Development and validation of a nomogram to predict the risk of death within 1 year in patients with non-ischemic dilated cardiomyopathy: a retrospective cohort study

Abstract

Predicting the chances mortality within 1 year in non-ischemic dilated cardiomyopathy patients can be very useful in clinical decision-making. This study has developed and validated a risk-prediction model for identifying factors contributing to mortality within 1 year in such patients. The predictive nomogram was constructed using a retrospective cohort study, with 615 of patients hospitalized in the First Affiliated Hospital of Guangxi Medical University between October 2012 and May 2020. A variety of factors, including presence of comorbidities, demographics, results of laboratory tests, echocardiography data, medication strategies, and instances of heart transplant or death were collected from electronic medical records and follow-up telephonic consultations. The least absolute shrinkage and selection operator and logistic regression analyses were used to identify the critical clinical factors for constructing the nomogram. Calibration, discrimination, and clinical usefulness of the predictive model were assessed using the calibration plot, C-index and decision curve analysis. Internal validation was assessed with bootstrapping validation. Among the patients from whom follow-up data were obtained, the incidence of an end event (deaths or heart transplantation within 1 year) was 171 cases per 1000 person-years (105 out of 615). The main predictors included in the nomogram were pulse pressure, red blood cell count, left ventricular end-diastolic dimension, levels of N-terminal pro b-type natriuretic peptide, medical history, in-hospital worsening heart failure, and use of angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers. The model showed excellent discrimination with a C-index of 0.839 (95% CI 0.799–0.879), and the calibration curve demonstrated good agreement. The C-index of internal validation was 0.826, which demonstrated that the model was quite efficacious. A decision curve analysis confirmed that our nomogram was clinically useful. In this study, we have developed a nomogram that can predict the risk of death within 1 year in patients with non-ischemic dilated cardiomyopathy. This will be useful in the early identification of patients in the terminal stages for better individualized clinical decisions.