Antipsychotic polypharmacy and metabolic syndrome in schizophrenia: a review of systematic reviews
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: There is conflicting evidence on the association between antipsychotic polypharmacy and metabolic syndrome in schizophrenia. We conducted a review of published systematic reviews to evaluate evidence on the association between metabolic syndrome (diabetes, hypertension, and hyperlipidaemia) and exposure to antipsychotic polypharmacy in schizophrenia. METHODS: We searched five electronic databases, complemented by reference screening, to find systematic reviews that investigated the association of antipsychotic polypharmacy in schizophrenia with hypertension, diabetes, or hyperlipidaemia. Selection of reviews, data extraction and review quality were conducted independently by two people and disagreements resolved by discussion. Results were synthesised narratively. RESULTS: We included 12 systematic reviews, which reported heterogeneous results, mostly with narrative syntheses and without pooled data. The evidence was rated as low quality. There was some indication of a possible protective effect of drug combinations including aripiprazole for diabetes and hyperlipidaemias, compared to other combinations and/or monotherapy. Only one review reported the association between APP and hypertension. The most frequently reported combinations of medication included clozapine, possibly representing a sample of patients with treatment resistant illness. No included review reported results separately by setting (primary or secondary care). CONCLUSIONS: Further robust studies are needed to elucidate the possible protective effect of aripiprazole. Long-term prospective studies are required for accurate appraisal of diabetes risk, hypertension and hyperlipidaemia in patients exposed to antipsychotic polypharmacy.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it