Pragmatic issues and prescribing patterns in bipolar disorder
Bibliographic record
Abstract
ABSTRACT Background: There is substantial treatment gap between the suggested guidelines and pragmatic clinical practice for psychotropic usage in bipolar disorder (BD) due to the lack of naturalistic studies and not taking into account the transcultural differences and diverse background. We intend to study this treatment gap and elucidate the preference of psychotropics and prescription patterns, critical clinical issues faced and related pragmatics in BD by conducting the mental health professionals survey. Methodology: After focused discussions, Canadian Network for Mood and Anxiety Treatments guidelines being the primary anchor, a 46-item online survey questionnaire was prepared. With 25.4% response rate, 127 psychiatrists were evaluated using Survey Monkey® electronic platform on the demographics, predominant polarity; usage of antipsychotics, antidepressants, and electroconvulsive therapy, psychotropic's preference (monotherapy vs. polytherapy) in the acute and maintenance phase of BD. Results: Majority of the participants were males (70.9%) and placed in government institute or medical colleges. Majority agreed that child and adolescent and old age bipolar probands are not routinely seen but subthreshold BD cases are frequent; did not prefer mood stabilizer in pregnancy (61.4%) and antidepressants, preferred polytherapy in acute but monotherapy in maintenance phase (after 3 rd episode), seldom preferred ECT as an option (more in suicidality), agreed to a subset of BD being refractory and neuroprogressive. Conclusion: This study elucidates the importance of treatment preferences, prescribing patterns and pragmatic issues faced by the clinicians. These patterns if studied longitudinally in a systematic manner would help in modifying the potential treatment strategies and reduce treatment gap.
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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 | 0.004 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".