Statin Use and the Risk of Surgical Site Infections in Elderly Patients Undergoing Elective Surgery
Bibliographic record
Abstract
OBJECTIVE: To examine whether preoperative statin use is associated with a reduced risk of surgical site infections. DESIGN, SETTING, AND PATIENTS: Population-based retrospective cohort study of all elderly patients undergoing elective surgery in Ontario from April 1, 1992, through March 31, 2006. Preoperative statin use was identified using provincewide pharmacy records. Procedure and patient characteristics were derived from hospital and physician claims databases within Canada's single-payer universal health care system. MAIN OUTCOME MEASURE: The 30-day risk of surgical site infection was derived from the initial admission, outpatient consultations, and hospital readmissions. RESULTS: The cohort included 469,349 distinct elderly patients undergoing elective surgery, of whom 68,387 (14.6%) were statin users. The primary analysis included 53,565 statin users matched to 53,565 statin nonusers undergoing the same procedure in the same hospital by the same surgeon. Unadjusted analysis revealed a slight increase in the risk of surgical site infection among statin users compared with nonusers (8.9% vs 8.7%; P < .001), which disappeared after adjustment for demographics, health care utilization variables, comorbidities, and concurrent medication therapy (odds ratio, 1.00; 95% confidence interval, 0.95-1.04; P = .85). A similar lack of association was seen when matching was extended to include propensity scores (odds ratio, 0.99; 95% confidence interval, 0.94-1.05; P = .82). The lack of association persisted across pharmacologic, patient, and procedure subgroups. CONCLUSIONS: Statin use is not associated with an altered risk of surgical site infection. Prevention efforts should be directed toward other evidence-based strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".