Does the GENSINI score predict postoperative atrial fibrillation in patients undergoing on-pump CABG surgery?
113 patients undergoing on-pump coronary artery bypass grafting (CABG) surgery
GENSINI score (angiographic atherosclerosis quantification)
Postoperative atrial fibrillation (POAF)hard clinical
The GENSINI score, a measure of angiographic atherosclerosis, independently predicts the development of postoperative atrial fibrillation following on-pump CABG.
Aim: Postoperative atrial fibrillation (POAF) is common after coronary artery by-pass grafting surgery (CABG) and associated with adverse events. GENSINI score is a widely-used scoring system that quantifies angiographic atherosclerosis. The value of GENSINI score to predict POAF has not been studied previously. Aim of this study was to evaluate this relationship in our patients undergoing on-pump CABG surgery.Material and Methods: In this retrospective, single-center study, a total of 113 patients without exclusion criteria were included. Demographic and clinical characteristics of patients were recorded and GENSINI scores were calculated. Univariate and multivariate logistic regression analyses were performed to identify the independent predictors of POAF.Results: Postoperative atrial fibrillation developed in 34 (30%) patients. Multivariate logistic regression analyses revealed that C-Reactive Protein ß=0.037, p=0.011, OR=1.03, 95% CI (1.008-1.065) and GENSINI score ß=0.015, p=0.024,OR=1.012, 95% CI (1.002-1.028) are independent predictors of POAF. The ROC analysis showed an area under the curve of 0.587 (p=0.012). GENSINI score of 50.75 had 82.4% sensitivity in predicting POAF p=0.012, 95%CI (0.464-0.711). Conclusion: Our results showed that GENSINI score is an independent predictor of POAF in patients undergoing on-pump CABG surgery.
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Emir Karaçağlar
University of Leeds
Arzu Neslihan Akgün
Ministry of Health
Orçun Çiftci
Başkent University
Turkish Journal of Clinics and Laboratory
Başkent University
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Karaçağlar et al. (Tue,) studied this question.
synapsesocial.com/papers/69d56f7a75589c71d767d90f — DOI: https://doi.org/10.18663/tjcl.547919
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