The effect of preoperative statins on postoperative mortality, renal, and neurological complications in patients undergoing cardiac surgeries: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Cardiac surgery is performed worldwide to treat severe cases of cardiovascular diseases. Statins have shown controversial effects on complications after cardiac surgeries. We aimed to investigate the effect of preoperative statin therapy on the frequency of postoperative mortality, renal, and neurological complications. METHODS: In a retrospective cohort study, the database of patients operated on in two hospitals in southern Iran during 2008-2019 was used to compare preoperative statin use with no use on the composite outcome of mortality, renal, and neurological complications as well as on each component of the composite, separately. Effects of low dose (<40 mg simvastatin equivalence) vs. high dose (≥40 mg) statins were also evaluated. Confounders that could affect the outcomes were considered in the logistic regression model, and multiple imputation techniques were used to categorize patients with unknown statin dose use as either high or low-dose users. RESULTS: Of total 7329 patients, 17.6% of statin users and 17% of non-statin users developed the composite outcome (P=0.51). Statin use had no statistically significant association with the composite outcome (aRR 1.01 [95% CI: 0.88-1.16]). There was no significant association with mortality [aRR: 0.75 (95% CI: 0.34-1.69)], neurological [aRR: 1.25 (95% CI: 0.77-2.12)], or renal complications [aRR: 1.03 (95% CI 0.90-1.19)] after surgery. Neither low nor high doses had any statistically significant effect on the composite or any of its components. CONCLUSIONS: In this large study, preoperative statin use, either high dose or low dose, did not affect short-term postoperative mortality, neurological, or renal complications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".