Development and evaluation of a mortality risk prediction model for severe bacterial infections in children
10.3760/cma.j.issn.1671-0282.2023.04.009
- VernacularTitle:儿童重症细菌感染死亡风险预测模型的建立及评价
- Author:
Haoyu ZHA
1
;
Rui TAN
;
Haonan WANG
;
Xuejian MEI
;
Mingxing FAN
;
Meiling PAN
;
Tingting CHEN
;
Jun CHEN
;
Yao LIU
;
Shaodong ZHAO
;
Zhuo LI
;
Hongjun MIAO
Author Information
1. 南京医科大学儿科学院，南京 210005
- Keywords:
Serious bacterial infection;
Model;
Prognosis;
Logistic regression analysis;
Nomorgraphy
- From:
Chinese Journal of Emergency Medicine
2023;32(4):489-496
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To establish a mortality risk prediction model of severe bacterial infection in children and compare it with the pediatric early warning score (PEWS), pediatric critical illness score (PCIS) and pediatric risk of mortality score Ⅲ (PRISM Ⅲ).Methods:A total of 178 critically ill children were selected from the PICU of the Children's Hospital of Nanjing Medical University from May 2017 to June 2022. After obtaining the informed consent of the parents/guardians, basic information such as sex, age, height and weight, as well as indicators such as heart rate, systolic blood pressure and respiratory rate were collected from all children. A standard questionnaire was used to score the child 24 h after admission to the PICU. The children were divided into the survival and death groups according to their survival status at 28 d after admission. A mortality risk prediction model was constructed and nomogram was drawn. The value of the mortality risk prediction model, PEWS, PCIS and PRISM in predicting the risk of death was assessed and compared using the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC).Results:Among the 178 critically ill children, 11 cases were excluded due to severe data deficiencies and hospitalization not exceeding 24 h. A total of 167 children were included in the analysis, including 134 in the survival group and 33 in the death group. A mortality risk prediction model for children with severe bacterial infection was constructed using pupillary changes, state of consciousness, skin color, mechanical ventilation, total cholesterol and prothrombin time. ROC curve analysis showed that the AUCs of mortality risk prediction model was 0.888 ( P<0.05). The AUCs of PEWS, PCIS and PRISM Ⅲ in predicting death in children with severe bacterial infection were 0.769 ( P< 0.05), 0.575 ( P< 0.05) and 0.759 ( P< 0.05), respectively. Hosmer-Lemeshow goodness-of-fit test showed the best agreement between risk of death and PEWS predicted morbidity and mortality and actual morbidity and mortality (χ 2 = 5.180, P = 0.738; χ 2 = 4.939, P = 0.764), and the PCIS and PRISM Ⅲ predicted mortality rates fitted reasonably well with actual mortality rates (χ 2= 9.110, P= 0333; χ 2 = 8.943, P= 0.347). Conclusions:The mortality risk prediction model for predicting the death risk has better prognostic value than PEWS, PCIS and PRISM Ⅲ for children with severe bacterial infection.
