Delirium after elective surgery among elderly patients taking statins
Bibliographic record
Abstract
BACKGROUND: Postoperative delirium after elective surgery is frequent and potentially serious. We sought to determine whether the use of statin medications was associated with a higher risk of postoperative delirium than other medications that do not alter microvascular autoregulation. METHODS: We conducted a retrospective cohort analysis of 284 158 consecutive patients in Ontario aged 65 years and older who were admitted for elective surgery. We identified exposure to statins from outpatient pharmacy records before admission. We identified delirium by examining hospital records after surgery. RESULTS: About 7% (n = 19 501) of the patients were taking statins. Overall, 3195 patients experienced postoperative delirium; the rate was significantly higher among patients taking statins (14 per 1000) than among those not taking statins (11 per 1000) (odds ratio [OR] 1.30, 95% confidence interval [CI] 1.15-1.47, p < 0.001). The increased risk of postoperative delirium persisted after we adjusted for multiple demographic, medical and surgical factors (OR 1.28, 95% CI 1.12-1.46) and exceeded the increased risk of delirium associated with prolonging surgery by 30 minutes (OR 1.20, 95% CI 1.19-1.21). The relative risk associated with statin use was somewhat higher among patients who had noncardiac surgery than among those who had cardiac surgery (adjusted OR 1.33, 95% CI 1.16-1.53), and extended to more complicated cases of delirium. We did not observe an increased risk of delirium with 20 other cardiac or noncardiac medications. INTERPRETATION: The use of statins is associated with an increased risk of postoperative delirium among elderly patients undergoing elective surgery.
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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 | 0.001 | 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".