Atrial fibrillation and risk of cardiovascular events and mortality in patients with symptomatic peripheral artery disease: A meta‐analysis of prospective studies
Bibliographic record
Abstract
Background Atrial fibrillation (AF) is associated with adverse outcomes in terms of survival and morbidity. Peripheral artery disease (PAD) and AF share several common risk factors and often coexist. Whether AF has a prognostic role in patients with PAD has not been extensively studied. Hypothesis AF is associated with major adverse cardiac events (MACE) and mortality in symptomatic PAD patients. Methods Using MEDLINE and Scopus, we searched for studies published before December 2016 that evaluated cardiovascular outcomes based on the presence/absence of AF in a prospective manner with a follow‐up period of ≥12 months. The outcomes were reported using a random‐effects model, and heterogeneity was assessed using the I 2 statistic. Sensitivity analyses were performed to test the contribution of each study to the overall results. Results Six prospective studies (Newcastle‐Ottawa score range, 7–9) with 14 656 patients were included in the final analysis (age range, 66–70 years; median follow‐up, 1.4 years). Our pooled analysis found a significant association between AF and mortality (odds ratio: 2.52, 95% confidence interval: 1.91‐3.34, I 2 = 32.6%), without evidence of publication bias ( P = 0.63). Meta‐analysis showed a significant impact of AF on MACE (odds ratio: 2.54, 95% confidence interval: 1.78‐3.63, I 2 = 74.3%), without detected publication bias ( P = 0.08). Conclusions AF is associated with increased risk of mortality and MACE in symptomatic PAD.
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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 | 0.019 | 0.033 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.065 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 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".