Risk Score for Prediction of 10-Year Atrial Fibrillation: A Community-Based Study

Abstract

We provide a simple score for the prediction of 10-year risk for AF. The score can be used to select patients at highest risk for treatments of modifiable risk factors, monitoring for sub-clinical AF detection or for clinical trials of primary prevention of AF.

A general presentation on how to carry out aCHARMSanalysis for prognostic multivariate models

“…After consolidating all the publications, a total of 3466 records were obtained (Figure 1). After eliminating duplicates, the figure fell to 3132 and of these, 3114 were excluded, since neither the title nor the abstract indicated that the publication described a predictive model of the characteristics proposed, leaving 18 articles to be analyzed in full text 16‐33 . Analysis of these articles resulted in 12 more publications being excluded, 16‐27 five because they were congress abstracts, 16‐20 two because they were revisions, 21,22 two because the authors analyzed the predictive value of risk factors, 23,24 two because the models were not performed in the general population, 25,26 and one because the authors did not use their own data 27 .…”

“…Analysis of these articles resulted in 12 more publications being excluded, 16‐27 five because they were congress abstracts, 16‐20 two because they were revisions, 21,22 two because the authors analyzed the predictive value of risk factors, 23,24 two because the models were not performed in the general population, 25,26 and one because the authors did not use their own data 27 . Accordingly, six scientific articles that followed the 11 CHARMS domains were finally analyzed 28‐33 . The following acronyms are used to facilitate the nomenclature of the three older articles: ARIC (atherosclerosis risk in communities), 32 CHARGE‐AF (cohorts for heart and aging research in genomic epidemiology‐atrial fibrillation), 31 and FHS (Framingham heart study) 33 …”

“…First, we will describe the main results of the included studies and then the 11 items of the CHARMS checklist at the group level, with all the individual information shown in Tables 2 and 3 and expanded in the Supplementary Material 28‐33 …”

“…Of the six models finally included, three have an acronym (ARIC, CHARGE‐AF, and FHS) and three do not. These latter three will be referred to either by the country of origin of the data or by the first author: Aronson (Israel), 28 Ding (China), 29 and Kokubo (Japan) 30 …”

Can atrial fibrillation be caused or triggered by air pollution? An epidemiological perspective

“…6 Several recognized risk factors for atrial fibrillation were previously identified, including advanced age, male sex, hypertension, diabetes mellitus, coronary artery disease, heart failure, sleep apnea, sedentary lifestyle, smoking and obesity. 6,7 Recent risk scores predicting atrial fibrillation development have been proposed, 8,9 showing moderate discriminatory power (C-statistic 0.75). Notably, these risk scores were based entirely on clinical data, to the exclusion of social and environmental determinants.…”