A Nomogram for Predicting Long Length of Stay in The Intensive Care Unit in Patients Undergoing CABG: Results From the Multicenter E-CABG Registry
| Autor: | Giovanni Mariscalco, Carmelo Dominici, Cristiano Spadaccio, Fausto Biancari, Raffaele Barbato, Francesco Santini, Antonio Salsano, Massimo Chello, Antonio Nenna |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
medicine.medical_specialty
cardiac surgery coronary artery bypass graft intensive care unit length of stay nomogram Renal function 030204 cardiovascular system & hematology Logistic regression Ventricular Function Left law.invention Angina 03 medical and health sciences 0302 clinical medicine Risk Factors 030202 anesthesiology law Humans Medicine Registries Coronary Artery Bypass Retrospective Studies Ejection fraction business.industry Stroke Volume Nomogram medicine.disease Intensive care unit Cardiac surgery Intensive Care Units Nomograms Anesthesiology and Pain Medicine Emergency medicine Cardiology and Cardiovascular Medicine business Body mass index |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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