• Ning Zhou, Jianping Gong, XiuSheng Liang, Weihua Liu, Heng Li, and Weichao Li.
• The Sixth Affiliated Hospital of Guangzhou Medical University: Department of Anesthesiology, Qingyuan people's Hospital, Qingyuan City, Guangdong Province, People's Republic of China.
• J. Cardiothorac. Vasc. Anesth. 2023 Jan 1; 37 (1): 127134127-134.

AbstractReperfusion ventricular fibrillation (VF) is a common arrhythmia after cardiac surgery. Predictors of reperfusion VF and its relationships with the adverse prognosis are still unclear. This study aimed to identify a risk score model to predict reperfusion VF and its effect on in-hospital outcomes. The authors enrolled 1,024 consecutive patients undergoing cardiac surgery, and a total of 823 patients were included in the study. A novel risk score model was developed following logistic regression analysis of the predictors of reperfusion VF. The receiver operating characteristic curve was used to validate this model, and the effect of VF on prognosis was later identified in multivariate or Kaplan-Meier analyses. Risk factors for reperfusion VF occurrence included weight >55 kg, preoperative left ventricular ejection fraction <50%, prior stroke, hypertension, aortic valve replacement, HTK solution, and the use of ≥3 grafts in coronary artery bypass grafting. A novel risk score model was developed using the abovementioned variables, and points were assigned to each risk factor according to its odds ratio. A high score (>6) predicted greater than 65% of patients with VF occurrence. Reperfusion VF increased the risk of in-hospital cardiovascular death (p = 0.03) and renal replacement therapy postoperatively (p = 0.022). More attention should be given to reperfusion VF due to an adverse postoperative prognosis, and the developed risk score model may predict this risk.Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.

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