Association between Preoperative Statin Therapy and Postoperative Infectious Complications in Patients Undergoing Cardiac Surgery: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Infectious complications of cardiac surgery are often severe and life threatening. Statins having both immunomodulatory and anti-inflammatory effects were intuitively thought to influence the development of postsurgical infections. We sought to systematically examine whether any association exists between statin use and risk of infectious complications in patients undergoing cardiac surgery. We searched Ovid MEDLINE, Ovid EMBASE, Thomson Scientific Web of Science, and Elsevier Scopus from inception through February 2011 for comparative studies examining the association between statin use and risk of postoperative infections in patients undergoing cardiac surgery. We contacted a study's author for missing information. We conducted a random-effects meta-analysis of individual studies' odds ratios (adjusted for potential confounders). We identified 6 cohort studies for inclusion, 3 of which were conducted in Canada and 3 of which were conducted in the United States. Four were single-center studies, and 2 were population based. Exposure ascertainment was based on a review of admission medication list or prescription databases. Infectious outcomes were heterogeneous and included surgical site infections within 30 days, serious infections (sepsis), or any other postoperative infection. Statin use in the preoperative period was associated with a trend toward reduction in the incidence of postoperative infections in patients who underwent cardiac surgery (odds ratio, 0.81 [95% confidence interval, 0.64-1.01]; [Formula: see text]; [Formula: see text]). Heterogeneity was explained by country effect. Studies performed in Canada showed weaker associations than studies performed in the United States. This difference could not be attributed to study quality alone. We did not find good evidence to support an association between statin use and postoperative infectious complications. However, the trend toward statistical significance for this association indicates that further investigation is warranted.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.016 | 0.002 |
| 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 | 0.000 |
| 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".