Bisphosphonates and risk of atrial fibrillation: a meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Bisphosphonates are the most commonly used drugs for the prevention and treatment of osteoporosis. Although a recent FDA review of the results of clinical trials reported no clear link between bisphosphonates and serious or non-serious atrial fibrillation (AF), some epidemiologic studies have suggested an association between AF and bisphosphonates. METHODS: We conducted a meta-analysis of non-experimental studies to evaluate the risk of AF associated with bisphosphonates. Studies were identified by searching MEDLINE and EMBASE using a combination of the Medical Subject Headings and keywords. Our search was limited to English language articles. The pooled estimates of odds ratios (OR) as a measure of effect size were calculated using a random effects model. RESULTS: Seven eligible studies with 266,761 patients were identified: three cohort, three case-control, and one self-controlled case series. Bisphosphonate exposure was not associated with an increased risk of AF [pooled multivariate OR 1.04, 95% confidence interval (CI) 0.92-1.16] after adjusting for known risk factors. Moderate heterogeneity was noted (I-squared score = 62.8%). Stratified analyses by study design, cohort versus case-control studies, yielded similar results. Egger's and Begg's tests did not suggest an evidence of publication bias (P = 0.90, 1.00 respectively). No clear asymmetry was observed in the funnel plot analysis. Few studies compared risk between bisphosphonates or by dosing. CONCLUSIONS: Our study did not find an association between bisphosphonate exposure and AF. This finding is consistent with the FDA's statement.
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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 | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.062 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".