Antipsychotic use and myocardial infarction in older patients with treated dementia
Bibliographic record
Abstract
Background Antipsychotic agents (APs) are commonly prescribed to older patients with dementia. Antipsychotic use is associated with an increased risk of ischemic stroke in this population. Our study aimed to investigate the association of AP use with the risk of acute myocardial infarction (MI). Methods A retrospective cohort of community-dwelling older patients who initiated cholinesterase inhibitor treatment was identified between January 1, 2000, and December 31, 2009, using the Quebec, Canada, prescription claims database. From this source cohort, all new AP users during the study period were matched with a random sample of AP nonusers. The risk of MI was evaluated using Cox proportional hazards models, adjusting for age, sex, cardiovascular risk factors, psychotropic drug use, and propensity scores. In addition, a self-controlled case series study using conditional Poisson regression modeling was conducted. Results Among the source cohort of 37 138 cholinesterase inhibitor users, 10 969 (29.5%) initiated AP treatment. Within 1 year of initiating AP treatment, 1.3% of them had an incident MI. Hazard ratios for the risk of MI after initiation of AP treatment were 2.19 (95% CI, 1.11-4.32) for the first 30 days, 1.62 (95% CI, 0.99-2.65) for the first 60 days, 1.36 (95% CI, 0.89-2.08) for the first 90 days, and 1.15 (95% CI, 0.89-1.47) for the first 365 days. The self-controlled case series study conducted among 804 incident cases of MI among new AP users yielded incidence rate ratios of 1.78 (95% CI, 1.26-2.52) for the 1- to 30-day period, 1.67 (95% CI, 1.09-2.56) for the 31- to 60-day period, and 1.37 (95% CI, 0.82-2.28) for the 61- to 90-day period. Conclusion Antipsychotic use is associated with a modest and time-limited increase in the risk of MI among community-dwelling older patients treated with cholinesterase inhibitors.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".