Guidelines Disconcordance in Acute Bipolar Depression: Data from the National Bipolar Mania Pathway Survey (BIPAS) in Mainland China
Bibliographic record
Abstract
With the recent attention to the importance of evidence-based medicine in psychiatry, a number of treatment guidelines have been published. This survey investigated prescribing pattern and predictors for guideline disconcordance in the acute treatment of bipolar depression across mainland China. Pharmacological treatments of 1078 patients with bipolar depression 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. Predictors for guidelines discordance were analyzed with logistic regression. Of the 1078 patients, 50.2% patients were treated against treatment guidelines recommendations. The patients who were treated in general hospitals (OR = 1.53, 95% CI 1.18–1.97), with a depressive episode (OR = 1.67, 95% CI 1.27–2.19) and an older age at first onset (OR = 1.62, 95% CI 1.15–2.28) were more likely to receive guideline-disconcordant treatment than their counterparts. In contrast, the patients with current mental comorbidity, an older age at study entry, a longer duration of disease, and more frequent episodes in past year were less likely to receive guideline-disconcordant treatments than their counterparts with an OR of 0.43 (95% CI 0.24–0.77), 0.52 (95CI% 0.36–0.75), 0.48 (95% CI 0.36–0.65), and 0.50 (95% CI 0.38–0.64), respectively. Our finding suggested the disconcordance with treatment guidelines in patients with an acute bipolar depression is common under naturalistic conditions in mainland China, and the predicting factors correlated with guidelines disconcordance include both psychiatrist-specific (clinicians from general hospitals) and patient-specific features (a depressive episode at first onset, no current co-morbidity with mental disorders, a younger age at study entry, an older age at first onset, shorter duration of disease, and non-frequent episodes in past year).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".