Related Experiment Video
Updated: Nov 12, 2025
A Modified Sonographic Algorithm for Image Acquisition in Life-Threatening Emergencies in the Critically Ill Newborn
Published on: April 7, 2023
A nomogram to predict in-hospital mortality of neonates admitted to the intensive care unit
Xihua Huang1, Zhenyu Liang1, Tang Li1
1Department of Pediatrics, Guangdong Second Provincial General Hospital, No. 466 Middle Xingang Road, Zhuhai District, Guangzhou, Guangdong 510317, P. R. China.
Background:
To explore the influencing factors for in-hospital mortality in the neonatal intensive care unit (NICU) and to establish a predictive nomogram.
Methods:
Neonatal data were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database. Both univariate and multivariate logit binomial general linear models were used to analyse the factors influencing neonatal death. The area under the receiver operating characteristics (ROC) curve was used to assess the predictive model, which was visualized by a nomogram.
Results:
A total of 1258 neonates from the NICU in the MIMIC-III database were eligible for the study, including 1194 surviving patients and 64 deaths. Multivariate analysis showed that red cell distribution width (RDW) (odds ratio [OR] 0.813, p=0.003) and total bilirubin (TBIL; OR 0.644, p<0.001) had protective effects on neonatal in-hospital death, while lymphocytes (OR 1.205, p=0.025), arterial partial pressure of carbon dioxide (PaCO2; OR 1.294, p=0.016) and sequential organ failure assessment (SOFA) score (OR 1.483, p<0.001) were its independent risk factors. Based on this, the area under the curve of this predictive model was up to 0.865 (95% confidence interval 0.813 to 0.917), which was also confirmed by a nomogram.
Conclusions:
The nomogram constructed suggests that RDW, TBIL, lymphocytes, PaCO2 and SOFA score are all significant predictors for in-hospital mortality in the NICU.
