One-year survival and admission to hospital for cardiovascular events among older residents of long-term care facilities who were prescribed intensive- and moderate-dose statins
Bibliographic record
Abstract
BACKGROUND: Guidance from randomized clinical trials about the ongoing benefits of statin therapies in residents of long-term care facilities is lacking. We sought to examine the effect of statin dose on 1-year survival and admission to hospital for cardiovascular events in this setting. METHODS: We conducted a retrospective cohort study using population-based administrative data from Ontario, Canada. We identified 21 808 residents in long-term care facilities who were 76 years of age and older and were prevalent statin users on the date of a full clinical assessment between April 2013 and March 2014, and categorized residents as intensive- or moderate-dose users. Treatment groups were matched on age, sex, admission to hospital for atherosclerotic cardiovascular disease, resident frailty and propensity score. Differences in 1-year survival and admission to hospital for cardiovascular events were measured using Cox proportional and subdistribution hazard models, respectively. RESULTS: Using propensity-score matching, we included 4577 well-balanced pairs of residents who were taking intensive- and moderate-dose statins. After 1 year, there were 1210 (26.4%) deaths and 524 (11.5%) admissions to hospital for cardiovascular events among residents using moderate-dose statins compared with 1173 (25.6%) deaths and 522 (11.4%) admissions to hospital for cardiovascular events among those taking intensive-dose statins. We found no significant association between prevalent use of intensive-dose statins and 1-year survival (hazard ratio [HR] 0.97, 95% confidence interval [CI] 0.90 to 1.05) or 1-year admission to hospital for cardiovascular events (HR 0.99, 95% CI 0.88 to 1.12) compared with use of moderate-dose statins. INTERPRETATION: The rates of mortality and admission to hospital for cardiovascular events at 1 year were similar between residents in long-term care taking intensive-dose statins compared with those taking moderate-dose statins. This lack of benefit should be considered when prescribing statins to vulnerable residents of long-term care facilities who are at potentially increased risk of statin-related adverse events.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".