QTc prolongation in patients with schizophrenia taking antipsychotics: Prevalence and risk factors
Bibliographic record
Abstract
Background:QTc prolongation is one of the possible complications in patients with schizophrenia taking antipsychotics, which leads to malignant cardiac arrhythmia. No meta-analysis has been reported assessing the prevalence and correlated risk factors for QTc prolongation.Methods:This meta-analysis aimed to assess the evidence for the prevalence of QTc prolongation and correlated risk factors in patients with schizophrenia taking antipsychotics. Web of Science and PubMed were searched according to preset strategy. The quality of research was assessed by the Newcastle–Ottawa Scale (NOS).Results:In all, 15 studies covering 15,540 patients with schizophrenia taking antipsychotics were included. Meta-analysis showed that the prevalence of QTc prolongation in patients with schizophrenia taking antipsychotics was about 4.0% (95% confidence interval (CI): 3.0%–5.0%, p < 0.001). The prevalence was about 4.0% in Asia (95%CI: 3.0%–6.0%, p < 0.001), about 5.0% in Europe (95%CI: 2.0%–7.0%, p < 0.001), and about 2.0% in America (95%CI: 1.0%–3.0%, p < 0.001). Sensitivity analyses indicated the robustness of the result. Publication bias analysis reported a certain publication bias (t = 3.37, p = 0.012). Meta-regression suggested that female and elderly patients were clinically associated with a higher prevalence of QTc prolongation. According to included studies, smoking, comorbidity of cardiovascular disease, and abnormal levels of high-density lipoprotein/low-density lipoprotein might be related to QTc prolongation in patients with schizophrenia taking antipsychotics.Conclusions:The prevalence of QTc prolongation in patients with schizophrenia taking antipsychotics was about 4.0%. Female and elderly patients were more likely to experience QTc prolongation. Close electrocardiogram monitoring was suggested in these at-risk populations.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.015 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".