Statins Reduce Abdominal Aortic Aneurysm Growth, Rupture, and Perioperative Mortality: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
Background There are no recognized pharmacological treatments for abdominal aortic aneurysms ( AAA ), although statins are suggested to be beneficial. We sought to summarize the literature regarding the effects of statins on human AAA growth, rupture, and 30‐day mortality. Methods and Results We conducted a systematic review and meta‐analysis of randomized and observational studies using the Cochrane CENTRAL database, MEDLINE , and EMBASE up to June 15, 2018. Review, abstraction, and quality assessment were conducted by 2 independent reviewers, and a third author resolved discrepancies. Pooled mean differences and odds ratios with 95% confidence intervals were calculated using random effects models. Heterogeneity was quantified using the I 2 statistic, and publication bias was assessed using funnel plots. Our search yielded 911 articles. One case‐control and 21 cohort studies involving 80 428 patients were included. The risk of bias was low to moderate. Statin use was associated with a mean AAA growth rate reduction of 0.82 mm/y (95% confidence interval 0.33, 1.32, P =0.001, I 2 =86%). Statins were also associated with a lower rupture risk (odds ratio 0.63, 95% confidence interval 0.51, 0.78, P <0.0001, I 2 =27%), and preoperative statin use was associated with a lower 30‐day mortality following elective AAA repair (odds ratio 0.55, 95% confidence interval 0.36, 0.83, P =0.005, I 2 =57%). Conclusions Statin therapy may be associated with reduction in AAA progression, rupture, and lower rates of perioperative mortality following elective AAA repair. These data argue for widespread statin use in AAA patients. Clinical Trial Registration URL : www.crd.york.ac.uk . Unique identifier: CRD 42017056480.
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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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.032 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".