Older Men with Dementia Are at Greater Risk than Women of Serious Events After Initiating Antipsychotic Therapy
Bibliographic record
Abstract
OBJECTIVES: To understand how drug therapy differently affects older women and men. DESIGN: Population-based, retrospective cohort study. SETTING: Ontario, Canada. PARTICIPANTS: Twenty-one thousand five hundred twenty-six older adults (13,760 women, 7,766 men) with dementia newly started on oral atypical antipsychotic therapy between April 1, 2007, and March 1, 2010. MEASUREMENTS: Numbers and rates of serious events. Serious events were defined as a hospital admission or death within 30 days of treatment initiation. Unadjusted and adjusted odds ratios of women and men were compared in the full cohort and in strata based on setting of care, age, Charlson Comorbidity Index (CCI), and antipsychotic dose. RESULTS: Of 21,526 older adults with a median age of 84, 1,889 (8.8%) had a serious event (1,044 women, 7.6%; 845 men, 10.9%). Of these, 363 women (2.6%) and 355 men (4.6%) died. Men were more likely than women to be hospitalized or die during the 30-day follow-up period (adjusted odds ratio = 1.47, 95% confidence interval = 1.33-1.62) and consistently more likely to experience a serious event in each stratum. A gradient of risk according to drug dose was found for the development of a serious event in women and men. CONCLUSION: The risk of developing a serious event shortly after the initiation of antipsychotic therapy was high in women and men with dementia but was consistently higher in older men. This pattern remained the same in strata based on setting of care, age, CCI, and antipsychotic dose.
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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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".