Adverse Events in Elderly Users of Antipsychotic Pharmacotherapy in the Province of Manitoba
Bibliographic record
Abstract
BACKGROUND: Antipsychotic medications have been widely used in elderly patients for treatment of a variety of diagnoses. The aim of our study was to compare the incidence of cerebrovascular and cardiac events as well as mortality in elderly persons treated with second-generation antipsychotics (SGAs) with that of elderly persons treated with conventional first-generation agents (FGAs) in the province of Manitoba. METHODS: A population-based retrospective cohort study of all residents of Manitoba aged 65 and older, who were dispensed antipsychotic medications for the first time during the period from April 1, 2000, to March 31, 2007, was conducted using Manitoba Health administrative databases. Cox proportional hazards models were used to compare risks of adverse events in FGA and SGA users. RESULTS: After controlling for potential confounders (demographics, comorbidity, and medication use), SGA use was not associated with a significantly greater risk of cerebrovascular events, cardiac arrhythmia, and congestive heart failure compared to FGA use (adjusted hazard ratios [HR], respectively: 1.136; 95% CI, 0.961-1.344; 0.865; 95% CI, 0.336-2.232; 1.127, 95% CI, 0.902-1.409). Second-generation antipsychotics users were found to be at a lower risk of mortality (adjusted HR, 0.683; 95% CI, 0.577-0.809), but at a higher risk of myocardial infarction (adjusted HR, 1.614; 95% CI, 1.024-2.543) compared to FGA users. CONCLUSIONS: Among elderly users of antipsychotic medications, the risk of cerebrovascular events, cardiac arrhythmia, and congestive heart failure was similar in FGA and SGA users. Whereas SGA users were at a higher risk of nonfatal myocardial infarction, the use of FGAs was associated with an increased risk of death. Antipsychotic pharmacotherapy in older persons needs to be chosen with careful consideration of all risks and benefits.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".