Clozapine and the Course of Bipolar Disorder in the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD): La clozapine et l’évolution du trouble bipolaire dans le Programme d’amélioration systématique du traitement du trouble bipolaire (STEP-BD)
Bibliographic record
Abstract
Objective: The potential of clozapine in severe bipolar disorder is suggested by its efficacy in refractory schizophrenia, but the evidence is limited thus far. This report utilizes data from the standard care pathway of the Systematic Treatment Enhancement Program to examine the clinical impact of clozapine in bipolar disorder, comparing it to two groups, one that received olanzapine and an additional group that received neither drug. Method: A total of 4,032 outpatients were available for this analysis. Groups for longitudinal analyses are based on the medication used at each visit. Outcomes assessed were clinical status, symptoms subscales, hospitalizations, and death. We utilized mixed models and generalized estimating equations to adjust for baseline differences and investigate longitudinal differences in symptoms, clinical status, and hospitalization rates between groups. Results: During the study, 1.1% ( n = 43) of the patients used clozapine at any time. Those on clozapine had significantly fewer manic and depressive symptoms during follow-up as compared with those on neither clozapine nor olanzapine, while those on olanzapine had more symptoms. The use of clozapine was not associated with an increased risk of hospitalization. No deaths were recorded for clozapine group during the trial. Conclusions: Although prescribed to very few patients, the impact of clozapine was notable, with fewer symptoms in patients who had more severe illnesses at baseline. Clozapine could prove to be as successful an intervention for late-stage bipolar disorder as it has been in schizophrenia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".