Systematic literature review of schizophrenia clinical practice guidelines on acute and maintenance management with antipsychotics
Bibliographic record
Abstract
Clinical practice guidelines (CPGs) translate evidence into recommendations to improve patient care and outcomes. To provide an overview of schizophrenia CPGs, we conducted a systematic literature review of English-language CPGs and synthesized current recommendations for the acute and maintenance management with antipsychotics. Searches for schizophrenia CPGs were conducted in MEDLINE/Embase from 1/1/2004-12/19/2019 and in guideline websites until 06/01/2020. Of 19 CPGs, 17 (89.5%) commented on first-episode schizophrenia (FES), with all recommending antipsychotic monotherapy, but without agreement on preferred antipsychotic. Of 18 CPGs commenting on maintenance therapy, 10 (55.6%) made no recommendations on the appropriate maximum duration of maintenance therapy, noting instead individualization of care. Eighteen (94.7%) CPGs commented on long-acting injectable antipsychotics (LAIs), mainly in cases of nonadherence (77.8%), maintenance care (72.2%), or patient preference (66.7%), with 5 (27.8%) CPGs recommending LAIs for FES. For treatment-resistant schizophrenia, 15/15 CPGs recommended clozapine. Only 7/19 (38.8%) CPGs included a treatment algorithm.
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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 | 0.030 | 0.137 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.025 | 0.022 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".