Construction and validation of a prognostic prediction model for pediatric sepsis based on the Phoenix sepsis score.
10.3760/cma.j.cn121430-20241008-00816
- Author:
Yongtian LUO
1
;
Hui SUN
1
;
Zhigui JIANG
2
;
Zhen YANG
1
;
Chengxi LU
1
;
Lufei RAO
1
;
Tingting PAN
1
;
Yuxin RAO
1
;
Xiao LI
1
;
Honglan YANG
3
,
4
Author Information
1. Pediatric Intensive Care Unit, Affiliated Hospital of Guizhou Medical University, Guiyang 550000, China.
2. Department of Pediatrics, Xishui County People's Hospital, Zunyi 564600, China.
3. Department of Pediatric Hematology and Oncology, Affiliated Hospital of Guizhou Medical University, Guiyang 550000, China. Corresponding author: Yang Honglan, Email: yhonglan2021@
4. com.
- Publication Type:Journal Article
- MeSH:
Humans;
Sepsis/diagnosis*;
Prognosis;
Retrospective Studies;
Logistic Models;
Intensive Care Units, Pediatric;
Nomograms;
Child;
ROC Curve;
Risk Factors;
Male;
Female;
Child, Preschool;
Infant
- From:
Chinese Critical Care Medicine
2025;37(9):856-860
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE:To construct and validate a prognostic prediction model for children with sepsis using the Phoenix sepsis score (PSS).
METHODS:A retrospective case series study was conducted to collect clinical data of children with sepsis admitted to the pediatric intensive care unit (PICU) of the Affiliated Hospital of Guizhou Medical University from January 2022 to April 2024. The data included general information, the worst values of laboratory indicators within the first 24 hours of PICU admission, PSS score, pediatric critical illness score (PCIS), and the survival status of the children within 30 days of admission. The statistically significant indicators in univariate Logistic regression analysis were included in multivariate Logistic regression analysis to screen the risk factors affecting the prognosis of children with sepsis and construct a nomogram model. The receiver operator characteristic curve (ROC curve) was drawn to evaluate the predictive performance of the model. The Bootstrap method was used to perform 1 000 repeated sampling internal verification and draw the calibration curve of the model.
RESULTS:A total of 199 children with sepsis were included, of which 32 died and 167 survived 30 days after admission. In the univariate Logistic regression analysis, shock, white blood cell count (WBC), international normalized ratio (INR), lactic acid (Lac), PSS score, and PCIS score were identified as statistically significant predictors. These variables were then included in the multivariate Logistic regression analysis, which demonstrated that shock [odds ratio (OR) = 4.258, 95% confidence interval (95%CI) was 1.049-17.288], WBC (OR = 1.124, 95%CI was 1.052-1.210), and PSS score (OR = 1.977, 95%CI was 1.298-3.012) were independent risk factors for mortality in pediatric patients with sepsis (all P < 0.05). A nomogram model was constructed based on these three risk factors, with the model equation as follows: -4.809+1.449×shock+0.682×PSS score+0.117×WBC. The calibration curve results showed that the model's predictions were highly consistent with the actual observations. The ROC curve showed that when the Youden index of the prediction model was 0.792, the sensitivity and specificity were 90.6% and 88.6%, respectively, and the area under the curve (AUC) was 0.957 (95%CI was 0.930-0.984), which was higher than the AUC of shock, WBC, and PSS score alone (0.808, 0.667, 0.908, respectively).
CONCLUSIONS:Shock, WBC, and PSS score have demonstrated certain predictive value for mortality in children with sepsis. The nomogram model based on the above indicators has important clinical significance for evaluating the prognosis and guiding treatment of children with sepsis.
