Comparing tolerability profile of quetiapine, risperidone, aripiprazole and ziprasidone in schizophrenia and affective disorders: a meta-analysis
Bibliographic record
Abstract
OBJECTIVE: Second-generation antipsychotics (SGAs) are extensively prescribed for psychiatric disorders. Based on clinical observations, schizophrenia (SCZ) and affective disorder (AD) patients can experience different SGA side effects. The expanded use of SGAs in psychiatry suggests a need to investigate whether there is a difference in the incidence and severity of side effects related to diagnosis. METHODS: A comprehensive literature search was conducted to identify studies reporting side effects of four common prescribed SGAs (aripiprazole, quetiapine, risperidone and ziprasidone) in the treatment of SCZ or AD. Randomized controlled trials were included in this study if they administered oral SGAs as a monotherapy, in adult patients. The metabolic and extrapyramidal side effects were collected separately for each group, and then were combined in a meta-analysis. RESULTS: 80 studies were included in the analysis (N = 14,319). Quetiapine treatment induced significantly higher low-density lipoprotein (LDL) and total blood cholesterol mean change in the SCZ group, relative to the AD group. Based on the results, the incidence of extrapyramidal side effects was more frequent in the AD group. Aripiprazole treatment led to significantly more akathisia incidence in the AD group, compared with the SCZ group. CONCLUSION: The results suggest that SCZ patients may be more vulnerable to some SGA-induced metabolic disturbances, in which lifestyle risk factors and possible inherent genetic vulnerabilities may play a role. Most of the studied SGAs caused more movement disorders in AD patients than SCZ. It might be that an antipsychotic induces severity of side effect according to the phenotype.
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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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.060 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".