Development of a risk score for atrial fibrillation (Framingham Heart Study): a community-based cohort study.

By R. Schnabel, Lisa Sullivan, Daniel Levy, Michael J. Pencina, J. Massaro, Ralph B. D’Agostino, C. Newton‐Cheh, J. Yamamoto, Jared W. Magnani, T. Tadros and 6 more. The Lancet, 2009

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2012 HRS/EHRA/ECAS expert consensus statement on catheter and surgical ablation of atrial fibrillation: recommendations for patient selection, procedural techniques, patient management and follow-up, definitions, endpoints, and research trial design (2012, background): “Diabetes mellitus and hyperthyroidism are well-recognized and independent risk factors for AF; even when well controlled, AF may recur [141, 153].”
Atrial fibrillation: profile and burden of an evolving epidemic in the 21st century. (2013, background): “…(95% CI 1.9 to 2.6) in women (Benjamin et al., 1994) Benjamin et al. (1994), Stewart et al. (2001), Tsang et al. (2003), Tsang et al. (2005) and Schnabel et al. (2009) Male gender: likelihood of AF increases if male - Men at 1.5 times greater risk (95% CI 1.3 to 1.8) of AF (although absolute…”
AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning (2018, methodology): “We compared the performance of A UTO P ROGNOSIS with the clinical risk scores used for predicting prognosis in each cohort (MAGGIC score in MAGGIC and UNOS-I (Wong et al., 2014), Framingham score in the UK Biobank (Schnabel et al., 2009), and IMPACT score in UNOS-II (Weiss et al., 2011)).”
Simple Risk Model Predicts Incidence of Atrial Fibrillation in a Racially and Geographically Diverse Population: the CHARGE‐AF Consortium (2013, neutral): “Age, y 60 (8) 73 (5) 73 (5) 63 (6) 62 (6) 76 (6) 72 (7)”