Clozapine Optimization: A Delphi Consensus Guideline From the Treatment Response and Resistance in Psychosis Working Group
Bibliographic record
Abstract
BACKGROUND AND HYPOTHESIS: There is limited evidence to guide the approaches to clozapine treatment. Accordingly, an international initiative was undertaken with the aim of developing consensus recommendations for the optimization of clozapine monotherapy. STUDY DESIGN: We conducted an online Delphi survey among members of the Treatment Response and Resistance in Psychosis (TRRIP) working group comprising experts from twenty-nine countries. The threshold criterion for a consensus recommendation was ≥ 75% agreement ("agree" and "strongly agree" responses) on a question. Agreement of ≥ 50% but < 75% in a second or third Delphi round was deemed to provide guidance. STUDY RESULTS: Forty-nine (first round), 32 (second round), and 48 (third round) of the 91 current TRRIP members participated. Expert recommendations at ≥ 75% comprised second-line treatment with clozapine in cases of persistent positive symptoms with co-occurring extrapyramidal symptoms, tardive dyskinesia, or suicidality/aggression. There was considerable disagreement on myocarditis screening parameters. The management of somatic and neuropsychiatric adverse drug reactions warrants further research for more evidence-based recommendations. Rechallenge with clozapine was recommended for eosinophilia, sinus tachycardia and fever and guidance (agreement ≥ 50%) was reached for pneumonia and thrombocytopenia. CONCLUSIONS: Given the limited evidence available, this consensus-based series of recommendations and guidance statements supports clinical decision-making to optimize clozapine monotherapy and provides guidance for future research in treatment-resistant 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 | 0.198 | 0.160 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".