Relative association of treatment‐emergent adverse events with quality of life of patients with schizophrenia: <i>post hoc</i> analysis from a 3‐year observational study
Bibliographic record
Abstract
OBJECTIVE: To explore the relative association of adverse events with health-related quality of life (HRQL) in patients (N = 16 091) with schizophrenia, treated with antipsychotic medication. METHODS: In this post hoc analysis of data from two 3-year observational studies, a mixed effects model with repeated measures was used to evaluate the association between HRQL (EuroQoL visual analogue scale (EQ-VAS)) and pre-specified covariates including: severity of illness, extrapyramidal symptoms, tardive dyskinesia, sexual dysfunction, and clinically significant weight gain (> 7% increase from baseline after > or = 3 months of treatment). RESULTS: Mean EQ-VAS increased from 47.8 +/- 21.7 at baseline to 72.4 +/- 18.4 after 36 months. The rank order of the negative association of adverse events with HRQL was: sexual dysfunction (effect estimate -4.04; 95% CI -4.30 to -3.79), extrapyramidal symptoms (effect estimate -2.09; 95% CI -2.43 to -1.75), and tardive dyskinesia (effect estimate -0.89; 95% CI -1.46 to -0.32). CONCLUSIONS: Differences were observed in the direction and magnitude of the association between each adverse event and HRQL. Recognition of the relative association of adverse events with HRQL may contribute to improved adherence of patients with schizophrenia to antipsychotic therapy.
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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 | 0.013 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.007 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".