Risk factors for pediatric sepsis-induced coagulopathy and construction of nomogram model
10.3760/cma.j.issn.1673-4912.2025.05.007
- VernacularTitle:儿童脓毒症诱导凝血功能障碍的危险因素分析及列线图模型构建
- Author:
Zhenying WANG
1
;
Yuanyuan ZHANG
1
;
Xifeng ZHANG
1
;
Xiuqing ZHANG
1
;
Guixia XU
1
Author Information
1. 山东第一医科大学附属聊城市第二人民医院儿科，临清 252600
- Publication Type:Journal Article
- Keywords:
Children;
Sepsis-induced coagulopathy;
Risk factors;
Nomogram model
- From:
Chinese Pediatric Emergency Medicine
2025;32(5):352-357
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the risk factors of pediatric sepsis-induced coagulopathy（pSIC），and to construct a nomogram prediction model for early prediction of pSIC.Methods:Using a cross-sectional retrospective cohort design，children with sepsis who were hospitalized in PICU of the Second People's Hospital of Liaocheng Subsidiary to Shandong First Medical University from January 2017 to December 2023 were selected as the study objects，and the diagnosis of sepsis met the diagnostic criteria for childhood sepsis of the 2015 edition.According to the diagnostic criteria of pSIC，the children with sepsis were divided into common sepsis group and pSIC group.The clinical data of both groups were compared，such as general condition，inflammatory indicators，coagulation indicators，sequential organ failure assessment（pSOFA），pSIC score，PICU duration，etc.The risk factors of pSIC were initially screened by Lasso regression analysis，and the independent risk factors were screened by multivariate Logistic regression analysis.R software was used to construct the risk prediction nomogram and evaluate the model.Results:A total of 150 children with sepsis were included in the study，including 121 in the common sepsis group and 29 in the pSIC group.Lasso regression and multivariate Logistic regression analysis showed that pSOFA，prothrombin time（PT），alanine aminotransferase（ALT），blood urea nitrogen（BUN），mean platelet volume/platelet（MPV/PLT）and pediatric critical illness score(PCIS) were independent risk factors for pSIC（all P<0.05）.Since the sources of the pSIC score overlaped with those of pSOFA and PT, only four indicators including ALT，BUN，MPV/PLT and PCIS were used to construct a nomogram model for predicting pSIC.The consistency index of the nomogram model was 0.98，and the area under the receiver operating characteristic curve was 0.975（95% CI 0.952-0.999）.The calibration curve was shown as a straight line with slope close to 1，indicating that the nomogram model had good accuracy in predicting pSIC.The clinical decision curve indicated that the nomogram model had good clinical applicability. Conclusion:pSOFA，PT，ALT，BUN，MPV/PLT and PCIS were all independent risk factors for pSIC.The risk prediction nomogram model of pSIC based on ALT，BUN，MPV/PLT and PCIS can predict the occurrence of pSIC，and provide reference for early clinical recognition and intervention.
