• Carmelo Dominici, Antonio Salsano, Antonio Nenna, Cristiano Spadaccio, Raffaele Barbato, Giovanni Mariscalco, Francesco Santini, Fausto Biancari, and Massimo Chello.
• Department of Cardiovascular Surgery, Università Campus Bio-Medico di Roma, Rome, Italy. Electronic address: c.dominici@unicampus.it.
• J. Cardiothorac. Vasc. Anesth. 2020 Nov 1; 34 (11): 2951-2961.

ObjectiveMany papers evaluated predictive factors for prolonged intensive care unit (ICU) stay after cardiac surgery, but efforts in translating those models in practical clinical tools is lacking. The aim of this study was to build a new nomogram score and test its calibration and discrimination power for predicting a long length of stay in the ICU among patients undergoing coronary artery bypass graft surgery (CABG).DesignRetrospective analysis of an international registry.SettingMulticentric.ParticipantsBased on the european multicenter study on coronary artery bypass grafting (E-CABG) registry (NCT02319083), a total of 7,352 consecutive patients who underwent isolated CABG were analyzed.InterventionsA "long length of stay" in the ICU was considered when equal to or more than 3 days. Predictive factors were analyzed through a multivariate logistic regression model that was used for the nomogram.ResultsLong length of ICU stay was observed in 2,665 patients (36.2%). Ten independent variables were included in the final regression model: the SYNTAX score class critical preoperative state, left ventricular ejection fraction class, angina at rest, poor mobility, recent potent antiplatelet use, estimated glomerular filtration rate class, body mass index, sex, and age. Based on this 10-risk factors logistic regression model, a nomogram has been designed.ConclusionThe authors defined a nomogram model that can provide an individual prediction of long length of ICU stay in cardiovascular surgical patients undergoing CABG. This type of model would allow an early recognition of high-risk patients who might receive different preoperative and postoperative treatments to improve outcomes.Copyright © 2020 Elsevier Inc. All rights reserved.

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