A Nomogram for Predicting Long Length of Stay in The Intensive Care Unit in Patients Undergoing CABG: Results From the Multicenter E-CABG Registry

医学 列线图 重症监护室 逻辑回归 射血分数 推导 重症监护 心脏病学 心绞痛 比例危险模型 内科学 外科 急诊医学 动脉 心肌梗塞 重症监护医学 心力衰竭
作者
Carmelo Dominici,Antonio Salsano,Antonio Nenna,Cristiano Spadaccio,Raffaele Barbato,Giovanni Mariscalco,Francesco Santini,Fausto Biancari,Massimo Chello
出处
期刊:Journal of Cardiothoracic and Vascular Anesthesia [Elsevier]
卷期号:34 (11): 2951-2961 被引量:6
标识
DOI:10.1053/j.jvca.2020.06.015
摘要

Objective Many 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). Design Retrospective analysis of an international registry. Setting Multicentric. Participants Based on the european multicenter study on coronary artery bypass grafting (E-CABG) registry (NCT 02319083), a total of 7,352 consecutive patients who underwent isolated CABG were analyzed. Interventions A “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. Results Long 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. Conclusion The 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. Many 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). Retrospective analysis of an international registry. Multicentric. Based on the european multicenter study on coronary artery bypass grafting (E-CABG) registry (NCT 02319083), a total of 7,352 consecutive patients who underwent isolated CABG were analyzed. A “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. Long 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. The 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.
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