Bipolar Disorder: A Clinician's Guide to Biological Treatments
Bibliographic record
Abstract
Bipolar Disorder: A Clinician's Guide to Biological Treatments. Lakshmi N Yatham, Vivek Kusumaker, Stanley Kutcher, editors. New York: Brunner-Routledge; 2002. 320p. US$60.00. Reviewer rating: Excellent What an excellent guidebook! We realize it is not typical for a book review to open with such an effusive statement; however, this book certainly deserves this level of praise from all North American clinical psychiatrists. Currently, bipolar disorder (BD) is the preeminent psychiatric disorder of interest to both practising psychiatrists and the public at large. It is a complex disorder, presenting frequently, perniciously, and confusingly to our offices, with patient stories of misdiagnosis and inappropriate treatment being the rule. We psychiatrists have all wished for a wise, fair, balanced, research-driven, yet clinically useful guide to advise us as we attempt to help our BD patients with pharmacotherapy. Here is the long-awaited, clinician-centred guide to the pharmacotherapy of BD. The editors of this book are widely respected international authorities on this topic. Additionally, the list of contributors reads like an all-star cast of the best and brightest in the field in Canada and the US. The book has 12 mostly multiauthored chapters, each of which focuses on important aspects of BD. The first 2 chapters focus on different phases of the illness-hypomania or mania and depression. Successive chapters focus on rapid cycling, maintenance therapy, special population issues, and comorbidities with other Axis I diagnoses. The next 4 chapters focus on separate classes of medications used in the treatment of BD: lithium, atypical neuroleptics, antidepressants, and anticonvulsants. There is also a chapter on somatic treatment for BD. The book ends with a chapter on pharmacologie issues pertaining to the medications, including possible adverse effects and their management. With so many authors writing separate chapters, there is understandably some overlap in material covered. This, however, is not distracting. The opening chapter on the diagnosis and treatment of hypomania and mania is a tour de force, with an excellent discussion of the clinical pitfalls that face each of us as we assess patients with mood disorders. The authors have clearly kept practising clinician readers in mind: they have broken the chapter into sections that closely follow how clinicians assess and treat these patients. There is a wonderfully thought-out section on rationale in designing treatment strategies and an equally useful and practical treatment algorithm section. The second chapter, on bipolar depression, does not offer as many pearls of wisdom, but this is because our understanding of the treatment of bipolar depression is less well studied. Experts, particularly those from Europe, have differing views on this subject. …
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.051 | 0.086 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".