A nomogram to predict the risk of death during hospitalization in Chinese neonates with respiratory failure
Year: 2024
Type: article
Study design: Observational Study
Abstract: Background: Neonatal respiratory failure (NRF) is a critical condition with high morbidity and mortality rates. This study aimed to develop a nomogram prediction model to early predict the risk of death in Chinese neonates with NRF. Methods: A retrospective analysis was conducted on NRF neonates from 21 tertiary neonatal intensive care units (NICUs) across 13 prefecture-level cities in Jiangsu Province, China, from March 2019 to March 2022. NRF neonates from one random NICU were selected as the external validation set, while those from the remaining 20 NICUs were divided into the training set and the internal validation set at a 7:3 ratio. Death was the primary outcome. LASSO regression and multivariate logistic regression were used to identify the predictive factors from the training set and then the nomogram was constructed. Results: A total of 5387 neonates with NRF were included in the analysis. Among them, 3444 were in the training set, 1470 were in the internal validation set, and 473 were in the external validation set. The nomogram was constructed based on the eight predictors of the 1-min Apgar score, birth weight, gestational age, the relationship between birth weight and gestational age, mode of first respiratory support, inhaled nitric oxide, antenatal corticosteroids, and vasoactive drugs. The area under the curve of the nomogram in the training set, internal validation set, and external validation set was 0.763, 0.733, and 0.891, respectively. The P-values of the Hosmer-Lemeshow goodness of fit test were 0.638, 0.273, and 0.253, respectively. Brier scores were 0.066, 0.072, and 0.037, respectively. The decision curve analysis demonstrated a significant net benefit in all cases. These data indicate the good performance of the nomogram. Conclusions: This nomogram can serve as a reference for clinicians to identify high-risk neonates early and reduce the incidence of neonatal mortality.
Source: Heliyon
Authors: Bo Wang, Yue Wu, Jie Shao, Rui Cheng, Rui Cheng, Zuming Yang, Zuming Yang, Yan Xu, Yan Xu, Bo Wang, Guihua Shu, Hong Li, Huaiyan Wang, Jinlan Cai, Jie Shao, Jinjun Zhou, Li Ye, Mengzhu Yu, Qin Zhou, Rui Cheng, Rui Cheng, Shuping Han, Songlin Liu, Xiaoqing Chen, Xinping Wu, Xiaoping Yin, Yan Gao, Yue Wu, Yan Xu, Yan Xu, Zhidan Bao, Zhenguang Li, Zhaojun Pan, Zuming Yang, Zuming Yang, Zhengying Li
Institutions: Nanjing Medical University, Nanjing Children's Hospital, Second Affiliated Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Suzhou Municipal Hospital, Affiliated Hospital of Xuzhou Medical College, Soochow University, Nantong Maternity and Child Health Hospital, Nanjing Drum Tower Hospital, Affiliated Hospital of Jiangsu University, Maternal and Child Health Hospital of Xuzhou, Jiangsu Province Hospital, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Lianyungang Maternal and Children’s Hospital, Jiangyin People's Hospital, Xuzhou Children Hospital
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,100
Award: G8087607192
OpenAlex ID: W4402292458