Pharmacotherapy for acute mania and disconcordance with treatment guidelines: bipolar mania pathway survey (BIPAS) in mainland China
Bibliographic record
Abstract
BACKGROUND: With the recent attention to evidence-based medicine in psychiatry, a number of treatment guidelines for bipolar disorders have been published. This survey investigated prescribing patterns and predictors for guideline disconcordance in the acute treatment of a manic and mixed episode across mainland China. METHODS: The pharmacological treatments of 2828 patients with a recent hypomanic/manic episode or mixed state were examined. Guidelines disconcordance was determined by comparing the medication(s) patients were prescribed with the recommendation(s) in the guidelines of the Canadian Network for Mood and Anxiety Treatments. RESULTS: The most common pattern of pharmacological treatments for an acute manic or mixed episode was a mood stabilizer plus an atypical antipsychotic (n = 1345, 47.6%), and the rate of guideline-disconcordant treatments was 11.1%. The patients who were treated in general hospitals were more likely to receive guideline-disconcordant treatments than those who were treated in psychiatric hospitals, with an OR of 1.84 (95% CI 1.44-2.36). Similarly, the patients with a mixed episode at study entry were more likely to receive guideline-disconcordant treatments than those with a manic episode, with an OR of 1.69 (95% CI 1.22-2.35). In contrast, the patients with a longer duration of disease (>5 years) were less likely to receive guideline-disconcordant treatments than those with a short duration, with an OR of 0.47 (95% CI 0.36-0.60). CONCLUSIONS: In mainland China, the disconcordance with treatment guidelines for a most recent acute manic or mixed episode was modest under naturalistic conditions. The higher risk for disconcordance in general hospitals than in psychiatric hospitals suggests that special education based on treatment guidelines to practitioners in general hospitals is necessary in order to reduce the risk for disconcordant treatments.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".