Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2025
[Predictors of sepsis-induced coagulopathy in children and development of a prediction model].
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Maihemuti Mayire, Simijiang Yipaguli
Аннотация
OBJECTIVES: To identify predictors of sepsis-induced coagulopathy (SIC) in children and to establish a prediction model.
METHODS: Clinical data were retrospectively collected from children with sepsis treated in the pediatric intensive care unit of Xinjiang Hospital of Beijing Children's Hospital between July 2021 and December 2023. Patients were classified into the SIC group (n=64) and the non-SIC group (n=61) according to whether SIC occurred. Multivariable logistic regression was employed to identify independent predictors of SIC. A prediction model was developed based on these factors. The predictive performance and clinical utility of the model were evaluated using the area under the receiver operating characteristic curve, calibration curve, and decision curve analysis.
RESULTS: The multivariable logistic regression analysis showed that procalcitonin, Pediatric Sequential Organ Failure Assessment (pSOFA) score, and mean platelet volume were independent predictors of SIC in children with sepsis (P<0.05). The model developed from these three predictors yielded an area under the curve of 0.903 (95%CI: 0.852-0.953; P<0.001), with sensitivity and specificity of 0.922 and 0.738, respectively. The calibration curve analysis indicated good agreement between predicted and observed outcomes. The decision curve analysis showed favorable clinical benefit of the prediction model.
CONCLUSIONS: Procalcitonin, pSOFA score, and mean platelet volume are predictors of SIC among children with sepsis; the prediction model based on these three predictors shows high performance and has good clinical applicability.
METHODS: Clinical data were retrospectively collected from children with sepsis treated in the pediatric intensive care unit of Xinjiang Hospital of Beijing Children's Hospital between July 2021 and December 2023. Patients were classified into the SIC group (n=64) and the non-SIC group (n=61) according to whether SIC occurred. Multivariable logistic regression was employed to identify independent predictors of SIC. A prediction model was developed based on these factors. The predictive performance and clinical utility of the model were evaluated using the area under the receiver operating characteristic curve, calibration curve, and decision curve analysis.
RESULTS: The multivariable logistic regression analysis showed that procalcitonin, Pediatric Sequential Organ Failure Assessment (pSOFA) score, and mean platelet volume were independent predictors of SIC in children with sepsis (P<0.05). The model developed from these three predictors yielded an area under the curve of 0.903 (95%CI: 0.852-0.953; P<0.001), with sensitivity and specificity of 0.922 and 0.738, respectively. The calibration curve analysis indicated good agreement between predicted and observed outcomes. The decision curve analysis showed favorable clinical benefit of the prediction model.
CONCLUSIONS: Procalcitonin, pSOFA score, and mean platelet volume are predictors of SIC among children with sepsis; the prediction model based on these three predictors shows high performance and has good clinical applicability.