M112. Clozapine Use in Early-Intervention Programs Across Canada
Bibliographic record
Abstract
Background: Clozapine remains to this day the treatment of choice for people with schizophrenia who have failed to respond to 2 consecutive antipsychotic trials. It is estimated that approximately 20% of first-episode psychotic patients fail to respond adequately to 2 consecutive antipsychotic trials, thereby meeting criteria for a Clozapine trial. As much as 80% of the first-episode patients meeting criteria for a Clozapine trial who undergo such a trial could show a robust response. Methods: A survey on Clozapine use was conducted across 11 early intervention programs in Canada (total N = 1771). We used Fleiss’ method (a meta-analysis technique) to derive mean prevalence estimates and to compare rates across programs according to 6 program characteristics. Results: The weighted mean rates of Clozapine use across programs was 13.5% (95% CI: 7.1%, 19%). The rates varied from 4.4% to 30%; these variations in rates of Clozapine use across programs were highly significant (P < .0001). Rates of CLZ use were higher in programs that that use a systematic algorithm to assess treatment resistance (17.2%) vs those that do not (13.6%; P < .0001); that have hospital beds (17.3%) vs those that do not (9.5%; P < .0001); that have a follow-up ≥ 3 years (14.2%) vs those with a <3-year follow-up (6.8%; P < .0001). There were no differences in rates of Clozapine use according to: (1) the inclusion or not of teenagers; (2) the percentage of patients in the first year of treatment; (3) the upper limit in duration of prior treatment for inclusion in the program. However, there was highly significant heterogeneity within all these groups. Conclusion: This survey thus documented rates of CLZ use in these early intervention programs that are even higher than the rates generally observed in other settings including more chronic patients. It also documented very important variations in rates of Clozapine use across these programs. We identified at least 3 distinct program characteristics that could account for part of this heterogeneity. However, there was highly significant heterogeneity across groups of programs defined according to any of these characteristics; hence, other sources of variations in Clozapine have yet to be identified. Hence, data at an individual level are needed to better understand the determinants of Clozapine use. Such data could eventually lead to recommendations to guide optimal Clozapine use in early intervention programs; we are currently completing such an investigation based on individual chart reviews.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".