Abstract

New-onset atrial fibrillation during critical illness is an independent risk factor for mortality. The ability to identify patients at high risk for new-onset atrial fibrillation is limited. We hypothesized that genetic susceptibility contributes to risk of new-onset atrial fibrillation in the ICU. Retrospective sub-study of a prospective observational cohort study. Medical and general surgical ICUs in a tertiary academic medical center. One-thousand three-hundred sixty-nine critically ill patients admitted to the ICU for at least 2 days with no known history of atrial fibrillation who had DNA available for genotyping. None. We genotyped 21 single-nucleotide polymorphisms associated with atrial fibrillation in ambulatory studies using a Sequenom platform (San Diego, CA). We collected demographics, medical history, and development of new-onset atrial fibrillation during the first four days of ICU admission. New-onset atrial fibrillation occurred in 98 patients (7.2%) and was associated with age, male sex, coronary artery disease, and vasopressor use. Single-nucleotide polymorphisms associated with new-onset atrial fibrillation were rs3853445 (near PITX2, p = 0.0002), rs6838973 (near PITX2, p = 0.01), and rs12415501 (in NEURL, p = 0.03) on univariate testing. When controlling for clinical factors, rs3853445 (odds ratio, 0.47; 95% CI, 0.30-0.73; p = 0.001) and rs12415501 (odds ratio, 1.72; 95% CI, 1.27-2.59; p = 0.01) remained significantly associated with new-onset atrial fibrillation. The addition of genetic variables to clinical factors improved new-onset atrial fibrillation discrimination in a multivariable logistic regression model (C-statistic 0.82 vs 0.78; p = 0.0009). We identified several single-nucleotide polymorphisms associated with new-onset atrial fibrillation in a large cohort of critically ill ICU patients, suggesting there is genetic susceptibility underlying this common clinical condition. This finding may provide new targets for future mechanistic studies and additional insight into the application of genomic information to identify patients at elevated risk for a common and important condition in the ICU.

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