Age, Antipsychotics, and the Risk of Ischemic Stroke in the Veterans Health Administration
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Time-dependent effects of antipsychotics on risk of stroke and potential effect modification by age have not been fully investigated. A case-case-time-control design uses within- and between-case comparisons to evaluate short-term effects at the same time as adjusting for unmeasured time-invariant confounders and exposure-time trends. METHODS: We conducted a case-case-time-control design study using data from the Veterans Health Administration. Veterans with inpatient hospitalizations for ischemic stroke between 2002 and 2007 were included. For every stroke case, the "current" exposure period was defined as 1 to 30 days before hospitalization and the "reference" period as 91 to 120 days before hospitalization. Exposure during the current period was compared with exposure during the reference period within cases. Exposure-time trend-adjusted estimates of the effect of antipsychotic exposure on risk of stroke were obtained by dividing exposure odds for antipsychotic exposure by average exposure odds for other medications over the same time period among the same cases. RESULTS: After adjusting for exposure-time trends, odds of stroke were 1.8 (95% CI, (1.7-1.9) times higher when exposed to antipsychotics than when unexposed. Age-stratified estimates suggest a greater triggering effect of antipsychotics among older patients. CONCLUSIONS: Exposure to antipsychotics may be a proximal trigger for stroke. Elevation in risk is apparent after brief exposure to antipsychotics.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".