Title

Noninvasive biomarker-based risk stratification for development of new onset atrial fibrillation after coronary artery bypass surgery

Aurora Affiliations

Center for Integrative Research on Cardiovascular Aging (CIRCA), Patient Centered Research, Advocate Aurora Research Institute, Aurora St. Luke's Medical Center School of Diagnostic Sonography, Aurora Cardiovascular and Thoracic Services, Center for Advanced Atrial Fibrillation Therapies, Advocate Aurora Health

Abstract

BACKGROUND: Postoperative atrial fibrillation (PoAF) is a common complication after cardiac surgery. A pre-existing atrial substrate appears to be important in postoperative development of dysrhythmia, but its preoperative estimation is challenging. We tested the hypothesis that a combination of clinical predictors, noninvasive surrogate markers for atrial fibrosis defining abnormal left atrial (LA) mechanics, and biomarkers of collagen turnover is superior to clinical predictors alone in identifying patients at-risk for PoAF.

METHODS: In patients without prior AF undergoing coronary artery bypass grafting, concentrations of biomarkers reflecting collagen synthesis and degradation, extracellular matrix, and regulatory microRNA-29s were determined in serum from preoperative blood samples and correlated to atrial fibrosis extent, alteration in atrial deformation properties determined by 3D speckle-tracking echocardiography, and AF development.

RESULTS: Of 90 patients without prior AF, 34 who developed PoAF were older than non-PoAF patients (72.04 ± 10.7 y; P = 0.043) with no significant difference in baseline comorbidities, LA size, or ventricular function. Global (P = 0.007) and regional longitudinal LA strain and ejection fraction (P = 0.01) were reduced in PoAF vs. non-PoAF patients. Preoperative amino-terminal-procollagen-III-peptide (PIIINP) (103.1 ± 39.7 vs. 35.1 ± 19.3; P = 0.041) and carboxy-terminal-procollagen-I-peptide levels were elevated in PoAF vs. non-PoAF patients with a reduction in miR-29 levels and correlated with atrial fibrosis extent. Combining age as the only significant clinical predictor with PIIINP and miR-29a provided a model that identified PoAF patients with higher predictive accuracy.

CONCLUSIONS: In patients without a previous history of AF, using age and biomarkers of collagen synthesis and regulation, a noninvasive tool was developed to identify those at risk for new-onset PoAF.

Document Type

Article

PubMed ID

31952855

DOI

10.1016/j.ijcard.2019.12.067

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