A novel nomogram for predicting 3-year mortality in critically ill patients after coronary artery bypass grafting.

BMC Surg

Department of Geriatric Cardiology, The First Affiliated Hospital of China Medical University, NO.155 Nanjing North Street, Heping Ward, Shenyang, 110001, China.

Published: November 2021

Background: The long-term outcomes for patients after coronary artery bypass grafting (CABG) have been received more and more concern. The existing prediction models are mostly focused on in-hospital operative mortality after CABG, but there is still little research on long-term mortality prediction model for patients after CABG.

Objective: To develop and validate a novel nomogram for predicting 3-year mortality in critically ill patients after CABG.

Methods: Data for developing novel predictive model were extracted from Medical Information Mart for Intensive cart III (MIMIC-III), of which 2929 critically ill patients who underwent CABG at the first admission were enrolled.

Results: A novel prognostic nomogram for 3-year mortality was constructed with the seven independent prognostic factors, including age, congestive heart failure, white blood cell, creatinine, SpO, anion gap, and continuous renal replacement treatment derived from the multivariable logistic regression. The nomogram indicated accurate discrimination in primary (AUC: 0.81) and validation cohort (AUC: 0.802), which were better than traditional severity scores. And good consistency between the predictive and observed outcome was showed by the calibration curve for 3-year mortality. The decision curve analysis also showed higher clinical net benefit than traditional severity scores.

Conclusion: The novel nomogram had well performance to predict 3-year mortality in critically ill patients after CABG. The prediction model provided valuable information for treatment strategy and postdischarge management, which may be helpful in improving the long-term prognosis in critically ill patients after CABG.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8638264PMC
http://dx.doi.org/10.1186/s12893-021-01408-8DOI Listing

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