ArticleJournal of atrial fibrillation
Quantifying Risk Factors for Atrial Fibrillation: Retrospective Review of a Large Electronic Patient Database.
Article in Journal of atrial fibrillation. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 3 citations in OpenAlex.
- Definition of Polypharmacy in Atrial Fibrillation and Atrial Flutter: A Scoping Review.Cardiology research · 2026Review
- Article
- Review
- Risk of atrial fibrillation in patients with inflammatory bowel disease: A systematic review and meta-analysis.International journal of cardiology. Heart & vasculature · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDespite the numerous comorbidities associated with atrial fibrillation (AF), the relative risk has been varying and not well-documented.
aimTo quantify the risk of diseases associated with AF.
methodsPopulation-based retrospective analysis in IBM Explorys (1999-2019), an electronic database with over 63 million patients in the United States. Odds ratios were calculated between AF and other diseases. AF patients were also stratified by age, gender, and race to assess trends of AF in different demographic groups.
results1,812,620 patients had AF in the database. Congestive heart failure had the highest association with AF (OR 42.95). Cardiomyopathy, coronary artery disease, hypertension, and myocardial infarction all had odds greater than 15. Anemia of chronic disease and chronic kidney disease had odds greater than 18, the highest for chronic inflammatory conditions. Other conditions commonly associated with AF were found to have odds less than 8, including hyperthyroidism, alcohol use, and sleep apnea. Helicobacter pylori infection had the lowest odds at 1.98.
conclusionsEpidemiologic information could be integrated with current clinical algorithms to more rapidly identify patients at risk of AF.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.