change in a neurocognitive composite score after 2 months of treatment. Secondary outcomes included neurocognitive composite score change at 6 months and 18 months after continued treatment and changes in neurocognitive domains. Results: At 2 months, treatment resulted in small neurocognitive improvements of z= 0.13 for olanzapine (P.002), 0.25 for perphenazine (P.001), 0.18 for quetiapine (P.001), 0.26 for risperidone (P.001), and 0.12 for ziprasidone (P.06), with no significant differences between groups. Results at 6 months were similar. After 18 months of treatment, neurocognitive improvement was greater in the perphenazine group than in the olanzapine and risperidone groups. Neurocognitive improvement predicted longer time to treatment discontinuation, independently from symptom improvement, in patients treated with quetiapine or ziprasidone. Conclusions: After 2 months of antipsychotic treatment, all groups had a small but significant improvement in neurocognition. There were no differences between any pair of agents, including the typical drug perphenazine. These results differ from the majority of previous studies, and the possible reasons are discussed.

/pdf/neurocognitive-effects-of-antipsychotic-medications-in-x1fok1zvcv.pdf

Neurocognitive Effects of Antipsychotic Medications in Patients With Chronic Schizophrenia in the CATIE Trial

Practice guideline for the treatment of patients with obsessive-compulsive disorder.

Anxiety and related disorders are among the most common mental disorders, with lifetime prevalence reportedly as high as 31%. Unfortunately, anxiety disorders are under-diagnosed and under-treated. These guidelines were developed by Canadian experts in anxiety and related disorders through a consensus process. Data on the epidemiology, diagnosis, and treatment (psychological and pharmacological) were obtained through MEDLINE, PsycINFO, and manual searches (1980–2012). Treatment strategies were rated on strength of evidence, and a clinical recommendation for each intervention was made, based on global impression of efficacy, effectiveness, and side effects, using a modified version of the periodic health examination guidelines. These guidelines are presented in 10 sections, including an introduction, principles of diagnosis and management, six sections (Sections 3 through 8) on the specific anxiety-related disorders (panic disorder, agoraphobia, specific phobia, social anxiety disorder, generalized anxiety disorder, obsessive-compulsive disorder, and posttraumatic stress disorder), and two additional sections on special populations (children/adolescents, pregnant/lactating women, and the elderly) and clinical issues in patients with comorbid conditions. Anxiety and related disorders are very common in clinical practice, and frequently comorbid with other psychiatric and medical conditions. Optimal management requires a good understanding of the efficacy and side effect profiles of pharmacological and psychological treatments.

/pdf/canadian-clinical-practice-guidelines-for-the-management-of-3kjxn44j0v.pdf

Canadian clinical practice guidelines for the management of anxiety, posttraumatic stress and obsessive-compulsive disorders

SummaryIn this report, recommendations for the pharmacological treatment of anxiety and obsessive-compulsive disorders are presented, based on available randomized, placebo-or comparator-controlled

/pdf/world-federation-of-societies-of-biological-psychiatry-wfsbp-4hulj8ttls.pdf

World Federation of Societies of Biological Psychiatry (WFSBP) Guidelines for the Pharmacological Treatment of Anxiety, Obsessive-Compulsive and Post-Traumatic Stress Disorders – First Revision

Social anxiety disorder.

Objective To describe the prevalence of patients who screen positive for symptoms of bipolar disorder in primary care practice using the validated Mood Disorders Questionnaire (MDQ). Design Prevalence survey. Setting Fifty-four primary care practices across Canada. Participants Adult patients presenting to their primary care practitioners for any cause and reporting, during the course of their visits, current or previous symptoms of depression, anxiety, substance use disorders, or attention deficit hyperactivity disorder. Main outcome measures Subjects were screened for symptoms suggestive of bipolar disorder using the MDQ. Health-related quality of life, functional impairment, and work productivity were evaluated using the 12-Item Short-Form Health Survey and Sheehan Disability Scale. Results A total of 1416 patients were approached to participate in this study, and 1304 completed the survey. Of these, 27.9% screened positive for symptoms of bipolar disorder. All 13 items of the MDQ were significantly associated with screening positive for bipolar disorder (P < .05). Patients screening positive were significantly more likely to report depression, anxiety, substance use, attention deficit hyperactivity disorder, family history of bipolar disorder, or suicide attempts than patients screening negative were (P < .001). Health-related quality of life, work or school productivity, and social and family functioning were all significantly worse in patients who screened positive (P < .001). Conclusion This prevalence survey suggests that more than a quarter of patients presenting to primary care with past or current psychiatric indices are at risk of bipolar disorder. Patients exhibiting a cluster of these symptoms should be further questioned on family history of bipolar disorder and suicide attempts, and selectively screened for symptoms suggestive of bipolar disorder using the quick and high-yielding MDQ.

https://www.cfp.ca/content/cfp/57/2/e58.full.pdf

Prevalence of Bipolar Disorder symptoms in Primary Care (ProBiD-PC): A Canadian study

Background Screening for major depressive disorder (MDD) in tertiary care settings can be challenging, as patients often present with complex symptom profiles and false positives are common. We used machine learning (ML) to test our composite screening application—EarlyDetect (ED), which includes extant validated scales as well as a selection of life history factors—for predictive accuracy, with the central aim of improving specificity in tertiary settings. Methods This was a retrospective, naturalistic study at a tertiary mental health centre in western Canada. Participants (n = 955; 56.4% female; mean age 35.4; 34.6% MDD) completed ED and underwent a clinical interview with a blinded psychiatrist for diagnostic accuracy. ML was used to make more confident predictions at an individual level. Results Using composite scoring, the balanced accuracy of our tool was 72.0%, with a sensitivity of 74.2% and a specificity of 69.8%, with an AUC of 0.781. Compared with the MDD symptoms-only model, the fully composite ED model improved balanced accuracy by 5.6%, specificity by 13%, and AUC by 0.072. Limitations Patients were assessed using clinical psychiatric evaluations, which are subjective. There is also the potential for self-reporting bias, particularly with depressed patients. Finally, the cross-sectional design of this study rules out conclusions of causality. Conclusions Our results show improved MDD. detection accuracy using composite measures and highlight key predictive factors that contribute to the accurate diagnosis of MDD, including disability, family history of mental illness, and stressful events. These factors may need to be included in regular screening assessments.

Screening for major depressive disorder in a tertiary mental health centre using EarlyDetect: A machine learning-based pilot study

Dear Editor: We would like to thank Dr Paris and colleagues for bringing much-needed focus to adults suffering with attention-deficit hyperactivity disorder (ADHD), an illness associated with considerable personal and societal burden. We share their goal of ensuring that patients are correctly diagnosed by applying evidence-based screening and diagnostic criteria for ADHD. However, we have concerns with the negative tone of Paris et al.’s article, which may further stigmatize this illness and prevent people with ADHD from receiving the treatment they deserve. Paris et al. expressed concerns about overdiagnosis of ADHD despite a lack of evidence to support this. The increase in diagnosis of ADHD has followed a similar trajectory as other psychiatric disorders that were once thought to be rare, such as social anxiety, autism spectrum disorder, and bipolar II disorder. It only seems logical that an increase in the recognition of the disorder in children would lead to rising rates of ADHD in adulthood, as central nervous system dysfunction leading to attentional problems would not be expected to disappear after the 18th birthday. Perhaps Paris et al.’s article suggests a profound misunderstanding of the syndromal presentation of ADHD, which includes attentional difficulties and also deficits in executive function, affective dysregulation, and higher risk of accidents, premature death, marital discord, and educational and vocational underachievement. Effective treatment of ADHD improves symptoms, emotional lability, and patient functioning. While Paris et al.’s main concern is overtreatment of ADHD, we believe the risks of missed diagnosis and undertreatment, are far more compelling. Paris et al.’s article could deter some people from seeking help, and discourage clinicians from assessing and treating ADHD. They suggest nonmedical benefit seeking of people on ADHD treatments. This contrasts with literature suggesting that stimulants do not enhance cognitive performance outside the treatment of ADHD. It is ridiculous to suggest that researchers are inflating prevalence rates to boost their funding for grants or that the pharmaceutical industry is medicalizing ADHD to market new stimulants. Paris et al.’s criticism of clinicians for overrelying on screening tools, or for treating without establishing a correct diagnosis of ADHD, ignores the facts that the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, requires that the clinical interview confirm both childhood onset and impairment to establish a diagnosis of ADHD and the diagnostic criteria appear to be working. Studies suggest up to 40% of adults seeking an evaluation for ADHD do not meet full criteria for the disorder. In contrast to Paris et al.’s position, there is no evidence supporting the value of neuropsychological testing for improving the accuracy of diagnosis; indeed, neuropsychological testing may contribute to worsening diagnostic accuracy by missing up to one-third of confirmed ADHD cases. As clinicians in the field, we must be mindful of misdiagnosis of any psychiatric condition, and remind the authors that patients deserve the best evidence-based assessments and treatments for ADHD, but they do not benefit from a perspective paper that further exacerbates the stigmatization of the disorder in the field of psychiatry.

https://journals.sagepub.com/doi/pdf/10.1177/0706743715620143

Re: Is Adult Attention-Deficit Hyperactivity Disorder Being Overdiagnosed?

Background: Some studies suggest that it is important to take the end of “T” wave to quantify QT-interval variability, which signifies cardiac repolarization lability, as there is substantial and important information beyond the peak of the T wave on the surface electrocardiogram.



Methods: In this study, we examined the relationship between the variability of beat-to-beat RTe (beginning of R-peak to T-end) and the variability of RTp (R-peak to T-peak) in the following groups: normal controls (n = 26), patients with anxiety (n = 26), and patients with cardiovascular disease with or without diabetes (n = 63). We obtained ECG sampled at 1024 Hz in lead II configuration in supine posture to obtain beat-to-beat interbeat interval (R–R) and RT-interval variability for 256 seconds.



Results: We found significant positive correlations (r = 0.8; P < 0.00001) in normal controls and patients with anxiety between the variability of RTeVI and RTpVI (RTe and RTp variability indices, respectively, corrected for the mean of RTe and RTp and the mean and the variance of R–R). These correlations were also statistically significant in the medically ill group but the r values were much smaller (r = 0.45 in various groups). The slopes were also significantly different between the two groups (P < 0.001). Bland–Altman plots also showed better agreement between the two measures in the controls and patients with anxiety compared to the group with cardiovascular disease.



Conclusions: These findings have methodological implications for studies comparing people with and without overt cardiovascular illness. While RTe or RTp variability index may be used interchangeably in normal controls and some patients with no overt cardiovascular problems, it may be more prudent to use both RTe and RTp variability indices in patients with cardiovascular illness. These indices, especially RTeVI, may provide different information about cardiac repolarization lability. Future studies should address the importance of the relative usefulness of these two measures especially in cardiac patients before and after successful treatment.

Relationship between beat-to-beat variability of RT-peak and RT-end intervals in normal controls, patients with anxiety, and patients with cardiovascular disease.

By 2020, depression is projected to be among the most important contributors to the global burden of disease. A plethora of data confirms that despite the availability of effective therapies, major depressive disorder continues to exact an enormous toll; this, in part, is due to difficulties reaching complete remission, as well as the specific associated costs of both the disorder's morbidity and mortality. The negative effects of depression include those on patients' occupational functioning, including absenteeism, presenteeism, and reduced opportunities for educational and work success. The use of management algorithms has been shown to improve treatment outcomes in major depressive disorder and may be less costly than “usual care” practices. Nevertheless, many patients with depression remain untreated. As well, even those who are treated often continue to experience suboptimal quality of life. As such, the treatment algorithms in this article may improve outcomes for patients suffering with depression. This paper introduces some of the principal reasons underlying these treatment gaps and examines measures or recommendations that might be changed or strengthened in future practice guidelines to bridge them.

Pratap Chokka

Papers

Prevalence of Bipolar Disorder symptoms in Primary Care (ProBiD-PC): A Canadian study

Screening for major depressive disorder in a tertiary mental health centre using EarlyDetect: A machine learning-based pilot study

Re: Is Adult Attention-Deficit Hyperactivity Disorder Being Overdiagnosed?

Relationship between beat-to-beat variability of RT-peak and RT-end intervals in normal controls, patients with anxiety, and patients with cardiovascular disease.

Food for thought: understanding the value, variety and usage of management algorithms for major depressive disorder.