An mNUTRIC-based nomogram for predicting the in-hospital death risk in patients with acute stroke

Abstract

Objectives: To establish a risk prediction model for in-hospital death in acute stroke patients based on nutritional risk scores.

Methods: A retrospective analysis was performed including 268 acute stroke patients. The Nutritional Risk Screening 2002 (NRS2002) and modified Nutritional Risk in the Critically Ill (mNUTRIC) score were used to evaluate the nutritional status of patients with acute stroke after admission to the neurological intensive care unit (NICU), and laboratory parameters and clinical characteristics were collected. Multivariate logistic regression analysis was performed to screen the risk factors for in-hospital death in acute stroke patients, and a nomogram for predicting death based on the nutritional risk score was established.

Results: The mortality of acute stroke in the NICU was 25.8%. Multivariate logistic regression analysis showed that the mNUTRIC score, female sex, lymphocyte count, pulmonary infection and mechanical ventilation were independent risk factors for in-hospital mortality in acute stroke patients (P < 0.001 or 0.05). The above indexes were used to establish a prediction model of the in-hospital death risk for acute stroke patients. The area under the ROC curve, sensitivity, and specificity of the prediction model were 0.891 (95% CI = 0.853-0.928), 82.5%, and 81.7%, respectively. The nomogram was established and then internally validated using bootstrap repeat sampling 2000 times, the C-index was 0.880, and the predicted values of the calibration curve were in agreement with the measured values.

Conclusion: The mNUTRIC-based nomogram model can be used as a reliable tool to predict the in-hospital mortality risk of acute stroke patients.