for substance abuse.

“Behavioral addiction treatment often focuses on learning to think more concretely about the consequences of relapse,” Dr. Boettiger added, “suggesting that stronger mental representations of long-term consequences enables more future-oriented decisions. Our results point to the lateral orbitofrontal cortex as a possible key site for such representations, and support identifying addiction therapies that strengthen orbitofrontal cortex activity during decision making.”

Funding for this research was provided by the Department of Defense and the Wheeler Center for the Neurobiology of Addiction. (J Neurosci. 2007;27(52):14383-14391.) –LS


Sleep Medications Often Denied to Insomnia Patients with Anxiety and Depression

Approximately 20% of the United States population has sleep problems, and every one out of 10 patients experiences chronic insomnia. Patients with insomnia usually endure other comorbidities such as depression and anxiety. According to a study by Rajesh Balkrishnan, PhD, of Ohio State University, and colleagues, patients who suffer from both insomnia and mental health disorders are denied sleep medication more often than those without mental health diagnoses.

The study involved a retrospective data analysis of the National Ambulatory Medical Care Survey. It recorded 5,487 physician visits by patients with insomnia between 1995 and 2004, a sample calculated to represent 161.4 million US patients. Approximately 38% of those surveyed were diagnosed with at least one other condition, including anxiety, episodic mood disorders, high blood pressure, depression, and diabetes. Patients with both insomnia and mental health disorders were 36% less likely to receive pharmacotherapy for insomnia while anxiety patients were 45% less likely. These results reveal that patients with these comorbid disorders are the lowest candidates for sleep medication. In addition, the findings suggest that physicians are tentative to prescribe sleep aids due to these patients’ higher risk of dependence and abuse, a groundless assumption that could lead to worsened mental health conditions.

Funding for this research was provided by a grant from sanofi-aventis. (J Med Econ. 2008;11(1):41-56.) –ML

Dispatches is written by Michelisa Lanche, Carlos Perkins, Jr., and Lonnie Stoltzfoos.


November 25, 2007

To the Editor:

A recent editorial addressing the side effects of psychotropic medications1 brings a welcomed focus on the deficiencies surrounding the present system of documenting and monitoring suspected postmarketing adverse events. Side effects attributed to selective serotonin reuptake inhibitors (SSRIs) have been extensively documented over the past 2 decades, but some distressing symptoms were initially unappreciated or underestimated due to reliance on voluntary reporting instead of direct interview or questionnaire.2 Because of the high degree of safety, efficacy, and tolerability of the SSRIs, primary care physicians (PCPs) commonly diagnose and treat uncomplicated cases of major depression without the patient ever presenting at the door of a mental health professional.3 While this has simplified access to antidepressant therapy for patients with limited healthcare resources, PCPs are frequently overburdened by large patient volumes and shrinking reimbursements, and relatively “minor” (non-life threatening) drug-related side effects may be easily minimized or overlooked.

Sexual side effects manifest in a variety of presentations and severities, but sexual functioning is assumed to return to normal once antidepressants are discontinued.4 In the recent peer-reviewed literature, three separate case reports5-7 have detailed sustained persistence of sexual dysfunction and genital anesthesia well after termination of SSRIs in the absence of residual psychopathology or another identifiable disorder. In each report, the annoying symptoms were absent prior to antidepressant therapy. Oddly, these case reports have not appeared in the psychiatric or psychopharmacology literature, but rather, two have been published in psychology journals5,6 and the third in a gynecology/women’s health journal.7

Additionally, a community of adults claiming persistence of the sexual symptoms well after termination of SSRIs has surfaced on the Internet.8 Their plight seems to have garnered little interest from the medical community or pharmaceutical industry. In addition to a case report by Kauffman and Murdock,7 this author has encountered another woman in a university-based consultative gynecologic practice with persistent post-treatment orgasmic dysfunction and diminished genital sensation following sertraline administration, but she refused to undergo psychological or neuro-endocrine evaluation. In the absence of a more comprehensive evaluation, a straightforward cause and effect relationship could not be reliably established.

Considering the documented cases already in peer-reviewed journals and self reports on the Internet (which are admittedly unsubstantiated), a formal post-marketing epidemiologic study of this vexing problem is overdue. The pharmaceutical industry is unlikely to undertake this task given the paucity of documented cases, the medico-legal implications, and potential economic fallout.

Introduction of SSRIs to the market has provided physicians with a powerful tool in the fight to allay human suffering, but if drug-related permanent aberrations of normal sexual response persist even in a small number of individuals, such findings should come to light. If those at risk can be identified in the future, utilization of alternatives to SSRIs could prevent long-term anguish and improve patient capacity for healthy sexual relationships.

Robert P. Kauffman, MD

Dr. Kauffman is associate professor, interim chairman, and director of Reproductive Medicine and Infertility in the Department of Obstetrics and Gynecology at Texas Tech University School of Medicine at Amarillo.

Disclosure: Dr. Kauffman reports no affiliation with or financial interest in any organization that may pose a conflict of interest.



1.    Sussman N. Side effects of psychotropic medications: importance of postmarketing surveillance. Primary Psychiatry. 2007;14(9):14-15.
2.    Zajecka J, Mitchell S, Fawcett J. Treatment-emergent changes in sexual function with selective serotonin reuptake inhibitors as measured with the Rush Sexual Inventory. Psychopharmacol Bull. 1997;33(4):755-760.
3.    Pirraglia P, Stafford R, Singer D. Trends in prescribing of selective serotonin reuptake inhibitors and other newer antidepressant agents in adult primary care. Prim Care Companion J Clin Psychiatry. 2003;5(4):153-157.
4.    Ferguson JM. The effects of antidepressants on sexual functioning in depressed patients: a review. J Clin Psychiatry. 2001;62(suppl 3):22-34.
5.    Bolton J, Sareen J, Reiss J. Genital anaesthesia persisting six years after sertraline discontinuation. J Sex Marital Ther. 2006;32(4):327-30.
6.    Csoka A, Shipko S. Persistent sexual side effects after SSRI discontinuation. Psychother Psychosom. 2006;75(3):187-188.
7.    Kauffman R, Murdock A. Prolonged post-treatment genital anesthesia and sexual dysfunction following discontinuation of citalopram and the atypical antidepressant nefazodone. Open Women’s Health Journal. 2007;1:1-3.
8.    Yahoo! Health. SSRIsex: Persistent SSRI sexual side effects. Available at: Accessed January 26, 2008.

Please send letters to the editor to Primary Psychiatry, c/o Norman Sussman, MD, 333 Hudson St., 7th Floor, New York, NY 10013; E-mail:




Print Friendly 

Gary J. Kennedy, MD

Primary Psychiatry.


Dr. Kennedy is professor in the Department of Psychiatry and Behavioral Sciences at Albert Einstein College of Medicine, and director of the Division of Geriatric Psychiatry at Montefiore Medical Center in the Bronx, New York.

Disclosure: Dr. Kennedy has received research support or honoraria from AstraZeneca, Eli Lilly, Forest, Janssen, Myriad, and Pfizer.

Please direct all correspondence to: Gary J. Kennedy, MD, Director, Department of Geriatric Psychiatry, MMC, 111 East 210th St, Klau One, Bronx, NY 10467; Tel: 718-920-4236; Fax: 718-920-6538; E-mail:



Treatment of bipolar depression is both a challenge and a paradox. It is a challenge because persistent disability and recurrence are common, and a paradox because antidepressants appear to be counterproductive. Although bipolar depression in late life is not common, the increasing number of older people in the population insures that primary care providers will confront the paradox. Data from the older adult segment of the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) study have yet to emerge, but a review of published studies offers considerable guidance. A combination of one or more mood stabilizers plus aggressive psychosocial intervention offers hope of more effective treatment.


Bipolar Depression Defined

Occurring in approximately 0.5% of the United States population, bipolar disorder type II is characterized by recurrent major depressive episodes (MDEs) interspersed with periods of hypomania.1 Hypomania is defined as a disturbance in which mood is persistently and abnormally elevated, irritable, or expansive for at least 4 days duration. Associated symptoms include grandiosity or inflated self-regard, decreased need for sleep, loquaciousness or pressured speech, flight of ideas, racing thoughts, distractibility, agitation, increased goal-directed activity, and increased pursuit of pleasures with high self-destructive potential. The symptoms represent an unequivocal, uncharacteristic, and socially disruptive change in behavior. The absence of psychosis and severe social impairment and the duration of symptoms less than one week distinguish hypomania from the mania of bipolar disorder type I.

Because the social disruption may be minimal, and some of the symptoms may even seem beneficial, past episodes of hypomania may be ignored or dismissed by the patient and family. MDEs also occur in bipolar disorder type I in which the occurrence of one or more manic episodes is the distinguishing diagnostic feature. And there are mixed states in which criteria for both mania and major depression are present. As a result, the term “bipolar depression” spans the spectrum of bipolar disorders. This broad rather heterogenous definition may explain why the array of proven treatments, especially for older patients, remains limited.


Aftermath of Bipolar Depression

Among older adults with bipolar disorder, mania is a more frequent cause of hospitalization than depression,2 but depression may account for more disability.3 Worse, the results of present treatment for older adults with bipolar disorders are not remarkably better than those recorded prospectively from 1959–1985.4 Indeed, few older people with the disorder experience a full functional recovery despite symptom remission. Perlis and colleagues5 prospectively assessed potential predictors of recurrent mood disturbance among 858 symptomatic patients who subsequently recovered from an episode of bipolar disorder. Of people followed for up to 2 years, nearly half experienced a recurrence. Further, depressive episodes were twice as frequent as manic. The proportion of days depressed or anxious in the preceding year as well as residual symptoms of depression or mania at recovery predicted a subsequent depressive episode. Proportion of days with elevated mood in the preceding year as well as residual symptoms of mania were associated with a shorter time to the recurrence of a manic, mixed, or depressive episode. Impairments in cognitive speed and executive dysfunction6,7 and changes in subcortical brain structures are common,8 further reducing the chances of return to full function.


Biomedical Interventions

Strakowski9 characterized the lack of data on bipolar depression by noting that nine agents are approved by the US Food and Drug Administration for the treatment of mania, but only two (quetiapine and the olanzepine/fluozetine combination) are approved specifically for bipolar depression. Table 1 displays the agents suitable for older adults with doses, precautions, and therapeutic levels. Ziprasidone and chlorpromazine were omitted due to cardiovascular hazards despite FDA approval for bipolar disorder. As seen in Table 1, several medications are approved for episodes of “mixed” mania and depression. Historically, off-label use of antidepressants for bipolar disorder has been common. However, numerous studies suggest that antidepressants may be counterproductive.


Sachs and colleagues3 sought to determine whether adding an antidepressant to a mood stabilizer (lithium or an antiepileptic) reduced symptoms of bipolar depression without increasing the risk of mania. They were also interested in the durability of recovery defined as a minimum of 8 weeks virtually free of depressive symptoms. Patients were randomized to receive a mood stabilizer plus either an antidepressant or placebo. Rates of treatment-emergent mania or hypomania were less among the mood stabilizer-only group. Similarly, slightly more than one quarter of those in the mood stabilizer-only group experienced a durable recovery compared to slightly less than one quarter among those who received an antidepressant as well. In neither case were the differences statistically significant. Thus, prescription on adjunctive treatment with an antidepressant conveyed no advantage above that observed for a mood stabilizer alone.

These data are similar to that of Nemeroff and colleagues10 who found that once lithium levels were 0.8 meq/liter, neither imipramine nor paroxetine conveyed any additional benefits for people with bipolar depression. Nierenberg and colleagues11 examined 66 bipolar patients in a current MDE who had not responded to adequate doses of mood stabilizers and at least one antidepressant. In an open-label study, the patients were randomly assigned to inositol, lamotrigine, or risperidone. Here again the primary outcome was an 8-week period virtually free of depressive symptoms. Although pair-wise comparisons did not reach statistical significance, the recovery rate, level of depressive symptoms, Clinical Global Impression, and Global Assessment of Functioning all favored lamotrigine. Even so, slightly less than one quarter of the lamotrigine group experienced a durable recovery.

Leverich and colleagues12 randomized bipolar depressed patients to a mood stabilizer plus either bupropion, sertaline, or venlafaxine. Depending on the agent and whether or not there was a past history of mania, 20% to 35% of patients experienced either treatment-emergent mania or hypomania. In less than 25% of patients was there a sustained response to the antidepressant without a switch into mania or hypomania. The lowest risk of a switch was found with bupropion, and the highest with venlafaxine. Goldberg and colleagues13 also tested the adjunctive antidepressant hypothesis among bipolar patients with mixed mania and depression. They found significantly higher mania symptom severity after 3 months of follow-up associated with antidepressant therapy compared to mood stabilizers alone. The addition of an antidepressant did not speed recovery.

Thus, the emerging consensus based on expert opinion9,14 published guidelines,15-17 and the STEP-BD reports12,13 is that mood stabilizers are preferable both for acute treatment and the prevention of recurrence in late-life bipolar depression. An algorithm based on the expert opinions of Hilty and colleagues17 and Dolder and colleagues18 appears in the Figure. The prescribing pathway is characterized more by off-label than FDA-approved indications. Beyond the initial step of prescribing either lithium or lamotrigine, next steps are dictated by the patient’s symptom profile. For episodes of depression in both bipolar types I and II where the patient’s history exhibits relatively less mania, the antidepressant bupropion is a reasonable addition. However, for instances characterized by mixed symptoms or more frequent episodes of mania, an atypical antipsychotic or a second mood stabilizer is advisable. Purely on the basis of side-effect profile and likelihood of drug interactions, lamotrigine would appear to be preferable to lithium, divalproex, and carbamazepine.




Electroconvulsive Therapy

Electroconvulsive therapy (ECT) has a long history in the treatment of mania,19 but the data for bipolar depression are minimal to nonexistent for seniors.20 Although cardiovascular complications and transient amnesia are the most frequent adverse reactions to ECT, ECT-induced mania has also been reported.21 Nonetheless, when bipolar depression is associated with life-threatening weight loss, suicidal intent, or refusal of life-saving medications (antiarrhythmics, insulin), or when pharmacotherapy proves ineffective or intolerable, ECT should be recommended.


Psychosocial Interventions

Evidenced-based psychosocial interventions for bipolar depression have grown in number and sophistication but mainly focused on younger rather than older adults. Intensive psychosocial interventions prevent hospitalization associated with recurrence22,23 and improve functional recovery.24 As implemented in the STEP-BD study, patients were randomized to collaborative care or one of thee intensive psychosocial interventions applied in three 30-minute sessions. People in the collaborative care condition received a self-care workbook, viewed an educational videotape, and were counseled on sleep monitoring and relapse prevention. The intensive psychosocial interventions included cognitive-behavioral therapy (CBT), interpersonal and social rhythms therapy (ISRT), and family-focused treatment (FFT).

In individual CBT, patients and therapists discussed behavioral activation exercises, problem solving, and cognitive restructuring, all meant to reverse negative self attributions and increase rewarding habits. In ISRT, interpersonal problems and difficulties maintaining a physiologically stable schedule of sleep, waking, and activity were examined with a goal of preventing destabilizing social and interpersonal situations. For people with at least one family member willing to participate, FFT focused on shared planning for relapse prevention, improved listening and communication, and problem solving skills. Compared to three sessions of collaborative/educational care, the improvements in relationship functioning and life satisfaction associated with the psychosocial interventions went beyond those expected from improvements in mood. Thus, the benefits were independent of improvements in mood. However, enthusiasm for these psychosocial interventions must be tempered by the frequency with which cognitive impairment accompanies bipolar disorder even when patients are euthymic.6,7 Cognitive remediation may be necessary in order to improve function in social roles and recreational activities.24



With the increase in the older adult population, primary care physicians and general psychiatrists will inevitably encounter the paradox and challenge of late-life bipolar depression. Data from the older adult segment of the STEP-BD study will add considerably to the empirical basis for treatment. Results from the Geriatric Bipolar Disorder study of late-life mania25,26 should provide guidance on the benefit versus burden comparison of lithium to divalproex for bipolar depression as well. In the meanwhile, inferences based on guidelines,15-17 the STEP-BP publications,12,13,22 and others27-29 provide considerable guidance for both biomedical and psychosocial interventions. Initial treatment should begin with a mood stabilizer. For people who remain symptomatic despite reaching adequate dose or therapeutic level, ongoing adjunctive therapy with a second mood stabilizer or an atypical antipsychotic may be superior to the addition of an antidepressant. Nonetheless, people with little or no history of mania may still benefit from an antidepressant.

Table 2 provides consumer and advocacy information. PP





1.  Mitchell PB, Wilhelm K, Parker G, Austin MP, Rutgers P, Malhi GS.. The clinical features of bipolar depression: a comparison with matched major depressive disorder patients. J Clin Psychiatry. 2001;62(3):212-216.
2.  Sajatovic M, Blow FC, Ignacio RV, Kales HC. New-onset bipolar disorder in later life. Am J Geriatr Psychiatry. 2005;13(4):282-289.
3.  Sachs GS, Nierenberg AA, Calabrese JR, et al. Effectiveness of adjunctive antidepressant treatment for bipolar depression. N Eng J Med. 2007;356(17):1711-1722.
4.  Angst J, Preisig M. Outcome of a clinical cohort of unipolar, bipolar, and schizoaffective patients. Results of a prospective study from 1959 to 1985. Schweiz Arch Neurol Psychiatr. 1995;146(1):17-23.
5.  Perlis RH, Ostacher MJ, Patel JK, et al. Predictors of recurrence in bipolar disorder: primary outcomes from the systematic Treatment Enhancement Program for Bipolar Disorders (STEP-BD). Am J Psychiatry. 2006;163(2):217-224.
6.  Gildengers AG, Butters MA, Chisholm D, et al. Cognitive functioning and instrumental activities of daily living in late-life bipolar disorder. Am J Geriatr Psychiatry. 2007;15(2);174-179.
7.  Murphy FC, Sahakian BJ, Rubinsztein JS, et al. Emotional bias and inhibitory control processes in mania and depression. Psychol Med. 1999;29(6):1307-1321.
8.  McDonald WM, Krishnan KR, Doraiswamy PM, Blazer DG. Occurrence of subcortical hyperintensities in patients with mania. Psychiatry Res. 1991;40(4):211-220.
9.  Strakowski SM. Approaching the challenge of bipolar depression: results from STEP-BD. Am J Psychiatry. 2007;164(9):1301-1303.
10.  Nemeroff CB, Evans DL, Gyulai L, et al. Double-blind, placebo controlled comparison of imipramine and paroxetine in the treatment of bipolar depression. Am J Psychiatry. 2001;158(6):906-912.
11. Nierenberg AA, Ostacher MJ, Calabrese JR, et al. Treatment-resistant bipolar depression: a STEP-BD equipoise randomized effectiveness trial of antidepressant augmentation with lamotriginne, inositol, or risperidone. Am J Psychiatry. 2006;163(2):210-216.
12. Leverich GS, Altshuler LL, Frye MA, et al. Risk of switch on mood polarity to hypomania or mania in patients with bipolar depression during acute and continuation trials of venlafaxine, sertraline, and bupropion as adjuncts to mood stabilizers. Am J Psychiatry. 2006;163(2):232-239.
13. Goldberg JF, Perlis RH, Ghaemi SN, et al. Adjunctive antidepressant use and symptomatic recovery among bipolar depressed patients with concomitant manic symptoms; findings from the STEP-BD. Am J Psychiatry. 2007;164(9):1348-1355.
14. Keck PE, McElroy SL, Nemeroff CB. Anticonvulsants in the treatment of bipolar disorder. J Neuropsychiatry Clin Neurosci. 1992;4(4):395-405.
15. Hirschfeld RMA: Guideline Watch: Practice Guideline for the Treatment of Patients With Bipolar Disorder. Arlington, VA: American Psychiatric Association. Available at: Accessed February 1, 2008
16. American Psychiatric Association. Practice guideline for the treatment of patients with bipolar disorder (revision). Am J Psychiatry. 2002;159(4 suppl):1-50.
17. Hilty DM, Leamon MH, Lim RF, Kelly RH, Hales RE. Diagnosis and treatment of bipolar disorder in the primary care setting: a concise review. Primary Psychiatry. 2006;13(7);77-85.
18. Dolder CR, Depp CA, Jeste DV. Biological treatments of bipolar disorder in later life. In: Sajatovic M, Blow FC, eds. Bipolar Disorder in Later Life. Baltimore, MD: Johns Hopkins Press; 2007:71-93.
19. Lisanby SH. Electroconvulsive therapy of depression. N Engl J Med. 2007;357(19):1939-1945.
20. Sackeim HA, Prudic J. Length of ECT course in bipolar and unipolar depression. J ECT. 2005;21(3):195-197.
21. Serby M. Manic reactions to ECT. Am J Geriatr Psychiatry. 2001;9(2):180.
22. Miklowitz DJ, George EL, Richards JA, Simoneau TL, Suddath RL. A randomized study of family-focused psychoeducation and pharmacotherapy in the outpatient management of bipolar disorder. Arch Gen Psychiatry. 2003;60(9):904-912.
23. Miklowitz DJ, Otto MW, Frank E, et al. Psychosocial treatments for bipolar depression: a 1-year randomized trial from the systematic treatment enhancement program. Arch Gen Psychiatry. 2007;64(4):419-426.
24. Miklowitz GJ, Otto MW, Frank E, et al. Intensive psychosocial intervention enhances functioning in patients with bipolar depression: results from a 9-month randomized controlled trial. Am J Psychiatry. 2007;164(9):1340-1347.
25. Acute pharmacotherapy of late-life mania (GERI-BD). Available at: Accessed February 1, 2008.
26. Young RC, Beyer J, Gyulai L, et al. A randomized controlled trial of acute treatments in late-life mania. Abstract presented at: the 6th International Meeting of the International Society of Bipolar Disorder; Pittsburgh, PA; June 2005.
27. Calabrese JR, Bowden CL, Sachs GS, Ascher JA, Monaghan E, Rudd GD. A double-blind placebo-controlled study of lamotrigine in outpatients with bipolar I depression. Lamical 602 Study Group. J Clin Psychiatry. 1999;60(2):79-88.
28. Thase ME, Macfadden W, Weisler RH, et al. Efficacy of quetiapine monotherapy in bipolar I and II depression: a double blind, placebo-controlled study (the BOLDER II study). J Clin Psychopharmacol. 2006;26(6):600-609.
29. Perlis RH, Welge JA, Vornik LA, Hirshfeld RM, Keck PE Jr. Atypical antipsychotics in the treatment of mania: a meta-analysis of randomized, placebo-controlled trials. J Clin Psychiatry. 2006;67(4):509-516.
30. National Alliance on Mental Illness. Avaiable at: Accessed February 1, 2008.
31. Depression and Bipolar Support Alliance. Available at: Accessed February 1, 2008.
32. The Geriatric Mental Health Foundation. Available at: Accessed February 12, 2008.

Needs Assessment:
Stigma against depressed people who abuse alcohol leads to inadequate assessment and management. The resulting poor care compromises prognosis and leads to relapse, engendering negative feelings from healthcare professionals. Teaching better attitudes and treating both conditions hopefully improves outcome, reduces suicide risk, and fosters professionalism.

Learning Objectives:
• Recognize stigma against people with alcoholism and depression.
• Teach better attitudes toward patients with alcoholism and depression.
• Educate residents and medical students about management of these disorders.
• Identify the need for simultaneous treatment of alcoholism and depression.
• Counter stigma in medical systems and in healthcare professionals to improve approach toward these patients, especially when facing concerns about suicide.

Target Audience: Primary care physicians and psychiatrists.

CME Accreditation Statement: This activity has been planned and implemented in accordance with the Essentials and Standards of the Accreditation Council for Continuing Medical Education (ACCME) through the joint sponsorship of the Mount Sinai School of Medicine and MBL Communications, Inc. The Mount Sinai School of Medicine is accredited by the ACCME to provide continuing medical education for physicians.

Credit Designation: The Mount Sinai School of Medicine designates this educational activity for a maximum of 3 AMA PRA Category 1 Credit(s)TM. Physicians should only claim credit commensurate with the extent of their participation in the activity.

Faculty Disclosure Policy Statement: It is the policy of the Mount Sinai School of Medicine to ensure objectivity, balance, independence, transparency, and scientific rigor in all CME-sponsored educational activities. All faculty participating in the planning or implementation of a sponsored activity are expected to disclose to the audience any relevant financial relationships and to assist in resolving any conflict of interest that may arise from the relationship. Presenters must also make a meaningful disclosure to the audience of their discussions of unlabeled or unapproved drugs or devices. This information will be available as part of the course material.

This activity has been peer-reviewed and approved by Eric Hollander, MD, chair and professor of psychiatry at the Mount Sinai School of Medicine, and Norman Sussman, MD, editor of Primary Psychiatry and professor of psychiatry at New York University School of Medicine. Review Date: February 20, 2008.

Drs. Hollander and Sussman report no affiliation with or financial interest in any organization that may pose a conflict of interest.

To receive credit for this activity: Read this article and the two CME-designated accompanying articles, reflect on the information presented, and then complete the CME posttest and evaluation. To obtain credits, you should score 70% or better. Early submission of this posttest is encouraged: please submit this posttest by March 1, 2010 to be eligible for credit. Release date: March 1, 2008. Termination date: March 31, 2010. The estimated time to complete all three articles and the posttest is 3 hours.

Dr. Surja is psychiatry addiction fellow, Dr. Talari is psychiatry extern, Dr. Nair is psychiatry extern, Mr. Mettu is medical student, and Dr. Lippmann is professor, all in the Department of Psychiatry at the University of Louisville School of Medicine in Kentucky.

Disclosure: The authors report no affiliation with or financial interest in any organization that may pose a conflict of interest.

Please direct all correspondence to: Steven B. Lippmann, MD, University of Louisville Hospital, ACB- First Floor Psychiatry Clinic, 550 S Jackson St, Louisville, KY 40202; Tel: 502-852-5859; Fax: 502-562-4044; Email:





Depression comorbid with alcohol abuse is common but often stigmatized. Suicide gestures and attempts are frequent in this population and are often followed by subsequent self-induced injury or death. However, physicians and other healthcare professionals may not always regard these dual diagnoses as seriously as they do other presentations. All physicians, including medical school faculty, should teach consideration of suicidal issues in depressed patients who abuse alcohol and be knowledgeable in the management of both conditions. A dualistic approach to evaluation and treatment is recommended. A coordinated, simultaneously delivered intervention for depression and alcohol abuse is important in developing optimal therapy.



Affective disorders are a group of common illnesses that sometimes result in suicide, the third leading cause of death in people between 15 and 34 years of age.1 Alcohol abuse is also prevalent and strongly associated with depression and suicide.2 People who abuse alcohol commonly become depressed, and individuals with affective symptoms often drink ethanol to self medicate.3 Death by suicide is approximately six times as likely in those who are alcohol abusers as compared to non-drinkers,4 and many suicide attempts are made while under the influence of alcohol.

When dual diagnosis patients present with suicidal complaints, the depth of their distress is often less uniformly addressed. At times, one or the other condition is not specifically considered in planning intervention.5 Furthermore, access to treatment for this comorbidity is limited6 and some physicians are not fully informed about therapeutic resources available in their community.7 These deficiencies should be corrected. Psychiatrists ought to seriously consider and provide treatment for suicidal concerns in all depressed people, especially those who abuse alcohol.

It is important that medical students and residents be made aware of these issues; doctors should also provide such guidance to other healthcare professionals.8 As a patient advocate, educators have a responsibility to teach a positive attitude toward clinical recognition of depression and alcohol abuse, the means of identifying those at risk for suicide, and management for both of these conditions.



Unfortunately, psychiatric patients and those with substance abuse are often met with scorn in our society. They are frequently stigmatized and considered to be weak or inadequate. Many medical professionals share this bias as well.9 Using counter-transference, they may sometimes view these disorders as a behavioral dysfunction, unworthy of medical attention. Such negativity affects healthcare quality even in the best hospitals. Lack of training, inadequate knowledge of resources, and administrative or insurance barriers to comprehensive treatment potentially compromise good care. Improved teaching could correct this deficiency.8,9 Education about the needs for treatment and the ethical responsibility for providing good health care should fortify the trainees with more zeal at patient advocacy. Subsequently, it would be an expectation that the medical staff, while now knowing the available options, would be empowered to make the extra effort to overcome difficulties and secure the proper interventions.


The Challenges of Comorbidity

The comorbidities of affective illnesses and abuse of ethanol are common. Diagnosis is often a challenge as these two disorders can mimic one another and compound dysfunction. In addition, depression compromises sobriety and alcoholism worsens mood. Having both of these conditions often creates a problem leading to rejection from appropriate treatment.9 For example, many psychiatric facilities may refuse to accept such patients saying that the person just needs to quit drinking.5 Similarly, substance abuse units occasionally deny care on the basis of the psychiatric needs preclude admission. Often, alcohol treatment is refused with the commentary that people taking mind-altering substances will not be admitted, even if they are suicidally depressed and require antidepressant pharmacotherapy. Treatment for both problems requires greater effort and therapeutic expertise than for a single pathology. This approach requires teaching consideration of both the mood component and the addictive problem; each one needs an individualized intervention, provided simultaneously. Some communities offer too few therapeutic options for these dually diagnosed cases. Even when services are available, they are hard to access and rarely well coordinated.6


Depression and Alcohol Abuse are Chronic Brain Disorders

Like many other ailments such as diabetes or hypertension, depression and abuse of alcohol are often chronic. Relapse is expected and frequent emergency room visits are the norm. Despite today’s healthcare trends of inpatient admissions being more difficult to secure, some patients who recurrently present in crisis are in need of hospital restabilization with sobriety and long-term clinical follow up. The chronicity of these disorders can be linked to their physiologic basis. This perspective is well supported by research but is contrary to beliefs about weakness of character or lack of will. Abnormal brain function is documented in both depression and alcohol abuse. For example, males with a family history of alcoholism reportedly have a tendency toward abnormal electroencephalograms that mimic those of recovering addicts,10 and also have a significantly heightened risk of abusing alcohol themselves. Positron emission tomography studies demonstrate central nervous system pathology in these conditions.11 Even though initially the decision to drink is voluntary, prolonged ethanol exposure further alters brain function, making abstinence difficult and inducing changes in mood, loss of control over drinking, and compulsive ingestion despite adverse consequences. Health care improves when it is recognized that these mood and substance abuse conditions are not a matter of simple unwillingness to change.

Understanding these concepts is important to change the way clinicians deal with these debilitating situations. Teaching these principles in medical schools and at healthcare facilities should result in a better appreciation for the need of addressing such issues and applying this knowledge clinically.8


Clinical Awareness

The three important factors leading to suicide attempts in depressed individuals include hopelessness, impulsiveness, and abuse of alcohol. The ingestion of ethanol increases dangerousness for suicide due to disinhibition, impaired cognition, and poor judgment. Intoxication, therefore, becomes an additional risk factor for depression, dysfunction, dyscontrol, and self harm. A full assessment of mood and substance abuse is important in designing a therapeutic regimen since depression and alcohol are so prominently associated with suicide attempts and/or completions. These approaches include matching patients to appropriate treatment programs.5 Trainees and hospital personnel should understand that suicidal behaviors could occur acutely or be a long-term, recurrent issue.8 Most people who commit suicide have seen a doctor within 1 month prior to their demise, and many completers have communicated suicidal plans to close relatives.12 Patients who become actively suicidal need psychiatric attention and may be difficult to manage in some residential or even inpatient substance abuse facilities. Additional concern is required as these individuals often experience deprived social supports, personal losses, and/or have access to lethal means of self harm.

Education must also be provided about detoxification, vitamin repletion, and the management of alcohol withdrawal. Safe detoxification is only the beginning of a comprehensive treatment plan. Faculty should assure thorough trainee knowledge of antidepressant therapies. Additional important approaches include anti-craving pharmaceuticals (eg, acamprosate or naltrexone) and adverse reaction-to-alcohol medicinals (eg, disulfiram) that complement behavioral interventions like Alcoholics Anonymous membership. Halfway houses and many other community outreach or support services are among other valuable therapeutic options. Such inclusive offerings enhance the likelihood of success.

The learning process begins when psychiatrists demonstrate this knowledge as compassionate role models in their own patient care while stressing the need for comprehensive treatment. One should know the appropriate resources available from outpatient clinics to residential and inpatient units. Beyond familiarity with the options, they must manage medical systems in negotiation with insurance companies or hospitals to procure patient-focused appropriate services.7 Trainees learn best when receiving consistent guidance and following examples set by their educators.8



The presence of alcohol abuse reduces the likelihood of compliance with therapy. A depressed person who feels hopeless is unlikely to follow an antidepressant or sobriety regimen since the efforts seem in vain. Hopelessness compromises attendance at psychotherapy or Alcoholics Anonymous meetings if recovery appears to be impossible. When depression and its associated symptoms are present, treatment is mandatory. For example, anyone with chronic insomnia would respond poorly to pharmacotherapies or psychotherapeutic interventions. These patients also may require altered doses of psychotropic medication since alcohol induces hepatic enzymes and can result in liver dysfunction. Interventions are frequently needed for social, occupational, or legal disruptions. These important psychosocial issues should be addressed along with applying appropriate medical treatments. In addition, substance abuse therapies must always be made available. Focusing on both illnesses facilitates recovery. Concern for suicidal issues among dual diagnoses cases should remain active. Since these patients have significant risk for self injury, assessment of suicide potential, with family involvement if possible, is mandatory. Aggressive treatment, hospitalization, or very careful outpatient monitoring is important with a positive, therapeutic approach individualized to the patients’ needs. Clinical educators can play an important role in diminishing negative thinking by demonstrating an affirmative behavioral attitude and guiding their trainees and coworkers to be receptive to such practice.8 Attentiveness to these concepts fosters a better outcome.



People with depression, suicidal concerns, and/or alcoholism are frequently stigmatized in our culture. Even physicians and other healthcare professionals can have such negative attitudes. This detrimental approach compromises dual diagnosis patient evaluations, treatment, and prognosis. These individuals should be carefully assessed, especially if they are suicidal, and both conditions should be vigorously treated. Countering stigma is an important goal and teaching better attitudes should be provided to all levels of trainees, healthcare workers, and our own colleagues. It is important to show respect to these individuals regardless of personal feelings. Hopefully, better attitudes by the medical team leads to improved patient care and greater professionalism. PP



1.    Sher L, Zalsman G. Alcohol and adolescent suicide. Int J Adolesc Med Health. 2005;17(3):197-203.
2.    Goldberg JF, Singer TM, Garno JL. Suicidality and substance abuse in affective disorders. J Clin Psychiatry. 2001;62(suppl 25):35-43.
3.    Weiss RD, Griffin ML, Mirin SM. Drug abuse as self-medication for depression: an empirical study. Am J Drug Alcohol Abuse. 1992;18(2):121-129.
4.    Harris EC, Barraclough B. Suicide as an outcome for mental disorders. A meta-analysis. Br J Psychiatry. 1997;170:205-228.
5.    Sciacca K. An integrated treatment approach for severely mentally ill individuals with substance disorders. In: Sciacca K, ed. New Directions For Mental Health Services. Hoboken, NJ: Jossey-Bass Publishers; 1991:69-84.
6.    Young NK, Grella CE. Mental health and substance abuse treatment services for dually diagnosed clients: results of a statewide survey of county administrators. J Behav Health Serv Res. 1998;5(1):83-92.
7.    Ridgely MS, Goldman HH, Willenbring M. Barriers to the care of persons with dual diagnoses: organizational and financing issues. Schizophr Bull. 1990;16(1):123-132.
8.    Lindberg M, Vergara C, Wild-Wesley R, Gruman C. Physicians-in-training attitudes toward caring for and working with patients with alcohol and drug abuse diagnoses. South Med J. 2006;99(1):28-35.
9.    Lauber C, Nordt C, Braunschweig C, Rössler W. Do mental health professionals stigmatize their patients? Acta Psychiatr Scand Suppl. 2006;(429):51-59.
10.    Rangaswamy M, Porjesz B, Chorlian DB, et al. Resting EEG in offspring of male alcoholics: beta frequencies. Int J Psychophysiol. 2004;51(3):239-251.
11.    Sher L, Milak MS, Parsey RV, et al. Positron emission tomography study of regional brain metabolic responses to a serotonergic challenge in major depressive disorder with and without comorbid lifetime alcohol dependence. Eur Neuropsychopharmacol. 2007;17(9):608-615.
12.    Robins E, Gassner S, Kayes J, Wilkinson RH Jr, Murphy GE. The communication of suicidal intent: a study of 134 consecutive cases of successful (completed) suicide. Am J Psychitary. 1959;15(8):724-733.


Needs Assessment: There is no agreed upon medical clearance process for patients who present to an emergency department with psychiatric complaints. There is often a difference of opinion regarding need for testing these patients. A medical clearance protocol utilized in this research used clinical criteria as a determinate for laboratory testing.

Learning Objectives:
• Understand the controversy concerning the medical clearance process for psychiatric patients in the emergency department.
• Review effectiveness of medical clearance protocol for use in psychiatric patients.
• Determine the need for testing of psychiatric patients evaluated in the emergency department.

Target Audience:
Primary care physicians and psychiatrists.

CME Accreditation Statement:
This activity has been planned and implemented in accordance with the Essentials and Standards of the Accreditation Council for Continuing Medical Education (ACCME) through the joint sponsorship of the Mount Sinai School of Medicine and MBL Communications, Inc. The Mount Sinai School of Medicine is accredited by the ACCME to provide continuing medical education for physicians.

Credit Designation: The Mount Sinai School of Medicine designates this educational activity for a maximum of 3 AMA PRA Category 1 Credit(s)TM. Physicians should only claim credit commensurate with the extent of their participation in the activity.

Faculty Disclosure Policy Statement: It is the policy of the Mount Sinai School of Medicine to ensure objectivity, balance, independence, transparency, and scientific rigor in all CME-sponsored educational activities. All faculty participating in the planning or implementation of a sponsored activity are expected to disclose to the audience any relevant financial relationships and to assist in resolving any conflict of interest that may arise from the relationship. Presenters must also make a meaningful disclosure to the audience of their discussions of unlabeled or unapproved drugs or devices. This information will be available as part of the course material.

This activity has been peer-reviewed and approved by Eric Hollander, MD, chair and professor of psychiatry at the Mount Sinai School of Medicine, and Norman Sussman, MD, editor of Primary Psychiatry and professor of psychiatry at New York University School of Medicine. Review Date: February 20, 2008.

Drs. Hollander and Sussman report no affiliation with or financial interest in any organization that may pose a conflict of interest.

To receive credit for this activity: Read this article and the two CME-designated accompanying articles, reflect on the information presented, and then complete the CME posttest and evaluation. To obtain credits, you should score 70% or better. Early submission of this posttest is encouraged: please submit this posttest by March 1, 2010 to be eligible for credit. Release date: March 1, 2008. Termination date: March 31, 2010. The estimated time to complete all three articles and the posttest is 3 hours.

Dr. Zun is chairman and professor of emergency medicine in the Department of Emergency Medicine at Rosalind Franklin University of Medicine and Science/Chicago Medical School and chairman in the Department of Emergency Medicine at Mount Sinai Hospital in Chicago, Illinois. Dr. Downey is assistant professor in Public Policy at Roosevelt University in Chicago.

Disclosure: Drs. Zun and Downey report no affiliation with or financial interest in any organization that may pose a conflict of interest.

Acknowledgments: The authors would like to thank Roma Hernandez for her assistance in data collection and Louis Shicker, MD for his review of the patients who were transferred to a psychiatric faculty. We wish to acknowledge the Medical Clearance Work Group: Carol Black, MD, Grace Carag, Lambros Chrones, MD, Willie Earley, MD, Chris Fichner, MD, Deepak Kapoor, MD, Bruce McNulty, MD, Jeff Schaider, MD, and Kristen Welch, MD.

Please direct all correspondence to: Leslie S. Zun, MD, Chair, Department of Emergency Medicine, Mount Sinai Hospital Medical Center, 15th and California, Chicago, IL 60608; Tel: 773-257-6957; Fax: 773-257-6447; E-mail:



Introduction: A protocol for the prospective evaluation of patients presenting to the emergency department with psychiatric complaints has been described but not tested. The purpose of this study is to validate a protocol for the medical clearance of patients with behavioral complaints.
Methods: A checklist based on the protocol for patients presenting with psychiatric complaints was applied to a prospective sample of patients. The inclusion criteria were patients with behavioral complaints seen in one of five test urban emergency departments transferred to a state-operated psychiatric hospital (SOPH). The exclusion criteria included patients transferred to other psychiatric facilities and those that were clinically intoxicated without other behavioral complaints. The test protocol was validated to the usual physicians’ medical clearance procedure. Patients who were transferred back to an emergency department within 7 days of admission to a psychiatry facility for 6 months in 2001 were compared to those in 2000. The study was approved by the Institutional Review Boards as exempt because it was considered data collection study.
Results: There were 401 patients who met criteria, were enrolled, and had the checklist completed from January 1, 2001–June 30, 2001. The protocol was completed in 60.9% (401 of 659 patients) of all eligible cases. A majority of the patients were males (66.7%), with known psychiatric condition (82.2%), without prior medical illness (87.3%), with normal vital signs (98.0%), with normal physical exam (91.0%), and with normal mental status (96.2%). Approximately half had laboratories ordered (49.9%) and approximately half of these tests were abnormal (51.3%). No significant difference was found in the number of patients sent back to an emergency department after transfer to an SOPH in the study periods. One patient transferred in 2001 as compared to three patients in 2000 was found to have medical conditions necessitating emergency care that was related or possibly related to the medical clearance process.
Discussion: The study demonstrated that the similar number of patients returned to an emergency department before and after the use of the protocol. This study did not answer many of the key questions concerning the use of a new evaluation protocol. Further study is needed to answer these questions.
Conclusion: The test protocol for medical clearance of psychiatric patients was found valid as compared to the usual medical clearance evaluation performed in the emergency department. Further studies in the cost and time savings with the use of this protocol is needed.



“Medical clearance” of psychiatric patients is the initial medical evaluation of patients in the emergency department whose symptoms appear to be psychiatric in origin, the purpose being to determine whether serious underlying medical illness exists which would render admission to a psychiatric facility unsafe or inappropriate. A protocol for the prospective evaluation of patients presenting to the emergency department with psychiatric complaints has been described but not tested.1 This medical clearance in the emergency department has not been standardized and is commonly fraught with problems.2

Weissberg3 commented on the fact that non-psychiatrists prematurely refer patients as “medically clear” because of their unfamiliarity or discomfort with psychiatric patients. Psychiatrists frequently require extensive testing on psychiatric patients in the emergency department to ensure that these patients do not need any acute medical intervention and to hide their discomfort with medical assessment.3-5 Emergency physicians believe that the emergency department evaluation should not be routine but should be tailored to the patient’s presentation.

In order to resolve these concerns, a team of emergency physicians and psychiatrists developed a consensus medical clearance protocol.1 The protocol for the evaluation of patients presenting with psychiatric symptoms standardizes the process and includes both a psychiatric assessment and clinically indicated physical assessment. The performance of any laboratory tests is the emergency physicians’ prerogative based on the clinical indications and not by routine.

This study examines the use of this written protocol for the “medical clearance” of patients who present to an emergency department with psychiatric complaints. The purpose of this study was to compare a standardized protocol for the medical clearance of patients with psychiatric complaints to the current procedure for medical clearance. The authors hypothesize that the number of missed medical conditions with the use of the protocol will be no worse than the numbers missed prior to the use of the protocol.



Study Setting and Population

The medical clearance checklist (Figure) was applied at five test urban emergency departments that varied in volume from 26,000 to >150,000 visits per year, and with 17–63 emergency department beds that included teaching and non-teaching hospitals from January to June 2001. These emergency departments transfer patients to three of the 10 state-operated psychiatric hospitals (SOPH) with an average bed size of 150 beds and 2,200 admissions per year.



Study Protocol

A medical clearance protocol was developed by a statewide team of psychiatrists and emergency physicians to establish an acceptable evaluation methodology for psychiatric patients who need hospitalization in a SOPH.1 The protocol was reviewed for content validity by a team of SOPH psychiatrists and emergency medicine medical directors of five test facilities that transfer patients to the SOPH. The protocol was based on a sound history of the present illness, unclothed physical examination, mental status evaluation, and clinically-guided laboratory testing. A checklist was developed from the protocol so the emergency physician could accurately complete the steps of this medical clearance protocol, so to provide adequate documentation for the medical clearance and to aid in the communication between the emergency physician and the psychiatrist (Figure). Normality of physical examination, vital signs, mental status, laboratories, and radiographics are determined by the emergency physician.

The checklist was to be used on all patients presenting to five test emergency departments with psychiatric complaints, in need of hospitalization in a SOPH. The exclusion criteria included those who were admitted to another psychiatric facility, drug or alcohol intoxication without other significant psychiatric illness, and individuals <18 years of age. The study was approved by the Institutional Review Boards as exempt.

The emergency physicians in the test emergency department were informed that the patients would only be accepted for transfer if the medical clearance checklist was completed in total and faxed to the SOPH. Patients from the non-test facilities used the traditional transfer process that includes communication of the patient’s condition and may include routine testing. SOPHs require that the emergency department transmits information concerning the mental disorder of the patient requiring admission as well as voluntary or emergency admission paperwork to the SOPH intake worker for his or her review and acceptance (personal communication, Illinois State Mental Hospitals, 2001).


Measurements or Key Outcome Measures

In order to compare the standardized protocol to the “gold standard,” the patients sent back from a SOPH to an emergency department within 7 days in the study year were compared to the number transferred in the prior year. The “gold standard” was considered the usual and customary practice that occurred as the evaluation process performed in the emergency department prior to initiation of the protocol. The authors of this study reviewed the charts of the returned patients to determine if the protocol missed diagnoses. The decision of related, unrelated, or indeterminate relatedness to medical clearance process was based on whether a test or process could have identified an existing medical condition that would have influenced the decision to transfer a patient.


Data Analysis

The checklists from all the test hospitals were collected and the data were abstracted and analyzed using the Statistical Package for the Social Sciences, version 10.6 Descriptives, frequencies, and correlations were computed from the data. Pearson coefficients and independent t-tests were performed on the data. Completion of the protocol was a checkmark in at least the first five questions. The use of t-test to determine any significant differences in equality of means was used to account for differences in outcomes from using the medical clearance checklist.



Of the 659 patients who met criteria, 401 were enrolled (60.9%) and had the checklist completed from January 1 2001 to June 30 2001; 16.4% (659 of 4,026 patients) of all patients transferred to a SOPH were from a test emergency department. All items in the protocol were completed in 55.6% (223 of 401) of patients.

A majority of the patients had known psychiatric condition (82.2%; 327 of 398), were without prior medical illness (87.3%; 240 of 275), had normal vital signs (98.0%; 388 of 396), exhibited normal physical exam (91.0%; 363 of 399), and showed normal mental status (96.2%; 375 of 390). Eighty-six of 401 (21.4%) were currently taking medication. The age range was 18–80 years with a mean age of 37 years.

Approximately half of the patients had laboratories evaluations (49.9%; 200 of 317) and in these patients approximately half of the reported test results were abnormal (51.3%; 79 of 154; 46 not documented). The most frequent laboratories ordered were urine toxicology (25.2%; 109 of 433), complete blood count (CBC; 22.4%; 97 of 433), and chemistries (23.3%; 101 of 433). When multiple tests were ordered, the most frequent combination of tests was urine toxicology and alcohol (23.3%; 44 of 189) as well as CBC, chemistries, urinalysis, and urine toxicology (22.8%; 43 of 189; Table 1). Radiographs were ordered in 12% (48 of 292) and were reported as normal in 85.4% (35 of 41; 7 not documented). In 13.5% (54 of 277), medical treatment was needed prior to medical clearance; 55.1% (86 of 245) were currently on medications. Continued medical treatment at the SOPH was required in eight of 375 patients.



The most frequent psychiatric diagnoses were depression (125), schizophrenia or psychosis (129), and suicidal ideation (79). Few patients had substance-induced mood disorder (1), dysthymia (1), panic disorder (1), posttraumatic stress disorder (1), or an eating disorder (1). The most frequent medical diagnoses were related to physical trauma (18), diabetes (12), asthma (9), and hypertension (8). Many patients had a history of alcohol or substance abuse (207)—most frequently cocaine (69), alcohol (67), and heroin (17).

There was no increase in the number of patients sent back to an emergency department after transfer to an SOPH in the study and comparative time periods (Table 2). One patient was transferred in 2001, as compared to three patients in 2000, that was found to have medical conditions that needed emergency care related or possibility related to the medical clearance process. These medical conditions included pain secondary to physical trauma (2), leg swelling (1), and seizure (1). One indeterminate case and nine unrelated patients were returned in 2001 and two indeterminate cases and four unrelated cases were returned in 2000.


The ordering of laboratory tests was correlated with obtaining radiographs (Pearson coefficient=.178, P=.002) and receiving medical treatment needed in the emergency department (Pearson coefficient=.263, P=.000), and currently taking medications (Pearson coefficient=.183, P=.039), but was not correlated with age, presentation of a new psychiatric condition, abnormal physical exam, or abnormal mental status examination (P<.05). Abnormal test results were correlated with the abnormal mental status examination (Pearson coefficient=.168, P=.04), obtaining radiographs (Pearson coefficient=.178, P=.002), medical treatment needed in the emergency department (Pearson coefficient=.263, P=.000), and those currently taking medications (Pearson coefficient=.183, P=.039), but was not correlated with age, presentation of a new psychiatric condition, or abnormal physical exam (P<.05).

Significant difference in outcome using the checklist was found if patients had a psychiatric diagnosis (95% CI .1344, 19.1156 sig .047), had any abnormal physical exam (95% CI -.4765, -3.08 sig .027), or had any abnormal mental status examination (95% CI -.4765, -2.35 sig .032). Significance was also found with the presentation of a new psychiatric condition (95% CI 9.99, 22.3 sig .03), medical diagnosis (95% CI .8496, 10.63 sig .02), patient’s age (95% CI -6.02, -.4551 sig .023), substance abuse diagnosis (95% CI 3.01, 2.39 sig .04), or the performance of radiographs (95% CI -.232, -2.22 sig .01).



This study is the first prospective study of the medical clearance of unselected adult emergency department patients with psychiatric complaints. The study demonstrated that a similar number of patients returned to an emergency department before and after the use of the protocol. This study did not answer many of the key concerns regarding the use of a new evaluation protocol, including whether the use of the protocol reduces cost, the throughput time and error rate of missed diagnoses while enhancing quality of care, the ease of transfer, or improved customer satisfaction. The authors of this article did not evaluate these criteria in the study protocol but further study is needed to answer these questions.

The protocol establishes the  standard  of  evaluation  of psychiatric patients and the role of the emergency  physician  in  the  evaluation  and  transfer of  psychiatric  patients. The protocol also deals with the information that the psychiatrists require on the chart prior to transfer. A few authors have written about the poor emergency department chart documentation of psychiatric patients.2,4 Riba and Hale4 found that only 33% of the patients had a history of present illness, 68% had vital signs, 8% had a complete neurologic exam, and none had a mental status examination documented on the chart.
The importance of performing a medical clearance of psychiatric patients in the emergency department is well established to screen patients with medical illnesses that may have caused or exacerbated their psychiatric illness.7-22 In order to detect those patients with medical conditions in need of treatment, many studies have recommended extensive testing.8-14,18,20,22 More recent retrospective studies of psychiatric patients who present to the emergency department did not recommend extensive testing of all psychiatric patients, rather most testing should be abandoned in favor of a more clinically driven and cost-effective process.23-30 Hennenman and colleagues,6 in a prospective study of patients with new onset of psychiatric symptoms, refined these guidelines and recommended a battery of tests for these patients. It is probable that patients with new-onset psychiatric illness will need a different work-up than those with known psychiatric illness.

The study was limited by the usual medical clearance process as the “gold standard” for comparative purposes since no other such standard is generally accepted. One could argue that this process is no standard at all, but no better medical clearance has been presented in the literature. The authors of this article did not perform any side-by-side comparison from year to year because the evaluation varied between institutions and doctors. The study examined only those patients from a test emergency department who transferred to a SOPH rather than to another institution. Although the protocol was mandated prior to transfer, the compliance and completeness of the protocol varied in the test emergency departments. There was no observation of the type of evaluation that was actually performed to determine if the protocol was followed. The protocol did not establish the need for selective laboratory testing being performed but removed the requirement for testing. Emergency physicians were asked if the patient had a normal mental status, although prior studies have determined that emergency physicians do not perform an adequate mental status examination.31 The mental status determination was primarily an evaluation of the patients’ cognitive abilities, an evaluation not usually performed by psychiatrists. The number of patients sent back from a state-operated facility was small before and after the implementation of the protocol, limiting the data analysis. The study was limited by the non-blinded nature of the reviews concerning the need to return patients to an emergency department. Satisfaction analyses of both the emergency physicians and psychiatrists in the use of the checklist and interactions with their colleagues would be valuable.

Many physicians did utilize the protocol, but still ordered tests based on their own routine or their presumption that the transferring facility will request such testing. The next step is to establish stricter treatment guidelines based on the protocol where testing is established by set criteria in the protocol rather than based on physician judgment. It is uncertain if a tool can be developed to reduce the number of patients who were inappropriately transferred to a psychiatric facility.

Future study is needed to confirm the findings of the pilot. The study would be a randomized, controlled trial where half receive the medical clearance protocol and the other half would be evaluated in the usual evaluation. The two patient groups could then be compared for demographics, examination performed, tests and procedures ordered, and outcome measures.



This pilot study demonstrated that this medical clearance protocol for patients with behavioral complaints was similar to the prior means of medical clearance. Further testing in various settings is necessary to determine if a broader applicability is possible. PP



1.    Zun LS, Leikin JB, Stotland NL, Blade L, Marks RC. A tool for the emergency medicine evaluation of psychiatric patients. Am J Emerg Med. 1996;14(3):3.
2.    Tintinalli JE, Peacock FW, Wright MA. Emergency medical evaluation psychiatric patients. Ann Emerg Med. 1994;23(4):859-862.
3.    Weissberg MP. Emergency room medical clearance: an educational problem. Am J Psychiatry. 1979;136(6):787-790.
4.    Riba M, Hale M. Medical clearance: Fact or fiction in the hospital emergency room. Psychosomatics. 1990;31(4):400-404.
5.    McIntyre JS, Romano J. Is there a stethoscope in the house and is it used? Arch Gen Psychiatry. 1977;34(10):1147-1151.
6.    SPSS Inc. Statistical Package for the Social Sciences. Version 10. Chicago, IL; 2001.
7.    Henneman PL, Mendoza R, Lewis RJ. Prospective evaluation of emergency department medical clearance. Annals Emerg Med. 1994;24(4):672-677.
8.    Thomas C. The Use of screening investigations in psychiatry. Br J Psychiatry. 1979;135:67-72.
9.    Roca RP, Breakey WR, Fisher PJ. Medical care of chronic psychiatric outpatients. Hosp Commun Psych. 1987;38(7):741-745.
10.    Hall RC, Popkin MK, Devaul RA, Faillace LA, Stickney SK. Physical illness presenting as psychiatric disease. Arch Gen Psych. 1978;35(11):1315-1320.
11.    Bunce DF, Jones LR, Badger LW, Jones SE. Medical illness in psychiatric patients: barriers to diagnosis and treatment. Southern Med J. 1982;75(8):941-944.
12.    Hall RC, Beresford TP, Gardner ER, Popkin MK. The medical care of psychiatric patients. Hosp Commun Psych. 1982;3(1):25-34.
13.    Ferguson B, Dudleston K. Detection of physical disorder in newly admitted psychiatric patients. Acta Psychiatr Scand. 1986;74(5):485-489.
14.    Hall RC, Gardner ER, Stickney SK, LeCann AF, Popkin MK. Physical illness manifesting as psychiatric disease II analysis of a state inpatient population. Arch Gen Psych. 1980;37(80):989-995.
15.    Koran L, Sox HC, Marton KI, et al. Medical evaluation of psychiatric patients I: results in a state mental health system. Arch Gen Psych. 1989;46(8):733-740.
16.    Koranyi EK. Morbidity and rate of undiagnosed physical illnesses in a psychiatric clinic population. Arch Gen Psych. 1979;36(4):414-419.
17.    Hoffman RS. Diagnostic errors in the evaluation of behavioral disorders. JAMA. 1982;248(8):964-967.
18.    Summers WK, Munoz RA, Read MR, Marsh GM. The psychiatric physical examination – Part II: findings in 75 unselected psychiatric patients. J Clin Psychiatry. 1981;42(3):99-102.
19.    Hall RC, Gardner ER, Popkin MK, Lecann AF, Stickney SK. Unrecognized physical illness prompting psychiatric admission: a prospective study. Am J Psychiatry. 1981;138(5):629-635.
20.    Beresford TP, Hall RC, Wilson FC, Blow FB. Clinical laboratory data in psychiatric outpatients. Psychosomatics. 1985;26(9):731-741.
21.    Herridge CF. Physical disorders in psychiatric illness. A study of 209 consecutive admissions. Lancet. 1960;(2)949-951.
22.    McHugh P. William Osler and New Psychiatry. Ann Intern Med. 1987;107(6):914-8.
23.    Korn CS, Currier GW, Henderson SO. Medical clearance of psychiatric patients without medical complaints in the emergency department. J Emerg Med. 2000;18(2):173-176.
24.    Williams ER, Shepherd SM. Medical clearance of psychiatric patients. Emerg Med Clin North Am. 2000;18(2):173-176.
25.    Allen MH, Currier GW. Medical assessment in the psychiatric service. New Dir Ment Health Serv. 1999;82(82):21-28.
26.    McCourt JD, Weller JP, Broderick KB. Mandatory laboratory testing for emergency department (ED) psychiatric medical screening exam (PMSE): useful or useless? [abstract]. Acad Emerg Med. 2001;8(8):572-573.
27.    Olshaker JS, Browne B, Jerrard DA, Prendergast H, Stair TO. Medical clearance and screening of psychiatric patients in the emergency department. Acad Emerg Med. 1997;4(2):124-128.
28.    Allen MH, Currier GW. Medical assessment in the psychiatric emergency service. New Dir Ment Health Serv. 1999;82:21-28.
29.    Johnson DW. The evaluation of routine physical examination in psychiatric cases. Practitioner. 1968;200:686-691.
30.    Dolan JG, Mushlin AL. Routine laboratory testing for medical disorders in psychiatric inpatients. Arch Intern Med. 1985;145(11):2085-2088.
31. Zun LS, Gold I. A survey of the form of the mental status examination administered by emergency physicians. Ann Emerg Med. 1986 Aug;15(8):916-922.






Dr. Sussman is editor of Primary Psychiatry and professor of psychiatry at the New York University School of Medicine in New York City.


Dr. Sussman reports no affiliation with or financial interest in any organization that may pose a conflict of interest.


This issue of  Primary Psychiatry covers a broad range of topics. Anton A. Subuh Surja, MD, and colleagues address the prevalent stigmatization of depressed people who also abuse alcohol. They note that depression comorbid with alcohol abuse is common. As a consequence of this stigma, these dual-diagnoses patients receive inadequate assessment and treatment, which in turn compromises prognosis and leads to relapse. The authors note that alcohol and other substance abusers tend to engender negative feelings from healthcare professionals. Underlying mood disorders, if undiagnosed and unmanaged, can result in suicide. Thus, there is a need to teach better attitudes that improve outcomes and foster professionalism. Among many points made in the article, the authors note that when depression and its associated symptoms are present, treatment of depression is mandatory. Patients may require altered doses of psychotropic medication since alcohol induces hepatic enzymes and can result in liver dysfunction. Interventions for social, occupational, or legal disruptions may be needed. Substance abuse therapies must always be made available.

Ian A. Cook, MD, describes how “advances in understanding the machinery of the brain and how it is altered in disorders of the mind” may soon lead to the identification of clinical biomarkers that can be used to make a diagnosis and predict prognosis or response to treatment. He provides illustrative examples drawn from studies of physiologic measures in mood disorders, and reviews pragmatic aspects of evaluating biomarker technologies that may lead to the development and possible adoption of these techniques.


Surprisingly, according to Leslie S. Zun, MD, MBA, and LaVonne Downey, PhD, there is no agreed upon medical clearance process for patients who present to an emergency department with psychiatric patients. They note that there is often a difference of opinion regarding the need for testing these psychiatric patients. The authors describe and present the results of a study designed to validate a protocol for the medical clearance of patients with behavioral complaints. A checklist based on the protocol for patients presenting with psychiatric complaints was applied to a prospective 401 patients who met criteria. The study found the protocol for medical clearance of psychiatric patients to be valid as compared to the usual medical clearance evaluation performed in the emergency department.


Also in this issue is the second of a two-part adaptation of a reference guide by Jeffrey L. Cummings, MD, focusing on the treatment of Alzheimer’s disease and other dementias. Included in this month’s educational review is the expansion of diagnostic approaches to include more mild syndromes, such as mild cognitive impairment, as information is needed to manage patients using the latest advances. The presentations and discussions in these articles are deliberately concise and full of tables that should facilitate diagnostic and treatment decisions.


Also included in this issue is a Letter to the Editor from Robert Kauffman, MD, who addresses one of my recent editorials,1 and calls attention to recent peer-reviewed literature—three separate case reports of sustained persistence of sexual dysfunction and genital anesthesia after discontinuation of selective serotonin reuptake inhibitor (SSRI) treatment. He also references a Website2 of former SSRI users who have experienced this previously unrecognized adverse event. Dr. Kauffman describes a woman with persistent post-treatment orgasmic dysfunction and diminished genital sensation following sertraline administration and suggests that efforts be made to prevent long-term impairment of sexual functioning. PP






1.    Sussman N. Side effects of psychotropic medications: importance of postmarketing surveillance. Primary Psychiatry. 2007;14(9):14-15.
2.    Yahoo Health Groups. SSRIsex · Persistent SSRI sexual side effects. Available at: Accessed February 18, 2008.


Dr. Cummings is the Augustus S. Rose Professor of Neurology, professor of psychiatry and biobehavioral sciences, director of the Mary S. Easton Center for Alzheimer Research at the University of California, Los Angeles (UCLA), and director of the Deane F. Johnson Center for Neurotherapeutics at the David Geffen School of Medicine at UCLA.

Disclosures: Dr. Cummings has served as a consultant for Acadia, Adamas, Astellas, Avanir, CoMentis, Eisai, EnVivo, Forest, Janssen, Lundbeck, Medivation, Merck, Merz, Myriad, Neurochem, Novartis, Ono, Pfizer, Prana, Sanofi-Aventis and Takeda. Dr. Cummings owns the copyright of the Neuropsychiatric Inventory. Dr. Cummings has been supported by a National Institute on Aging Alzheimer Disease Center grant (P50 AG 10157), an Alzheimer’s Disease Research Center of California grant, the Sidell-Kagan Foundation, and the August Rose Chair of the University of California.

Acknowledgments: Dr. Cummings thanks his colleagues at the UCLA Alzheimer Disease Center and the patients and caregivers who have given meaning to his commitment to find more effective treatments for Alzheimer’s Disease. He also thanks his wife Kate (Xue) Cummings (Zhong) without whose enthusiasm, love, and support this project would have been impossible.

Please direct all correspondence to: Please direct all correspondence to: Jeffrey L. Cummings, MD, Alzheimer Disease Center, 10911 Weybrun Ave, #200, Los Angeles, CA 90095-7226; Tel: 310-794-3665; Fax: 310-794-3148; E-mail:


Focus Points

• Alzheimer’s disease is the most common cause of dementia in the elderly.
• Clinical features and diagnostic criteria help identify dementia and related syndromes.
• Antidementia therapies, management of behavioral symptoms, and family counseling assist in the treatment of dementia and related syndromes.



This educational review is the second of a two-part adaptation of an ultra-quick reference guide useful in the diagnosis and treatment of Alzheimer’s disease and other dementias (The Black Book of Alzheimer’s Disease. J.L. Cummings, MD, 2008, publication pending). The classification of dementia, the expansion of diagnostic approaches to include more mild syndromes such as mild cognitive impairment (MCI), and the rapid evolution of new therapies make it difficult to remain informed about all critical progress relevant to Alzheimer’s disease and related conditions. These two articles provide information needed to manage patients using contemporary advances in diagnosis and management. They will be updated annually in the form of a Black Book to ensure that the information remains current.

This educational review is not intended as a comprehensive reference. It provides critical information only. The first part provided references and Websites where more information can be found on each topic presented. This second part emphasizes criteria-based diagnosis and optimizing pharmacotherapy. The set of diagnostic criteria provided in this educational review is among the most comprehensive available. However, the presentations and discussions have been kept deliberately short, as the purpose is not to serve as a comprehensive review but to provide information critical to patient care embedded in enough context to make management decisions coherent and logical.

Alzheimer’s disease research is forging ahead rapidly toward new therapies and the possibility of disease-modifying interventions. The context of these therapies is provided in the pathophysiology section of the text and the forward-looking therapies are introduced in the antidementia therapy section.


Clinical Features and Diagnostic Criteria for Dementias and Related Syndromes

Differential Diagnosis of Cognitive Impairment

The differential diagnosis of cognitive impairment include depression, delirium, MCI, and a variety of common and uncommon dementia syndromes (Figures 1–3).1,2 Distinctive mental status, neuropsychiatric, neurologic, and imaging manifestations assist in differential diagnosis. Data are collected to determine if patients meet diagnostic criteria for specific neurologic disorders. Research diagnostic criteria are provided here to assist the clinician in diagnosis and differential diagnosis.

Mild Cognitive Impairment

MCI refers to patients who have cognitive impairment greater than age- and education-matched healthy elderly but do not meet diagnostic criteria for Alzheimer’s disease or any dementia. The patient or family member is aware of cognitive decline, the patient does not have impaired activities of daily living, and the patient does not meet criteria for dementia. Most patients with MCI progress to a dementia syndrome within 3 years; however, some remain with MCI for long periods of time and some recover. The amnestic form of MCI (disproportionate memory impairment) is often the prodrome of dementia of the Alzheimer type. Patients with amnestic MCI progress to diagnosable dementia of the Alzheimer type at a rate of 12% to 15% annualy. Nonamnestic forms of MCI may presage Alzheimer type dementia or other types of dementia. Alzheimer’s disease progresses from an asymptomatic phase to MCI to Alzheimer type dementia as the burden of pathology increases (Figure 4).


Dementia Syndromes

Dementia syndromes comprise memory impairment, decline in at least one other cognitive domain, deterioration from a higher level of function, and sufficient cognitive impairment to interfere with activities of daily living. The disorder cannot be present exclusively during a delirium.

Specific diagnostic criteria assist in identifying individual types of dementia syndromes (Figures 5 and 6; Tables 1-27).3-19 Dementia of the Alzheimer type, vascular dementia, frontotemporal dementia, prion disorders (eg, Creutzfeldt-Jakob disease), and dementia with various types of parkinsonism are the major diagnostic categories to be identified.

































Antidementia Therapies

Current Treatment Approaches

Currently available antidementia therapies include cholinesterase inhibitors and the (NMDA) receptor antagonist, memantine. Tables 29–34 provide comprehensive prescribing and side-effect monitoring information.


Emerging Therapies

Alzheimer’s disease research has identified plausible targets for new symptomatic and disease-modifying treatment. Some of these agents are in advanced stages of clinical testing. The steps of the amyloid cascade comprise one set of pharmacologic targets, and neuroprotective approaches comprise an alternate treatment strategy (Figures 7–10; Tables 28-35).















Management of Behavioral Symptoms in Dementia

Behavioral changes and neuropsychiatric symptoms are among the most disabling manifestations of Alzheimer’s disease and other dementias. Behavioral disturbances are a great source of distress for patients and caregivers, decrease quality of life, may precipitate institutionalization, and increase the cost of care.


Nonpharmacologic Management

Nonpharmacologic approaches to management of neuropsychiatric symptoms may obviate the need for pharmacotherapy or may decrease the necessary dose or length of time required for pharmacologic intervention.


Pharmacologic Management

There are no medications approved by the FDA specifically for the treatment of behavioral symptoms in patients with dementia. There have been relatively few masked, placebo-controlled trials to provide evidence-based guidance for pharmacotherapy of neuropsychiatric symptoms in dementia (Figures 11 and 12; Tables 36–44; Figures 13–15; Tables 45 and 46).20-25























Family Counseling

Families provide most of the care to patients with Alzheimer’s disease and other dementias. Even after the patient is resident in a nursing home, families continue to visit often and provide some of the care. Caregiving is associated with increased medical illness, psychological stress, and substance (eg, alcohol, tranquilizers) use. Caregiver burden may lead to caregiver “burnout,” with an inability to continue to provide care. Optimal care of dementia patients requires developing an alliance with the family and referring family members to community resources.26-45

Practical strategies useful in working with families include educating families about the course of Alzheimer’s disease, what to expect over time, and how best to manage the patient and their own response; referring to the Alzheimer Association or other advocacy organizations to identify local resources for patients and families; monitoring the caregiver for “burnout” and recommending respite care or day care as needed; and providing culturally competent care recognizing the cultural individuality of patients and families. PP




1.    Winblad B, Palmer K, Kivipelto M, et al. Mild cognitive impairment–beyond controversies, towards a consensus: report of the International Working Group on Mild Cognitive Impairment. J Intern Med. 2004;256(3):240-246.

2.    Cairns NJ, Bigio EH, Mackenzie IR, et al. Neuropathologic diagnostic and nosologic criteria for frontotemporal lobar degeneration: consensus of the Consortium for Frontotemporal Lobar Degeneration. Acta Neuropathol. 2007;114(1):5-22.

3.    Diagnostic and Statistical Manual of Mental Disorders. 4th ed. Washington, DC: American Psychiatric Association; 1994.

4.    Diagnostic and Statistical Manual of Mental Disorders. 4th ed, text rev. Washington, DC: American Psychiatric Association; 2000.

5.    Mendez MF, Ghajarania M, Perryman KM. Posterior cortical atrophy: clinical characteristics and differences compared to Alzheimer’s disease. Dement Geriatr Cogn Disord. 2002;14(1):33-40.

6.    McMonagle P, Deering F, Berliner Y, Kertesz A. The cognitive profile of posterior cortical atrophy. Neurology. 2006;66(3):331-338.

7.     Whitwell JL, Jack CR, Kantarci K, et al. Imaging correlates of posterior cortical atrophy. Neurobiol Aging. 2007;28(7):1051-1061.

8.    McElroy SL. Keck PE Jr, Pope HG Jr, Smith JM, Strakowski S. Compulsive buying: a report of 20 cases. J Clin Psychiatry. 1994;55(6):242-248.

9.    Voon V, Fox SH. Medication-related impulse control and repetitive behaviors in Parkinson’s disease. Arch Neurol. 2007;64(8):1089-1096.

10.    Giovannoni G, O’Sullivan JD, Turner K, Manson AJ, Lees AJ. Hedonistic homeostatic dysregulation in patients with Parkinson’s disease on dopamine management therapies. J Neurol Neurosurg Psychiatry. 2000;68(4):423-428.

11.    Nirenberg MJ, Waters C. Compulsive eating and weight gain related to dopamine agonist use. Mov Disord. 2006;21(4):524-529.

12.    Evans AH, Katzenschlager R, Paviour DC, et al. Punding in Parkinson’s disease: its relation to the dopamine dysregulation syndrome. Mov Disord. 2004;19(4):397-405.

13.    Voon V, Fox SH. Medication-related impulse control and repetitive behaviors in Parkinson’s disease. Arch Neurol. 2007;64(8):1089-1096.

14.    Lang AE, Riley DE, Bergeron C. Cortico-basal ganglionic degeneration. In: Calne DB, ed. Neurodegenerative Diseases. Philadelphia, PA: W.B. Saunders; 1994:877-894.

15.    Kumar R, Bergeron C, Pollanen MS, Lang AE. Cortical basal ganglionic degeneration. In: Jankovic J, Tolosa E, eds. Parkinson’s Disease and Movement Disorders. Baltimore, MD: Williams and  Wilkins; 1998:297-316.

16.    McKeith IG, Dickson DW, Lowe J, et al. Diagnosis and management of dementia with Lewy bodies: third report of the DLB consortium. Neurology. 2005;65(12):1863-1872. Erratum in: Neurology. 2005;65(12):1992.

17.    Litvan I, Agid Y, Calne D, et al. Clinical research criteria for the diagnosis of progressive supranuclear palsy (Steele-Richardson-Olszewski syndrome): report of the NINDS-SPSP international workshop. Neurology. 1996;47(1):1-9.

18.    Nomenclature and research case definitions for neurologic manifestations of human immunodeficiency virus-type 1 (HIV-1) infection. Report of a working group of the American Academy of Neurology Aids Task Force. Neurology. 1991;41(6):778-785.

19.    Vonsattel JP, Myers RH, Hedley-Whyte ET, Ropper AH, Bird ED, Richardson EP Jr. Cerebral amyloid angiopathy without and with cerebral hemorrhages: a comparative histological study. Ann Neurol. 1991;30(5):637-649.

20.    Jeste DV, Blazer D, Casey D, et al. ACNP White Paper: update on use of antipsychotic drugs in elderly persons with dementia. Neuropsychopharmacology. 2007 Jul 18 [Epub ahead of print].

21.    Schneider LS, Dagerman KS, Insel P. Risk of death with atypical antipsychotic drug treatment for dementia. JAMA. 2005;294(15):1934-1943.

22.    Wang PS, Schneeweiss S, Avorn J, et al. Risk of death in elderly users of conventional vs. atypical antipsychotic medications. N Engl J Med. 2005;353(22):2335-2341.

23.    Miyasaki JM, Martin W, Suchowersky O, Weiner WJ, Lang AE. Practice parameter: initiation of treatment for Parkinson’s disease: an evidence-based review: report of the Quality Standards Subcommittee of the American Academy of Neurology. Neurology. 2002;58(1):11-17.

24.    Pahwa R, Factor SA, Lyons KE, et al. Practice parameter: treatment of Parkinson disease with motor fluctuations and dyskinesia (an evidence-based review): report of the Quality Standards Subcommittee of the American Academy of Neurology. Neurology. 2006;66(7):983-995.

25.    Miyasaki JM, Shannon K, Voon V, et al. Practice parameter: evaluation and treatment of depression, psychosis, and dementia in Parkinson disease (an evidence-based review): report of the Quality Standards Subcommittee of the American Academy of Neurology. Neurology. 2006;66(7):996-1002.

26.    Alzheimer’s Association. Available at: Accessed February 6, 2008.

27.    Alzheimer’s Disease International (ADI). Available at: Accessed February 6, 2008.

28.    Alzheimer’s Foundation of America. Available at: Accessed February 6, 2008.

29.    American Stroke Association. Available at: Accessed February 6, 2008.

30.    Brain Injury Association of America. Available at: Accessed February 6, 2008.

31.    Clinical Trials. Available at: Accessed February 6, 2008.

32.    Deane F. Johnson Center for Neurotherapeutics at UCLA. Available at: Accessed February 6, 2008.

33.    The Association for Frontotemporal Dementias. Available at: Accessed February 6, 2008.

34.    Leeza Gibbons Memory Foundation. Available at: Accessed February 6, 2008.

35.    Lewy Body Dementia Association. Available at: Accessed February 6, 2008.

36.    National Institute on Aging. Available at: Accessed February 6, 2008.

37.    National Parkinson Foundation. Available at: Accessed February 6, 2008.

38.    National Stroke Association. Available at: Accessed February 6, 2008.

39.    Parkinson’s Disease Foundation. Available at: Accessed February 6, 2008.

40.    Progressive Supranuclear Palsy Association (Europe). Available at: Accessed February 6, 2008.

41.    Society for Progressive Supranuclear Palsy. Available at: Accessed February 6, 2008.

42.    UCLA Alzheimer Disease Center. Available at: Accessed February 6, 2008.

43.    American Academy of Neurology. Available at: Accessed February 6, 2008.

44.    Alzheimer Research Forum. Available at: Accessed February 6, 2008.

45.    Food and Drug Administration. Available at: Accessed February 6, 2008.


Needs Assessment: Recent research advances have raised the potential for clinical application of biomarkers in psychiatric care. It is important for clinicians to understand not only the benefits that biomarkers may bring to practice, but also the needed scientific hurdles these advances should clear before they can be embraced by the field.

Learning Objectives:

• Describe what biomarkers may be able to contribute to care for mental illnesses.
• Discuss proposed characteristics of a clinically-appropriate biomarker in psychiatry.
• Evaluate the applicability of potential biomarkers to patient care.

Target Audience: Primary care physicians and psychiatrists.

CME Accreditation Statement:
This activity has been planned and implemented in accordance with the Essentials and Standards of the Accreditation Council for Continuing Medical Education (ACCME) through the joint sponsorship of the Mount Sinai School of Medicine and MBL Communications, Inc. The Mount Sinai School of Medicine is accredited by the ACCME to provide continuing medical education for physicians.

Credit Designation:
The Mount Sinai School of Medicine designates this educational activity for a maximum of 3 AMA PRA Category 1 Credit(s)TM. Physicians should only claim credit commensurate with the extent of their participation in the activity.

Faculty Disclosure Policy Statement:
It is the policy of the Mount Sinai School of Medicine to ensure objectivity, balance, independence, transparency, and scientific rigor in all CME-sponsored educational activities. All faculty participating in the planning or implementation of a sponsored activity are expected to disclose to the audience any relevant financial relationships and to assist in resolving any conflict of interest that may arise from the relationship. Presenters must also make a meaningful disclosure to the audience of their discussions of unlabeled or unapproved drugs or devices. This information will be available as part of the course material.

This activity has been peer-reviewed and approved by Eric Hollander, MD, chair and professor of psychiatry at the Mount Sinai School of Medicine, and Norman Sussman, MD, editor of Primary Psychiatry and professor of psychiatry at New York University School of Medicine. Review Date: February 20, 2008.

Drs. Hollander and Sussman report no affiliation with or financial interest in any organization that may pose a conflict of interest.

To receive credit for this activity: Read this article and the two CME-designated accompanying articles, reflect on the information presented, and then complete the CME posttest and evaluation. To obtain credits, you should score 70% or better. Early submission of this posttest is encouraged: please submit this posttest by March 1, 2010 to be eligible for credit. Release date: March 1, 2008. Termination date: March 31, 2010. The estimated time to complete all three articles and the posttest is 3 hours.

Dr. Cook is director of the Depression Research Program at the University of California, Los Angeles (UCLA) and associate director of the UCLA Laboratory of Brain, Behavior, and Pharmacology at the Semel Institute for Neuroscience and Human Behavior.

Disclosure: Dr. Cook receives grant support from Aspect Medical Systems, Cyberonics, Eli Lilly, Hi Q Foundation, the National Institutes of Health, Novartis, Pfizer, and Sepracor; and is on the speakers’ bureaus of Bristol-Myers Squibb, the Medical Education Speakers Network, and Wyeth. Dr. Cook is co-inventor of the cordance method, and his patent rights have been assigned to and are owned by the Regents of the University of California.

Acknowledgments: Dr. Cook wishes to acknowledge the mentoring of Dr. Andrew Leuchter; collegial discussions with Dr. Aimee Hunter and technical assistance from Ms. Kelly Nielson in the preparation of this manuscript; and the support of the professional staff at the UCLA Depression Research Program and the UCLA Laboratory of Brain, Behavior, and Pharmacology at the Semel Institute.

Please direct all correspondence to: Ian A. Cook, MD, UCLA Depression Research Program, Semel Institute, 760 Westwood Plaza, Los Angeles, CA 90024-1759; Tel: 310-825-0304; Fax: 310-825-7642; E-mail:; Website:




Advances in fundamental neurobiology, neuroimaging, neurophysiology, behavioral genetics, and other current high-throughput “omics” fields have yielded considerable advances in understanding the machinery of the brain and how it is altered in disorders of the mind. A recurrent theme for several decades of psychiatric research has been an interest in clinical biomarkers, namely, those biologic features that inform diagnosis, prognosis, or response to treatment. Recent research findings have increased the visibility of several promising biomarker approaches; some illustrative examples are drawn from studies of physiologic measures in mood disorders. The potential for biomarkers to advance the care of mental illness is great, but several caveats must be considered in order to avoid pitfalls that prevent adoption by the field. Pragmatic aspects of evaluating biomarker technologies are proposed that may guide useful development and possible adoption of these techniques.



Biomarkers are commonplace in most branches of medicine: specific biologic features of an individual patient provide critical information about that person’s diagnosis, prognosis, or predicted response to treatment. Examples include tumor markers in oncology,1-4 troponin in cardiology,5-7 a-feto-protein in obstetrics,8 and inflammatory markers and specific serum antibody levels in rheumatology.9 Additionally, the use of biomarkers may be useful in drug discovery and development, by monitoring response to a test exposure of an experimental medication.10 Nonetheless, in the field of psychiatry, the biologic features of a patient’s illness generally continue to be eclipsed by the central role played by clinical signs and symptoms.11

While numerous new research findings suggest that biomarkers may soon be suitable for clinical use in psychiatric disorders, the quest for biomarkers to improve the care of mental illnesses is not new in the 21st century. For several decades, measurements of specific molecules in cerebrospinal fluid (eg, homovanillic acid, 5-hydroxy-indoleacetic acid),12 metabolites of neurotransmitters in urine (eg, 3-methoxy-4-hydroxyphenylglycol),13 and serum markers of neuroendocrine dysregulation (dexamethasone suppression test)14,15 have been complemented by studies of sleep architecture,16,17 eye movement abnormalities,18,19 and electrodermal and other autonomic responses.20 Other recent investigations have used imaging methods to detect the presence and location of abnormal proteins21,22  or abnormal organization of white matter tissue,23 to monitor neurochemistry with spectroscopy,24 or to detect brain metabolic responses to cognitive “stress tests.”25 While these approaches greatly expanded knowledge of the neurobiology of psychiatric disorders by serving as research tools, they have unfortunately found limited application in daily clinical practice or in evidence-based practice guidelines.11,26 As biologic measures (“biomeasures”26) and new techniques are reported and considered for use as clinically-applicable biomarkers, it is important for clinicians to understand how these may or may not be “ready for prime time.”


The Potential

Biomarkers have great potential for improving care for psychiatric patients. Three areas in particular can be identified, including enhanced diagnostic accuracy, prognostic information about the natural course of an individual’s illness, and prediction of response to treatment.

As noted above, clinical signs and symptoms are the central basis for establishing psychiatric diagnoses.11 Yet, some symptoms may be present in multiple diagnoses; a reduction in sleep can be a diagnostic element of a depressive episode, a manic episode, or generalized anxiety disorder. Biomarkers have promise for enhancing diagnostic accuracy in this arena. Consider, for example, a patient 20 years of age with a 2-month bout of disabling depression. Is this depression a component of unipolar major depressive disorder (MDD) or does the person really suffer from bipolar disorder but has not yet experienced a floridly manic episode? In an older patient with mild but clear cognitive impairments, are these problems originating from the neurodegenerative changes of Alzheimer’s disease, from ischemic damage in vascular dementia, or from MDD (the “pseudo-dementia” of depression)? In a child, are inattention and disruptive behaviors a part of attention-deficit/hyperactivity disorder, the early onset of bipolar disorder, or simply reflective of coping skills that are overwhelmed by stressful circumstances (eg, parental divorce)? For most patients, clinical information is sufficient to converge on the salient psychiatric diagnosis rapidly, but for some, diagnostic ambiguity may challenge even expert clinicians. The use of biologic markers has potential to assist in this important process, but more work is needed before the field will have useful tools for this application.

Prognostic information is another area where biomarkers could offer valuable insights. In oncology, the elevation of a tumor marker may lead to a workup for a recurrence of disease and initiation of treatment, even before clinical manifestations would have prompted a re-evaluation. In psychiatry, in contrast, an impending full relapse of psychosis in schizophrenia is heralded principally by the return of symptoms. In recurrent depressions, the question can be framed by a patient as “when is a bad day just a ‘bad day,’ and when is it the start of a new episode?” In the care of older adults with depression, some will likely progress from late-life depression to dementia,27 but identification of this subset of patients remains problematic. Lastly, many patients with mood disorders experience recurrent thoughts of death and perceive life as painful and/or meaningless. While this group of patients has an elevated risk for suicidal behaviors, accurately determining which individuals will go on to harm themselves and which will not cannot be forecast reliably on clinical or historical grounds.28 Some preliminary work suggests measures of brain structure and function29 or genotyping30,31 may be developed to refine this process. Rather than believing that research will eventually identify the single, measurable factor that leads to a phenomenon as complex as suicide, it may be more reasonable to anticipate that the greatest utility for this prediction may emerge from a model combining genetic and neurobiologic features with current and past clinical features and familial history, though the relative weightings of these factors remains indeterminate at this time.

Prediction of individual treatment response is viewed by some as a critical area for improvement in psychiatry. While treatments are effective for managing psychiatric illnesses in general, no single treatment works for everyone with a given disorder, and selection of the best treatment for each patient remains a challenge. The general standard of care is to embark upon a course of treatment that is likely to be effective for that disorder, based on evidence from randomized clinical trials and myriad other data (eg, clinical experience, past patient response to treatment); one then monitors for a good outcome and allows for course correction if improvement fails to occur. Both steps fundamentally rely on clinical findings to assess the degree of symptomatic or functional response. Nobel laureate Niels Bohr is often considered to have observed that “prediction is difficult, especially about the future,” and this statement rings true in this aspect of psychiatric care. The failure of depressive symptoms to improve early in treatment is often a harbinger of poor eventual outcome,32 but what is true on a group level does not necessarily provide useful guidance patient by patient, and some patients simply may take longer than others to respond to treatment that will eventually work well for them.33 Measurement-based care,34,35 with its systematic collection of clinical data with rating scales, can improve detection of good or poor response to treatment with greater utility than a clinician’s global impression, but fundamentally these are better observations of what is already occurring, rather than predictions of future outcomes.

Genetic factors have been examined with inconsistent results (eg, as summarized by Rasmussen-Torvik and McAlpine36). In the largest prospective treatment trial dataset examined in MDD, several genes have been linked with response to antidepressants, including serotonin-2A receptor polymorphisms,37 differences in the GRIK4 gene encoding for a glutamate receptor,38 and a chaperone protein that may regulate hypothalamic-pituitary-adrenal axis function (FKBP5 gene).39 While group differences between responders and non-responders can be found, none of these genetic factors have yet shown adequate utility for guiding individual patient treatment decisions. Similarly, the Evaluation of Genomic Applications in Practice and Prevention Working Group was convened by the federal Centers for Disease Control and Prevention to evaluate the evidence for genetic tests and other genomics applications, and their recommendation for depression was that routine genotyping was not yet supported by the evidence.40 In the care of schizophrenia, there is promise that polymorphisms in the genes that relate to drug metabolism may help guide medication dosing,41 but the choice of a specific agent for any given patient cannot yet be guided by biomarkers. In terms of anxiety disorders, it appears that some genes may predispose individuals to develop anxiety disorders under conditions of stress, but predicting individual response to treatment remains elusive.42 Indeed, it may be that consideration of gene-environment interactions becomes essential to take full advantage of genetic information in the care of psychiatric patients.43

Three physiologically based biomarker approaches to predicting outcomes have emerged in recent years in the area of depression with peer-reviewed publication and independent replication of findings, and can serve as useful examples for evaluating a candidate biomarker for clinical use.

The first measure uses changes in resting-state prefrontal brain activity (“quantitative electroencephalography [EEG] cordance”)44 over the course of a test exposure to an antidepressant; that early change is predictive of later treatment outcome with that agent for an individual patient’s care, in studies using either serotonin reuptake inhibitors or dual-reuptake inhibitors. (n=7,45 n=51,46 n=1247).45-49 Cordance is a measure which combines features of absolute and relative EEG power. Because cordance is better correlated with regional cerebral blood flow than other EEG measures,44 findings with this measure can be interpreted within the same conceptual framework as other functional neuroimaging studies. A multi-site replication and extension project (NCT00375843) has recently closed enrollment (200 subjects), and data analysis is now underway. The relationship between early change in cordance and later clinical outcome was independently replicated in an inpatient sample (n=17).50 These findings collectively supported an even larger collaborative, multi-site trial, Biomarkers for Rapid Identification of Treatment Effectiveness in Major Depression (NCT00289523; n=375), using a related EEG measure (the antidepressant treatment response [ATR] index). The ATR can be computed using a simplified electrode array with five electrodes placed over prefrontal and frontal brain regions, instead of approximately 35–40 electrodes placed over all scalp locations for measuring cordance (“full head montage”); thus, this is a technology well suited for use in outpatient physicians’ offices, avoiding the need to send patients to a dedicated EEG facility. After a 1-week test period of escitalopram, subjects were randomized to receive either continued escitalopram treatment, a switch to bupropion, or a combination of the two medications; EEG data were recorded before and after the 1-week test period. In a real-world sample of outpatients with MDD, individuals who received treatment consistent with their biomarker prediction were significantly more likely to experience response and remission than individuals who were randomized to a treatment not predicted to be useful.51-53 Further development and replication projects are underway and must be completed before this paradigm of early physiologic change can be considered for clinical application.

The second approach utilizes an EEG measure which is proposed to reflect central serotonergic activity, the loudness dependent auditory evoked potential (LDAEP),54-56 though some other reports have suggested that the interpretation may be more complex than just central serotonergic activity.57,58 EEG data recorded prior to treatment are interpreted to indicate whether a depressed patient has a low or high level of serotonergic activity, and those with low activity are predicted to have a favorable response to a serotonergic medication (while high activity is linked to better outcomes with a noradrenergic agent). This method has been examined using treatment with serotonergic reuptake inhibitors (n=29,59 n=15,60 n=10061) or a noradrenergic agent (n=14,62 n=2063). The relationship between level of serotonergic activity and predicted treatment response has been observed in all these studies, though data presented in these reports generally does not permit evaluation on an individual case-prediction level. That level of detail in reporting of results would facilitate evaluation of the LDAEP approach for use in guiding clinical decisions. LDAEP values were calculated using dipole source analysis methods and data from full-head EEG electrode arrays.
The third approach links resting-state pretreatment measures of activity in the rostral anterior cingulate cortex (rACC) to outcome with a variety of treatments, including sleep deprivation (n=15,64 n=3665), numerous different medications (n=1866), nortriptyline (n=1867), and paroxetine (n=2768). Across all these studies, higher rACC activity was significantly associated with good treatment response. All utilized positron emission tomography methods to study regional brain metabolism, except one study67 in which an EEG method (low resolution electromagnetic tomography) was used to determine the level of electrical activity at current sources located in the rACC. An inexpensive, non-invasive measure, such as that used by Pizzagalli and colleagues,67 presents an intriguing approach, and independent replication with that methodology would be important for evaluating clinical applicability.


Some Pitfalls

There are numerous pitfalls that prior biomarker work has encountered, and researchers and clinicians should learn from past experiences. Perhaps most worrisome is the problem of premature clinical application, both because of the risk for harm to patients (misdirected in treatment decisions) and for the cynicism about biomarkers in general this engenders; still, the need for useful biomarkers is so great that sometimes enthusiasm and optimism may overtake consideration of results from carefully conducted controlled clinical trials. To paraphrase the film Jerry Maguire, “show me the data!” must be the watchword if clinicians are to make prudent choices for their patients. The usual vetting of new biomedical innovations—procedures, techniques, medications, and devices—requires peer review of findings and independent replication. What applicability is there to a biomarker if it has only been shown to work in a single laboratory and other researchers are unable to validate the results? Furthermore, it must be clearly disclosed what patient group was used to develop the biomarker, as this has great relevance to generalizability. In the universe of all patients with any psychiatric disorder, only a minority will have a syndrome that is refractory to multiple treatments; yet, this is just the sort of patient who may seek out expert care in desperation and consequently be enrolled in a biomarker discovery research program. The generalizability of such a biomarker may be quite limited, and without clear disclosure of these details it is difficult to evaluate the quality of a biomarker.

An additional caveat about biomarkers relates to the heterogeneity within a given clinical diagnosis. With current clinically defined diagnostic categories, there is variety both in the patients who seek care and in the individuals enrolled in research projects. A telling example is shown in Table 1, in which two individuals who both meet the diagnostic criteria for MDD have zero symptoms in common. Thus, development of biomarkers also should disclose the nature of the patient population and consider evaluating whether the accuracy and reliability of the measure are improved or degraded in some sub-populations (eg, psychotic depression, depression in bipolar type I versus bipolar type II patients).



While biomarkers should have a high degree of clinical utility in order to be considered for use, there is also a need for them to be interpretable in the context of the rest of neuroscience. What aspect of a patient’s pathophysiology is being assessed by a test? Is it the form of a reuptake transporter that is associated with greater or lesser efficiency, the level of activity in a particular brain region, or a component of a neuroendocrine feedback loop? Biomarker methods which fail to be comprehensible within or integrated into the extant body of neurobiologic knowledge are unlikely to gain clinical acceptance, even if an empiric trial suggests that they might be useful.

Finally, it is worthwhile to note that statistical significance is not the same thing as clinical significance. Studies may report that a result is significant at the P<.05 level, meaning simply that there is less than one chance in 20 that a finding arose by chance alone. Given a large enough sample, even a clinically-irrelevant difference (eg, a very small improvement on a clinical rating scale) might be reported to occur with an impressive P-value. An important measure for evaluating biomarkers includes the number needed to treat,69 which assesses the number of patients needed to be treated differently (eg, with biomarker guidance, with a new medication) in order to have one additional patient experience the desired, positive outcome. Predictive biomarkers are also often characterized by a series of metrics which can help evaluate the usefulness of a potential biomarker, ie, receiver operating characteristic (ROC) curves and measures such as sensitivity, specificity, and overall predictive accuracy.70-72 Sensitivity is the ratio of “true positive” tests to the number of individuals with the condition. For an outcome predictor, it would be the number of people in a sample who are predicted to respond to a treatment, divided by the total number of people who actually respond. Specificity is the ratio of “true negative” tests to the number of people who do not have a particular condition. In the outcome predictor context, this would be the number of people predicted not to respond divided by the total number of non-responders. Overall predictive accuracy is the proportion of predictions that are correct. ROC curves plot the trade-offs between sensitivity and specificity as different thresholds (cut-points) are used to differentiate between positive and negative tests (eg, between predicting response and non-response to a treatment).


Pragmatic Evaluation of Biomarkers for Psychiatric Management

Given the potential for improving care and the pitfalls that may await possible biomarkers, how then can one judge a biomarker for use in psychiatric management? Table 2 summarizes some key, desirable characteristics of psychiatric biomarkers. Many of them follow directly from the pitfalls detailed above, but the last three on the list merit special mention.

First, the information provided by the biomarker must be timely, clinically useful, and cost effective. A test that is able to predict 8-week treatment response at week 5 is much less timely than a prediction made at week 1. A biomarker that identifies an individual with a treatment-refractory illness (a “biomarker of doom”) is less useful than one which points the way to an alterative treatment strategy. It is unlikely that the field would adopt a biomarker which consumes more resources than it saves, either by direct expenses or by wrongly suggesting an alternative treatment.

Second, the technology needed to assess the biomarker must be available and well tolerated by the target patient population. For example, some neuroimaging methods may be well suited to neuroscience research applications, where a small number of subjects can be observed with great detail, but if the scanning technology costs too much to be deployed widely in the community, the method may not come to be translated into practice. Similarly, a procedure that is perceived as painful (eg, lumbar puncture) or challenging (eg, agitated children remaining conscious yet immobile during a scanning procedure) may have low penetration into the clinical arena for reasons of practicality.

Third, methods that can be seamlessly integrated into existing clinical care practice patterns are more likely to be accepted than those that require major shifts in the delivery of care. For example, sending a patient to a different facility for a biomarker procedure and waiting for test results is less desirable than being able to perform a test in one’s office or ward.



Biomarkers have great potential for improving the care of patients with psychiatric disorders, much as they have in other medical specialties. Adoption of biomarkers into clinical care, however, requires careful and thorough evaluation, and there is risk to patients if measures are embraced prematurely. A set of proposed criteria can be used in the pragmatic evaluation of candidate biomarkers. PP



1.    Bast RC Jr, Lilja H, Urban N, et al. Translational crossroads for biomarkers. Clin Cancer Res. 2005;11(17):6103-6108.
2.    Cho WC. Contribution of oncoproteomics to cancer biomarker discovery. Mol Cancer. 2007;6:25.
3.    Rhodes DR, Chinnaiyan AM. Bioinformatics strategies for translating genome-wide expression analyses into clinically useful cancer markers. Ann N Y Acad Sci. 2004;1020:32-40.
4.    Goonewardene TI, Hall MR, Rustin GJ. Management of asymptomatic patients on follow-up for ovarian cancer with rising CA-125 concentrations. Lancet Oncol. 2007;8(9):813-821.
5.    Manenti ER, Bodanese LC, Camey SA, Polanczyk CA. Prognostic value of serum biomarkers in association with TIMI risk score for acute coronary syndromes. Clin Cardiol. 2006;29(9):405-410.
6.    Wu AH, Jaffe AS, Apple FS, et al. National Academy of Clinical Biochemistry Laboratory Medicine Practice Guidelines: use of cardiac troponin and B-type natriuretic peptide or N-terminal proB-type natriuretic peptide for etiologies other than acute coronary syndromes and heart failure. Clin Chem. Oct 22, 2007 [Epub ahead of print].
7.    de Ferranti SD, Rifai N. C-reactive protein: a nontraditional serum marker of cardiovascular risk. Cardiovasc Pathol. 2007;16(1):14-21.
8.    Reddy UM. Prediction and prevention of recurrent stillbirth. Obstet Gynecol. 2007;110(5):1151-1164.
9.    Landewé R. Predictive markers in rapidly progressing rheumatoid arthritis. J Rheumatol Suppl. 2007;80:8-15.
10.    Ahmed S, Mozley PD, Potter WZ. Biomarkers in psychotropic drug development. Am J Geriatr Psychiatry. 2002;10(6):678-686.
11.    Vergare MJ, Binder RL, Cook IA, et al. Psychiatric Evaluation of Adults. 2nd ed. Arlington, VA: American Psychiatric Association; 2006.
12.    Berger PA, Faull KF, Kilkowski J, et al. CSF monoamine metabolites in depression and schizophrenia. Am J Psychiatry. 1980;137(2):174-180.
13.    Garvey M, Hollon SD, DeRubeis RJ, Evans MD, Tuason VB. Does 24-h urinary MHPG predict treatment response to antidepressants? I. A review. J Affect Disord. 1990;20(3):173-179.
14.    Carroll BJ, Cassidy F, Naftolowitz D, et al. Pathophysiology of hypercortisolism in depression. Acta Psychiatr Scand Suppl. 2007;(433):90-103.
15.    Carroll BJ. Dexamethasone suppression test: a review of contemporary confusion. J Clin Psychiatry. 1985;46(2 Pt 2):13-24.
16.    Rush AJ, Weissenburger JE. Melancholic symptom features and DSM-IV. Am J Psychiatry. 1994;151(4):489-498.
17.    Howland RH, Thase ME. Biological studies of dysthymia. Biol Psychiatry. 1991;30(3):283-304.
18.    Lee KH, Williams LM. Eye movement dysfunction as a biological marker of risk for schizophrenia. Aust N Z J Psychiatry. 2000;34(suppl):S91-S100.
19.    Copolov D, Crook J. Biological markers and schizophrenia. Aust N Z J Psychiatry. 2000;34(suppl):S108-S112.
20.    Crowell SE, Beauchaine TP, Gatzke-Kopp L, et al. J. Autonomic correlates of attention-deficit/hyperactivity disorder and oppositional defiant disorder in preschool children. J Abnorm Psychol. 2006;115(1):174-178.
21.    Nichols L, Pike VW, Cai L, Innis RB. Imaging and in vivo quantitation of beta-amyloid: an exemplary biomarker for Alzheimer’s disease? Biol Psychiatry. 2006;59(10):940-947.
22.    Small GW, Bookheimer SY, Thompson PM, et al.  Current and future uses of neuroimaging for cognitively impaired patients. Lancet Neurol. 2008;7(2):161-172.
23.    Kumar A, Ajilore O. Magnetic resonance imaging and late-life depression: potential biomarkers in the  era of personalized medicine. Am J Psychiatry. 2008;165(2):166-168.
24.    Olvera RL, Caetano SC, Fonseca M, et al.  Low levels of N-acetyl aspartate in the left dorsolateral prefrontal cortex of pediatric bipolar patients. J Child Adolesc Psychopharmacol. 2007;17(4):461-473.
25.    Bookheimer SY, Strojwas MH, Cohen MS, et al.  Patterns of brain activation in people at risk for Alzheimer’s disease. N Engl J Med. 2000;343(7):450-456.
26.    Kraemer HC, Schultz SK, Arndt S. Biomarkers in psychiatry: methodological issues. Am J Geriatr Psychiatry. 2002;10(6):653-659.
27.    Smith GS, Gunning-Dixon FM, Lotrich FE, Taylor WD, Evans JD. Translational research in late-life mood disorders: implications for future intervention and prevention research. Neuropsychopharmacology. 2007;32(9):1857-1875.
28.    Baldessarini RJ, Conwell Y, Fawcett JA, et al. Practice Guideline for the Assessment and Treatment of Patients with Suicidal Behaviors. Arlington, VA: American Psychiatric Association; 2003.
29.    Pompili M, Ehrlich S, De Pisa E, et al. White matter hyperintensities and their associations with suicidality in patients with major affective disorders. Eur Arch Psychiatry Clin Neurosci. 2007;257(8):494-499.
30.    Laje G, Paddock S, Manji H, et al. Genetic markers of suicidal ideation emerging during citalopram treatment of major depression. Am J Psychiatry. 2007;164(10):1530-1538.
31.    Perlis RH, Purcell S, Fava M, et al. Association between treatment-emergent suicidal ideation with citalopram and polymorphisms near cyclic adenosine monophosphate response element binding protein in the STAR*D study. Arch Gen Psychiatry. 2007;64(6):689-697.
32.    Nierenberg AA, McLean NE, Alpert JE, Worthington JJ, Rosenbaum JF, Fava M. Early nonresponse to fluoxetine as a predictor of poor 8-week outcome. Am J Psychiatry. 1995;152(10):1500-1503.
33.    Trivedi MH, Rush AJ, Wisniewski SR, et al. Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: implications for clinical practice. Am J Psychiatry. 2006;163(1):28-40.
34.    Trivedi MH, Rush AJ, Gaynes BN, et al. Maximizing the adequacy of medication treatment in controlled trials and clinical practice: STAR(*)D measurement-based care. Neuropsychopharmacology. 2007;32(12):2479-2489.
35.    Sussman N. Translating science into service: lessons learned from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study. Prim Care Companion J Clin Psychiatry. 2007;9(5):331-337.
36.    Rasmussen-Torvik LJ, McAlpine DD. Genetic screening for SSRI drug response among those with major depression: great promise and unseen perils. Depress Anxiety. 2007;24(5):350-357.
37.    McMahon FJ, Buervenich S, Charney D, et al. Variation in the gene encoding the serotonin 2A receptor is associated with outcome of antidepressant treatment. Am J Hum Genet. 2006;78(5):804-814.
38.    Paddock S, Laje G, Charney D, et al. Association of GRIK4 with outcome of antidepressant treatment in the STAR*D cohort. Am J Psychiatry. 2007;164(8):1181-1188.
39.    Lekman M, Laje G, Charney D, et al. The FKBP5-gene in depression and treatment response-an Association Study in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) cohort. Biol Psychiatry. Jan 10, 2008 [Epub ahead of print].
40.    Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group. Recommendations from the EGAPP Working Group: testing for cytochrome P450 polymorphisms in adults with nonpsychotic depression treated with selective serotonin reuptake inhibitors. Genet Med. 2007;9(12):819-825.
41.    Arranz MJ, de Leon J. Pharmacogenetics and pharmacogenomics of schizophrenia: a review of last decade of research. Mol Psychiatry. 2007;12(8):707-747.
42.    Xu K, Ernst M, Goldman D. Imaging genomics applied to anxiety, stress response, and resiliency. Neuroinformatics. 2006;4(1):51-64.
43.    Caspi A, Moffitt TE. Gene-environment interactions in psychiatry: joining forces with neuroscience. Nat Rev Neurosci. 2006;7(7):583-590.
44.    Leuchter AF, Uijtdehaage SH, Cook IA, O’Hara R, Mandelkern M. Relationship between brain electrical activity and cortical perfusion in normal subjects. Psychiatry Res. 1999;90(2):125-140 
45.    Cook IA, Leuchter AF. Prefrontal changes and treatment response prediction in depression. Semin Clin Neuropsychiatry. 2001;6(2):113-120
46.    Cook IA, Leuchter AF, Morgan M, et al. Early changes in prefrontal activity characterize clinical responders to antidepressants. Neuropsychopharmacology. 2002;27(1):120-131.
47.    Cook IA, Leuchter AF, Morgan ML, Stubbeman W, Siegman B, Abrams M. Changes in prefrontal activity characterize clinical response in SSRI nonresponders: a pilot study. J Psychiatr Res. 2005;39(5):461-466.
48.    Leuchter AF, Cook IA, Uijtdehaage SH, et al. Brain structure and function and the outcomes of treatment for depression. J Clin Psychiatry. 1997;58(suppl 16):22-31.
49.    Hunter AM, Cook IA, Leuchter AF. The promise of the quantitative electroencephalogram as a predictor of antidepressant treatment outcomes in major depressive disorder. Psychiatr Clin North Am. 2007;30(1):105-124.
50.    Bareš M, Brunovsky M, Kopecek M, et al. Changes in QEEG prefrontal cordance as a predictor of response to antidepressants in patients with treatment resistant depressive disorder: a pilot study. J Psychiatr Res. 2007;41(3-4):319-325.
51.    Leuchter AF, Cook IA, Marangell LB, et al. Biomarkers for Rapid Identification of Treatment Effectiveness in Major Depression (BRITE-MD): Predictors of Clinical Treatment Response. Poster presented at: the Annual Meeting of the Society of Biological Psychiatry; San Diego, CA; May 17, 2007.
52.    Leuchter AF, Cook IA, Gilmer W, et al. EEG-guided Antidepressant Selection May Improve Response Rates: Insights from the BRITE-MD Trial. Poster presented: the 47th Annual Meeting of the New Clinical Drug Evaluation Unit; Boca Raton, FL; June 11-14, 2007.
53.    Leuchter AF, Cook IA, Marangell LB, et al. Biomarkers for Rapid Identification of Treatment Effectiveness in Major Depression (BRITE-MD): Predictors of clinical response and remission to escitalopram. Poster presented at: the Annual Meeting of the American College of Neuropsychopharmacology; Boca Raton, FL; December 8-12, 2007.
54.    Hegerl U, Juckel G. Identifying psychiatric patients with serotonergic dysfunctions by event-related potentials. World J Biol Psychiatry. 2000;1(2):112-118.
55.    Nathan PJ, Segrave R, Phan KL, O’Neill B, Croft RJ. Direct evidence that acutely enhancing serotonin with the selective serotonin reuptake inhibitor citalopram modulates the loudness dependence of the auditory evoked potential (LDAEP) marker of central serotonin function. Hum Psychopharmacol. 2006;21(1):47-52.
56.    Pogarell O, Juckel G, Norra C, et al. Prediction of clinical response to antidepressants in patients with depression: neurophysiology in clinical practice. Clin EEG Neurosci. 2007;38(2):74-77.
57.    Norra C, Becker S, Bröcheler A, Kawohl W, Kunert HJ, Buchner H. Loudness dependence of evoked dipole source activity during acute serotonin challenge in females. Hum Psychopharmacol. 2008;23(1):31-42.
58.    Guille V, Croft RJ, O’Neill BV, Illic S, Phan KL, Nathan PJ. An examination of acute changes in serotonergic neurotransmission using the loudness dependence measure of auditory cortex evoked activity: effects of citalopram, escitalopram and sertraline. Hum Psychopharmacol. Jan 15, 2008; [Epub ahead of print].
59.    Gallinat J, Bottlender R, Juckel G, et al. The loudness dependency of the auditory evoked N1/P2-component as a predictor of the acute SSRI response in depression. Psychopharmacology (Berl). 2000;148(4):404-411.
60.    Mulert C, Juckel G, Augustin H, Hegerl U. Comparison between the analysis of the loudness dependency of the auditory N1/P2 component with LORETA and dipole source analysis in the prediction of treatment response to the selective serotonin reuptake inhibitor citalopram in major depression. Clin Neurophysiol. 2002;113(10):1566-1572.
61.    Lee TW, Yu YW, Chen TJ, et al. Loudness dependence of the auditory evoked potential and response to antidepressants in Chinese patients with major depression. J Psychiatry Neurosci. 2005;30(3):202-205.
62.    Linka T, Müller BW, Bender S, Sartory G, Gastpar M. The intensity dependence of auditory evoked ERP components predicts responsiveness to reboxetine treatment in major depression. Pharmacopsychiatry. 2005;38(3):139-143.
63.    Mulert C, Juckel G, Brunnmeier M, et al. Prediction of treatment response in major depression: integration of concepts. J Affect Disord. 2007;98(3):215-225.
64.    Wu JC, Gillin JC, Buchsbaum MS, Hershey T, Johnson JC, Bunney WE Jr. Effect of sleep deprivation on brain metabolism of depressed patients. Am J Psychiatry. 1992;149(4):538-543.
65.    Wu J, Buchsbaum MS, Gillin JC, et al. Prediction of antidepressant effects of sleep deprivation by metabolic rates in the ventral anterior cingulate and medial prefrontal cortex. Am J Psychiatry. 1999;156(8):1149-1158. Erratum in: Am J Psychiatry. 1999;156(10):1666.
66.    Mayberg HS, Brannan SK, Mahurin RK, et al. Cingulate function in depression: a potential predictor of treatment response. Neuroreport. 1997;8(4):1057-1061.
67.    Pizzagalli D, Pascual-Marqui RD, Nitschke JB, et al. Anterior cingulate activity as a predictor of degree of treatment response in major depression: evidence from brain electrical tomography analysis. Am J Psychiatry. 2001;158(3):405-415.
68.    Saxena S, Brody AL, Ho ML, et al. Differential brain metabolic predictors of response to paroxetine in obsessive-compulsive disorder versus major depression. Am J Psychiatry. 2003;160(3):522-532.
69.    Laupacis A, Sackett DL, Roberts RS. An assessment of clinically useful measures of the consequences of treatment. N Engl J Med. 1988;318(26):1728-1733.
70.    Zweig MH, Campbell G. Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clin Chemistry. 1993;39(8):561-577.
71.    Altman DG, Bland JM. Diagnostic tests 1: sensitivity and specificity. BMJ. 1994;308(6943):1552.
72.    Altman DG, Bland JM. Diagnostic tests 2: predictive values. BMJ. 1994;309(6947):102.


Dr. Erman is clinical professor in the Department of Psychiatry at the University of California, San Diego School of Medicine, a staff scientist for the Scripps Research Institute Department of Neuropharmacology, and chief medical officer of Avastra USA.

Disclosures: Dr. Erman is a consultant to Cephalon, Mallinckrodt, Neurocrine, sanofi-aventis, and Takeda; is on the speaker’s bureaus of Forest, sanofi-aventis, and Takeda; is on the advisory boards of Cephalon, Neurocrine, sanofi-aventis, and Takeda; has received grant/research support from Arena, Cephalon, Eli Lilly, GlaxoSmithKline, Mallinckrodt, Merck, Organon, Pfizer, Pharmacia, ResMed, sanofi-aventis, Schwarz Pharma, and Takeda; and owns stock in Cephalon, Forest, Merck, Neurocrine, Pfizer, sanofi-aventis, and Sepracor.



“Sleeplessness is a desert without vegetation or inhabitants.” —Jessamyn West  (American Author, 1902-1984)


Cognitive behavioral therapy for insomnia (CBTI) is well documented as an effective non-pharmacologic therapy for insomnia, but it is not widely understood or utilized in clinical practice. Greater understanding of the uses and limitations of this therapy may help it to be implemented more frequently and appropriately in clinical practice.

CBTI is a variant of cognitive behavioral therapy (CBT), developed as a treatment for depression. Although numerous therapists contributed to the development of cognitive therapy, major contributions were made by Beck1 and associates from the 1960s onward. Beck focused on cognition; the incorporation of behavioral treatment components as part of the therapeutic regimen for the treatment of depression has increased the effectiveness of this technique.

Beck’s approach reflected an important divergence from classic psychotherapeutic techniques for the treatment of depression. Rather than making an effort to understand the origins of depression in the context of early childhood or family conflicts, CBT assumes that patients with depression have developed negative thoughts and beliefs about their life situation, described as cognitive distortions. These distortions are perceived by these patients as being true, and as accurately reflecting the limitations and frustrations that afflict their everyday life.

How is the “work” of CBT accomplished? First, patients must accept the theoretical framework within which CBT operates, largely in the “here and now,” and be willing to examine and try to change the cognitive misperceptions that have lead to pathologic emotional states. CBT typically tries to identify irrational or maladaptive thoughts, assumptions, and beliefs that are related to pathologic negative emotions; it also works to identify how these beliefs are dysfunctional, inaccurate, or simply not helpful. The goal is to try to reject distorted cognitions and to replace them with more realistic and appropriate alternatives. Techniques utilized for CBT of depression may include keeping a diary of significant events, emotions, thoughts, and behaviors; exploring and testing assumptions and beliefs that might be distorted or unrealistic; increasing levels of comfort for various activities and interactions which have been avoided; and trying out new ways of behaving and reacting.

For example, the patient’s statement that “no one loves me or ever could care for me” is corrected by the therapist with evidence of past and current relationships that demonstrate care and affection; the patient’s assertion that they are “a failure in everything they do” is countered with evidence of past successes and recent failures caused by their belief in the inevitability of their failure, ensuring that they will not succeed. Patients being treated with CBT may also be trained in the use of relaxation and distraction techniques.

Patients with insomnia often are enmeshed in the same type of cognitive distortions, making CBTI an extremely powerful technique for the treatment of insomnia. For example, it has been well established that insomnia patients report a sleep latency (the period of time from lights out until entry into consolidated sleep) that is substantially longer than the “objective” sleep latency defined by polysomnography (PSG), and underestimate the number of minutes that they have slept. In 1976, Carskadon and colleagues2 studied the sleep of 122 drug-free subjects who complained of chronic insomnia. They compared the PSG recordings of these subjects with estimates of their usual sleep patterns and their estimated sleep time on the morning after sleeping in the laboratory. In comparison with PSG data, most subjects consistently underestimated the amount of time they slept and overestimated the amount of time it took them to get to sleep. All subjects consistently underestimated the number of arousals they experienced.

Similar findings are observed in essentially every study examining the sleep of insomnia subjects. Although individuals without insomnia demonstrate a mild version of this cognitive distortion, it has been demonstrated that insomniacs are much more likely to have such distorted perceptions. Perhaps as importantly, they perceive the amount of sleep they are able to obtain as a problem rather than a fact. For example, in reviewing a sleep questionnaire with a patient being seen in evaluation, this author noted that the patient reported that it regularly took 45 minutes to fall asleep. When asked how long he had this problem, his response was that it is not a problem; it just takes 45 minutes to fall asleep. The patient said he gets in bed, reads, and when he feels sleepy turns off the light and goes to sleep.

Means and colleagues3 examined sleep time perceptions in patients with primary insomnia sufferers and normal sleepers in the sleep laboratory and at home. Fifty-two insomniacs, middle-aged or older, and 49 matched normal sleepers were studied over multiple nights using laboratory and home polysomnography, and provided estimates of their sleep. As had been previously reported, the insomniacs, as a group, showed a greater tendency to underestimate sleep time than did the normal sleepers. However, wide variability in the accuracy of sleep time perceptions was seen within both groups.

These distorted perceptions of sleep latency and sleep duration are good candidates for “correction” using cognitive and behavioral techniques. It has thus been suggested that CBTI, which contains both cognitive and behavioral components, should be the first-line treatment for insomnia, with greatest probability of effective treatment.4 CBT challenges “black and white” thinking, including use of words such as “always” (sleep poorly) or “never” (perform well).5 The cognitive component reduces autonomic and cognitive arousal, targets maladaptive coping, challenges dysfunctional beliefs about sleep (eg, I must sleep 8 hours), corrects unrealistic expectations (eg, I should never wake up at night), reappraises perceptions of the insomnia consequences (eg, I cannot work without 8 hours of sleep), and recognizes maladaptive thoughts and associated catastrophic ideas that foster insomnia.

How is this accomplished? Patients complete sleep diaries listing their perceptions of their sleep latencies, sleep quality, and sleep duration. For example, Mr. Jones expresses his concerns that, following a poor night of sleep, he will be unable to function at work and will be in danger of losing his job. His sleep diary notes that on Monday night he slept particularly poorly. He is asked, “How was your day at work Tuesday? Were you fired? Did customers complain? Did your boss or co-workers observe that you were not doing your job or were not your usual self?” The typical (and expected) negative answer, “No, no one made any mention that I was not doing well…” allows the therapist to point out that the patient’s distorted perception is the concern, not the sleep loss itself.

CBTI also helps patients to recognize that their concerns about the consequence of poor sleep lead to increases in anxiety, further increasing their physiologic arousal and interfering with the capacity to relax and fall off to sleep. Changing their concerns and beliefs about poor sleep helps them to prevent this state of pathological arousal from developing; behavioral techniques reduce arousal, promoting better sleep.

The behavioral component of CBT identifies patient-specific perpetuating factors of insomnia and encourages their elimination (eg, use of alcohol to fall asleep, watching scary movies before going to bed). The patient is encouraged to create a relaxing routine to engage in before bedtime (eg, diary writing, hot bath, meditation) and not to try to compensate for a poor night’s sleep by spending more time in bed in the morning or napping.5 The behavioral components target maladaptive coping (eg, staying in bed for 12 hours), eliminates sleep incompatible behaviors (eg, poor sleep hygiene), regularizes the sleep schedule, and educates patients about healthier sleep practices.

The two behavioral treatments most commonly applied to accomplish these goals are stimulus-control therapy and sleep restriction therapy.6-8 The aim of stimulus-control therapy is to break the negative associations of being in bed unable to sleep. It is especially helpful for patients with sleep-onset insomnia and prolonged awakenings. Sleep restriction therapy is based on the observation that more time spent in bed leads to more fragmented sleep. Both therapies may take 3–4 weeks or longer to be effective.

Patients may also be taught other techniques to help them reduce levels of arousal at the start of the night and to help them return to sleep if they awaken during the night. These may include progressive muscular relaxation, focused imagery, relaxation audiotapes, self hypnosis, meditation, or techniques derived from yoga such as a focus on abdominal breathing. The use of any of these techniques must be accepted by patients as being reasonable and practical for them, and must be practiced and utilized on a regular basis if they are expected to be of benefit to the patient.

CBT is effective for 70% to 80% of insomnia patients. It significantly reduces several measures of insomnia, including sleep-onset latency and wake-after-sleep onset. Aside from the clinically measurable changes, CBT enables many patients to regain a feeling of control over their sleep, thereby reducing the emotional distress that sleep disturbances cause.6

Does CBTI work for all patients with insomnia? Is it appropriate to suggest, as proponents may argue, that it should be the first treatment offered to insomnia patients on the basis of its proven efficacy and absent risk profile? These are difficult questions to answer. In general, CBTI has been shown to be as effective, and in some studies and for some time periods more effective, than pharmacologic treatment. However, it is important to understand how patients are selected for these studies in order to appreciate for whom CBTI may be appropriate and for whom it may not. First, patients considering participation in such studies must not be using sleep, anti-anxiety or antidepressant medications. If they are using sleep medications they must be willing to discontinue these medications, typically for a period of 2 weeks, prior to evaluation for entry into CBTI research protocols. Such exclusionary criteria remove from research protocols many patients who might be seen in clinical practice, and who might be considered as candidates for CBTI.

Some patients using sleep medications may express a desire to participate in CBTI research, and agree to discontinue their use of these medications. If they are unable to be compliant—if they find during the 2-week period free of medications that their insomnia is so severe that they need to resume use of medications—they are also excluded from the subjects who are considered evaluable in CBTI protocols. One criticism of CBTI research may thus be that the patients who are accepted for treatment and who complete research protocols may not be fully representative of the general insomnia population.

The obvious question must be asked. If CBTI is so good, why is it not more readily available? Several barriers to access occur. As with any structured psychotherapy, practitioners need training in the techniques of CBTI in order to be capable of treating patients. Relatively few training programs in psychiatry and psychology have incorporated CBTI in their training programs, although several texts5,9 have been published which can help therapists understand the basic components of this treatment modality. Training programs are also provided at courses on insomnia sponsored by the American Academy of Sleep Medicine, and at the annual meetings of the American Psychiatric Association and the Associated Professional Sleep Societies.

Another barrier to access for patients is insurance coverage. Insurance policies often contain limited visits for psychotherapy and may exclude treatment for insomnia. Although CBTI has been demonstrated to be an effective therapy, patients may be reluctant to initiate a course of treatment if they are uncertain whether their insurance will pay for their sessions.

How can access to CBTI be improved? One way would be to make it available to patients in primary care practice settings. A recent study10 addressed the question of whether a treatment validated in academic research centers such as CBTI can be used effectively in clinical practice settings. In this study, nurse practitioners were trained to provide group CBT to patients with insomnia seen in primary care practices. The results showed an average reduction of sleep onset latency from 61 minutes to 28 minutes after treatment, with similar improvements on time awake after sleep onset. In addition, 84% of patients initially using hypnotics remained drug free at a 1-year follow-up.11 The benefits of brief consultation models involving one or two consultations have been documented in both primary care12 and specialty sleep clinics.13

In summary, CBTI is a therapeutic technique whose efficacy in the treatment of insomnia is well-established. Although some practical barriers exist which may interfere with its availability to patients in all areas of the United States, innovative approaches, such as Internet and telephonically-supported CBT, are likely to improve patient access to this treatment modality and increase the impact it has on the treatment of insomnia. Although not all patients will be willing or able to comply with the demands of this therapy, it clearly provides a rational, scientifically-based and effective non-pharmacologic treatment approach that can be of long-term benefit for many patients with insomnia. PP



1.    Beck AT. Cognitive Therapy and the Emotional Disorders. Madison, CT: International Universities Press, Inc.; 1975.
2.    Carskadon MA, Dement WC, Mitler MM, Guilleminault C, Zarcone VP, Spiegel R. Self-reports versus sleep laboratory findings in 122 drug-free subjects with complaints of chronic insomnia. Am J Psychiatry. 1976;133(12):1382-1388.
3.    Means MK, Edinger JD, Glenn DM, Fins AI. Accuracy of sleep perceptions among insomnia sufferers and normal sleepers. Sleep Med. 2003;4(4):285-296.
4.    Smith MT, Perlis ML. Who is a candidate for cognitive-behavioral therapy for insomnia? Health Psychol. 2006;25(1):15-19.
5.    Perlis ML, Jungquist C, Smith MT, Posner D. Cognitive Behavioral Treatment of Insomnia: A Session-by-Session Guide. New York, NY: Springer; 2005.
6.    Morin CM, Culbert JP, Schwartz SM. Nonpharmacological interventions for insomnia: a meta-analysis of treatment efficacy. Am J Psychiatry. 1994;151(8):1172-1180.
7.    Spielman AJ, Saskin P, Thorpy MJ. Treatment of chronic insomnia by restriction of time in bed. Sleep. 1987;10(1):45-56.
8.    Bootzin RR, Nicassio PM. Behavioral treatments for insomnia. In: Hersen M, Eisler RM, Miller PM, eds. Progress in Behavior Modification. Vol. 6. New York, NY: Academic Press, Inc; 1978:1-45.
9.    Morin CM, Espie CA. Insomnia: A Clinical Guide to Assessment and Treatment. New York, NY: Kluwer Academic/Plenum; 2003.
10.    Espie CA, Inglis SJ, Tessier S, Harvey L. The clinical effectiveness of cognitive behaviour therapy for chronic insomnia: Implementation and evaluation of a sleep clinic in general medical practice. Behav Res Ther. 2001;39(1):45-60.
11.    Espie CA, Inglis SJ, Harvey L. Predicting clinically significant response to cognitive behavior therapy for chronic insomnia in general medical practice: analyses of outcome data at 12 months posttreatment. J Consult Clin Psychol. 2001;69(1):58-66.
12.    Edinger JD, Sampson WS. A primary care “friendly” cognitive behavioral insomnia therapy. Sleep. 2003;26(2):177-182.
13.    Hauri PJ. Consulting about insomnia: a method and some preliminary data. Sleep. 1993;16(4):344-350.


This interview took place on September 7, 2007, and was conducted by Norman Sussman, MD.


This interview is also available as an audio PsychCastTM at

Disclosure: Dr. Janicak is consultant to and/or on the advisory boards of AstraZeneca, Bristol-Myers Squibb, Janssen, Neoronetics, and Solvay; is on the speaker’s bureaus of Abbott, AstraZeneca, Bristol-Myers Squibb, Janssen, and Pfizer; and receives grant support from AstraZeneca, Bristol-Myers Squibb, Janssen, Neuronetics, sanofi-aventis, and Solvay.



Dr. Janicak is professor of Psychiatry at Rush University in Chicago, Illinois, medical director of the Rush Psychiatric Clinical Research Center, and distinguished fellow at the American Psychiatric Association. He has been listed in Best Doctors of America since 1996 and Who’s Who in America since 2002. In 2003, the Illinois chapter of the National Alliance for the Mentally Ill named Dr. Janicak “Psychiatrist of the Year.” With a strong interest in the assessment and treatment of mood and psychotic disorders, he has been a National Institute of Mental Health grant awardee as both principal and co-investigator. Dr. Janicak is editor of the Psychopharm Review and has authored >250 publications in psychiatric literature, including Principles and Practice of Psychopharmacotherapy.


What types of neuromodulation are available for clinical use?

Using electrical or magnetic stimulation to alter neurocircuits in the brain is the core concept associated with neuromodulation. This is possible through a variety of device-based therapies, including electroconvulsive therapy (ECT), vagus nerve stimulation (VNS), deep brain stimulation (DBS), and repetitive transcranial magnetic stimulation (TMS). ECT has been available for >60 years and remains the standard for therapeutic neuromodulation. In 1997, the Food and Drug Administration approved DBS for patients with neurologic disorders such as Parkinson’s disease and dystonic reactions. VNS is another way to alter activity in the central nervous system for treatment-resistant depression (TRD) and epilepsy. TMS has been used for moderately severe TRD. Only ECT and VNS have FDA-approved indications for specific types of depression. The FDA is presently considering the approval of a TMS device.


What are the approved indications for VNS?

VNS was approved as an adjunctive treatment for depression since studies were done in combination with other pharmacologic agents. In addition, those studies involved a more resistant group of patients who, according to the FDA-approved indication, should have failed ≥4 adequate antidepressant trials during the index episode. This could include medication, cognitive behavioral therapy, or ECT.


What is the time course of improvement?

The pivotal trial1,2 was a sham control versus active design, in which VNS served as an adjunctive treatment to stable ongoing medication regimens over a 3-month period. The trial demonstrated a statistically significant difference between the active and sham procedure only on the secondary outcome measure, the Inventory of Depressive Symptomatology. Based on these results, the safety/tolerability profile, and patients who did not benefit from previous treatments improving, the advisory panel advised the FDA to approve VNS. However, the division within the FDA that makes the final decision initially chose to not take the panel’s advice. The FDA and Cyberonics (the company that makes the device) continued to discuss the potential advantages of VNS. In the meantime, the company continued to collect data after the 3-month sham-controlled trial. Response and remission rates continued to increase over extended periods of time (eg, 6 months, 1 year, 2 years) with more prolonged exposure to VNS. This improvement occurred in patients who generally did not experience lasting benefit from previous treatment strategies. The FDA decided that it would be better to provide VNS for these patients, and it became clinically available in July 2005.


Have parallel-like functional brain imaging studies been conducted to see whether or not clinical improvement correlates with changes in brain chemistry patterns?

Most of the imaging data are from animal studies. When ECT, VNS to the left vagus nerve, and TMS were used, all seemed to alter activity in structures of the mesolimbic system implicated in symptoms associated with depression. These observations are also supported by human imaging data. This evidence argues that neuromodulation, regardless of the approach (eg, electrical stimulation or magnetic pulses to the brain), affects areas known to modulate the symptoms of depression.


What factors contribute to the controversy over VNS?

Concern has focused on the efficacy of VNS. Numerous factors contribute to this. First, pharmacologic agents must meet certain FDA requirements to be approved. This usually requires two large, placebo-controlled, positive trials demonstrating that a drug is useful and safe for the treatment of depression. Second, there is a lack of experience with devices for the treatment of depression. Prior to VNS, ECT was the last form of neuromodulation to be approved. This means the division within the FDA that assesses devices is more accustomed to looking at a variety of devices for medical conditions. Third, discussions between Cyberonics representatives and the FDA did not go smoothly. Ultimately, the division that rejected the advisory panel’s suggestion to approve VNS had this decision overridden. Fourth, third-party payers such as Medicare and Medicaid have decided not to reimburse the cost of VNS implantation, still considering it an investigational device. The average cost is $25,000 for the implantation plus additional costs for follow-up visits and adjustments. As a result, the device may not have adequate use in a sufficient sample of patients over an extended period of time to assess its true benefit.


Has anyone reported getting manic on VNS?

Yes. The studies included both unipolar and bipolar patients, and a few patients became manic. However, it is hard to know if they spontaneously moved into a manic episode or if VNS induced it. One positive perspective is that most known effective antidepressant therapies have a propensity to increase the switch rate from depression to mania. Thus, if VNS were an effective antidepressant treatment for bipolar depression, one might expect some of these switches to occur. However, I think the bipolar group was too small to make any meaningful conclusions.


If a patient shows signs of TRD, when should the clinician recommend VNS?

The clinician should follow the FDA-approved indications for TRD. The patient should have a history of chronic, recurrent depression and failed ≥4 adequate antidepressant therapies during the index episode. In addition, based on the clinical trials, clinicians may expect response and remission rates after 2 years in the 15% to 25% range in a patient group that did not benefit from multiple prior treatments. In the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study, chances of achieving remission dramatically dropped after two failed adequate antidepressant trials.3,4 This demonstrates that this level of treatment-resistant patient has limited options. Since the data is not encouraging, the STAR*D results make VNS an appealing intervention for this population. If VNS works, it may be most effective with longer exposure.


What makes VNS a more desirable treatment than periodic ECT?

VNS is primarily a maintenance treatment strategy. It appears that the longer a patient is exposed the greater the benefit. ECT is usually an acute treatment. Treatment-resistant patients could possibly use both approaches, treating the acute episode with a course of ECT and then using VNS as a maintenance strategy.


What risks are associated with VNS?

The risks associated with VNS involve the electrical stimulation of the left vagus nerve. The most common complications include voice alteration such as hoarseness and other related symptoms which occurred in approximately 50% of patients. These symptoms, however, were not serious enough to require large numbers of patients to withdraw from the studies. In the sham controlled trial, shortness of breath, neck pain, dysphasia, and parethesias occurred in >10% of patients, and 25% to 35% experienced a cough. Most of those symptoms gradually subsided, and the percentage of patients who experienced cough dropped to <10% at 2 years. Of note, in the acute pivotal trial, both sham control and active VNS patients reported similar rates of mild, moderate, or severe adverse effects. Overall, VNS appears to be a safe treatment.

Stimulation to the nerve occurs in an on- and off-duty cycle. Thus, stimulation is on for a period of time then off for several minutes. The patient can also stop the device by placing a magnet over the chest area where it was implanted. Generally, patients do not go through that process unless a side effect is troublesome.

VNS does not result in any systemic effects (eg, weight gain, sexual dysfunction, sedation, and other common issues associated with pharmacologic treatments). When the device is implanted and the stimulus electrodes first attached to the left vagus nerve, rarely the device can cause a cardiac rhythm disturbances when initially turned on. If this happens, the surgeon can readjust the electrodes to prevent this.


Why is the approval for TMS taking a long time?

In January 2007, an FDA advisory panel discussed concerns about the a priori primary outcome measure (ie, Montgomery-Asberg Depression Rating Scale change score) comparing active TMS to a sham control in the Neuronetics-sponsored 6-week trial. At the 4-week juncture, the difference between active TMS and sham control achieved a P-value of .057, just missing the conventional level of statistical significance. However, several secondary measures demonstrated that active TMS achieved statistical separation from the sham procedure at the 4-week period, including the 24-item and 17-item Hamilton Rating Scale for Depression and the Inventory of the Depressive Symptomatology. At the 6-week juncture, both change scores and categorical response rates demonstrated statistical separation for the active versus sham procedure.

The panel also considered the absolute difference between the active TMS and sham control scores (ie, 3–5 points). Because of the modest differences, the clinical relevance was discussed. It is important to note that the patients in the TMS trial were a moderately treatment-resistant group who had failed one to four antidepressant trials during the index or a previous episode. In drug trials, pharmaceutical companies usually do not include patients with this level of TRD because it could skew the outcome against the investigational agent. In this study, even though the mean number of adequate antidepressant trials during the current episode was approximately 1.5, the TMS effect sizes were larger in comparison to those achieved in antidepressant placebo-controlled trials. Thus, studies involving patients who have similar levels of treatment resistance need to be conducted before meaningful comparisons can be made between TMS and other approved treatments.


Have people had an unmistakable effect with TMS?

We conducted a study comparing ECT to TMS.5 Patients in this study had to be clinically appropriate for ECT. Often, they were reluctant to go forward with ECT for a variety of reasons, including potential adverse effects, the treatment’s cost, and the social stigma associated with it. Some of these patients had dramatic improvement with TMS. While TMS will not replace ECT, I think a proportion of patients who are referred for ECT may benefit from TMS as an alternative. We also reviewed the ECT-TMS literature which consists of several small, primarily single-site trials.6 Six out of eight studies reported that TMS was comparable to ECT and two studies found ECT superior. If these data are distilled into a clinically meaningful picture there may be a proportion of patients referred for ECT not because they are highly suicidal, psychotically depressed, in need of hospitalization, or having substantial compromise of their physical status but because they have not benefited from psychotherapy, medication, or a combination of the two. In addition, some may not tolerate adequate trials of medication for their depression. Presently, ECT may be the only option for them. Based on the data from the eight ECT-TMS comparison studies, the large Neuronetics-sponsored trial7 and several other sham control studies, as many as 30% to 40% of patients referred for ECT might benefit from TMS.


What are the side effects of TMS?

The Neuronetics’ trial has the largest database on adverse effects associated with TMS for treatment of depression.8 The most common were headaches and discomfort at the site of the application of the magnetic pulses. Both usually subsided in the first week of treatments. The discontinuation rate due to these adverse events was quite low. In terms of serious adverse events, no seizures or deaths occurred in >10,000 sessions involving >300 patients. Further, this study used the most aggressive set of parameters in terms of the intensity of the stimulation, number of stimulations per treatment session, number of sessions, and total number of stimulations over a course of treatment. For example, previous studies typically averaged 15,000–30,000 total magnetic pulses over an entire course of TMS. In the Neuronetics trial, the average number of pulses was 90,000. A small number of serious adverse events (primarily related to an exacerbation of the illness process) occurred primarily in patients who received the sham rather than the active procedure. From a safety tolerability point of view, TMS appears to be a benign treatment. The Neuronetics’ trial showed no evidence of cognitive deficits, consistent with the findings in the ECT-TMS comparison studies.

Over extended periods of time, the loud clicking sound that occurs near the acoustic nerve could potentially cause damage. However, all patients were required to wear ear plugs during the procedure and changes in the auditory threshold between the sham and active procedure did not differ. In terms of safety and tolerability, TMS looks much better than ECT or VNS. TMS may be even better tolerated than many antidepressants because there are no adverse systemic effects. In the Neuronetics’ trial, responders could enter a third phase transitioning from TMS to maintenance antidepressant monotherapy for 6 months. Some patients needed TMS reintroduced when they started to relapse. Two thirds of these patients benefited and returned to their prior stable mood levels. Further, these patients did not experience an increase in adverse events when TMS was combined with their antidepressant. Prior studies that used TMS as an augmentation strategy in partially but insufficiently responsive patients also reported that it was safe to combine TMS with various medications for depression.


Do you think DBS is a practical treatment?

DBS is an alternative to psychosurgery. It is a procedure neurosurgeons use for a variety of conditions because it is potentially reversible and causes minimal tissue damage, most of which involves the procedure placing the stimulating electrodes in the brain. The device is similar to the one used with VNS and is implanted in the upper chest region. Two wires run subcutaneously from the device behind the ears to the head where two small burr holes are drilled. The wires are implanted under stereotactic observation in the part of the brain that may be involved with a particular disease process (eg, Parkinson’s disease, dystonias, obsessive compulsive disorder, depression, Tourette’s syndrome). The level of electrical stimulation can be adjusted. Some patients who have had the electrical stimulation turned on report an almost immediate relief of symptoms which return when the electrical stimulation is turned off.

Medtronics makes the device most frequently used for DBS and is planning a multicentered trial for intractable depression. Mayberg and colleagues conducted an open-label pilot trial in which very seriously depressed patients had stimulating electrodes placed in Brodman’s Area-25.9 The study reported four of six patients who were unresponsive to a variety of treatment strategies experienced “striking and substantial remission” in their mood symptoms when the device was activated. PP



1.    Rush AJ, George MS, Sackeim HA, et al. Vagus nerve stimulation (VNS) for treatment-resistant depression:  a multicentered study. Biol Psychiatry. 2000;47(4):276-286.
2.    Sackeim HA, Rush AJ, George MS, et al. Vagus nerve stimulation (VNS) for treatment-resistant depression: Efficacy, side effects, and predictors of outcome. Neuropsychopharmacology. 2001;25(5):713-728.
3.    Rush AJ, Trivedi MH, Wisniewski SR, et al. Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: a STAR*D report. Am J Psychiatry. 2006;163(11):1905-1917.
4.    Trivedi MH, Fava M, Wisniewski SR, et al. Medication Augmentation after the failure of SSRIs for depression. New Engl J Med. 2006;354(12):1243-1252.
5.    Janicak PG, Dowd SM, Martis B, et al. Repetitive transcranial magnetic stimulation versus electroconvulsive therapy for major depressive: preliminary results of a randomized trial. Biol Psychiatry. 2002;51(8):659-667.
6.    Janicak PG, Dowd SM, Rosa M, Marcolin MA. Transcranial magnetic stimulation versus electroconvulsive therapy for the treatment of more severe major depression. In: Marcolin MA, Padberg F, eds. Transcranial Brain Stimulation for Treatment of Psychiatric Disorders. (Advances in Biological Psychiatry). Basel, Switzerland: Karger. 2007;23:97-109.
7.    O’Reardon JP, Solvason B, Janicak PG, et al. Efficacy and safety of repetitive transcranial magnetic stimulation (rTMS) in the acute treatment of major depression: results of a multicenter randomized controlled trial. Biol Psychiatry. 2007;62(11):1208-1216.
8.    Janicak PG, O’Reardon JP, Sampson SM, et al. Transcranial magnetic stimulation in the treatment of major depressive disorder: a comprehensive summary of safety experience from acute exposure, extended exposure and reintroduction treatment. J Clin Psychiatry. In press.
9.    Mayberg HS, Lozano AM, Voon V, et al. Deep brain stimulation for treatment-resistant depression. Neuron. 2005;45(5):651-660.