Efficacy of statins for primary prevention in people at low cardiovascular risk: a meta-analysis
Bibliographic record
Abstract
BACKGROUND: Statins were initially used to improve cardiovascular outcomes in people with established coronary artery disease, but recently their use has become more common in people at low cardiovascular risk. We did a systematic review of randomized trials to assess the efficacy and harms of statins in these individuals. METHODS: We searched MEDLINE and EMBASE (to Jan. 28, 2011), registries of health technology assessments and clinical trials, and reference lists of relevant reviews. We included trials that randomly assigned participants at low cardiovascular risk to receive a statin versus a placebo or no statin. We defined low risk as an observed 10-year risk of less than 20% for cardiovascular-related death or nonfatal myocardial infarction, but we explored other definitions in sensitivity analyses. RESULTS: We identified 29 eligible trials involving a total of 80,711 participants. All-cause mortality was significantly lower among patients receiving a statin than among controls (relative risk [RR] 0.90, 95% confidence interval [CI] 0.84-0.97) for trials with a 10-year risk of cardiovascular disease < 20% [primary analysis] and 0.83, 95% CI 0.73-0.94, for trials with 10-year risk < 10% [sensitivity analysis]). Patients in the statin group were also significantly less likely than controls to have nonfatal myocardial infarction (RR 0.64, 95% CI 0.49-0.84) and nonfatal stroke (RR 0.81, 95% CI 0.68-0.96). Neither metaregression nor stratified analyses suggested statistically significant differences in efficacy between high-and low-potency statins, or larger reductions in cholesterol. INTERPRETATION: Statins were found to be efficacious in preventing death and cardiovascular morbidity in people at low cardiovascular risk. Reductions in relative risk were similar to those seen in patients with a history of coronary artery disease.
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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 | 0.016 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.056 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".