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Objective <p>This study aimed to develop a nomogram for assessing the risk of in-hospital mortality in children with suspected sepsis admitted to pediatric intensive care unit (PICU). Additionally, it sought to evaluate the applicability of the most recent international diagnostic criteria for pediatric sepsis, the Phoenix diagnostic criteria.</p> Methods <p>Data were collected from electronic medical records of pediatric sepsis patients admitted to the PICU at West China Second Hospital, Sichuan University, between January 1, 2021, and August 31, 2023, within the first 24&#xa0;h of admission. A total of 539 children were randomly assigned to two groups: a training set (<i>n</i> = 458, 85%) and a validation set (<i>n</i> = 80, 15%). The LASSO regression was employed for variable selection. Multivariable logistic regression analysis was used to construct a predictive model incorporating the predictors selected through LASSO regression. A nomogram was constructed based on the selected variables for visual representation. Model validation was performed using a calibration plot, ROC curve, and DCA. The AUC of this model were compared with those of the SIRS, PELODS-2, pSOFA, PMODS, and Phoenix criteria. Subsequently, the pSOFA, SIRS, and Phoenix criteria were applied to data collected within the first 24&#xa0;h of PICU admission to compare mortality rates based on these criteria in patients with suspected sepsis.</p> Results <p>Among the 42 variables examined, LASSO regression analysis identified six significant predictors: urea, P/F ratio, mechanical ventilation, HCO<sub>3</sub><sup>−</sup> levels, vasoactive medications, and neurological. The model, incorporating these six predictors, demonstrated excellent predictive performance, with an AUC of 0.983 in the training set and 0.979 in the validation set. And it was confirmed by the DCA that the model has some clinical utility in terms of the risk of in-hospital mortality. ROC-AUC values and 95% CI of Phoenix, pSOFA, PMODS, SIRS and PELODS-2 scoring systems are 0.958 (0.941–0.976), 0.941 (0.916–0.966), 0.839 (0.787–0.891), 0.662 (0.597–0.726) and 0.918 (0.878–0.958), respectively.</p> Conclusion <p>(1) The inclusion of P/F ratio, mechanical ventilation, HCO<sub>3</sub><sup>−</sup> levels, vasoactive medications, neurological, and urea in the risk nomogram enhanced its ability to predict mortality risk in sepsis patients. (2) The Phoenix diagnostic criteria exhibited superior discriminative power compared to pSOFA and SIRS.</p>

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Establishing a nomogram of the risk of in-hospital mortality in children with suspected sepsis and validating the applicability of the Phoenix

  • 期刊论文

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  • 发表日期：

    2026年4月29日

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  • Shouxing Hu,
  • Qinlan Liu,
  • Xiaoqing Li,
  • Lili Luo

摘要

Objective

This study aimed to develop a nomogram for assessing the risk of in-hospital mortality in children with suspected sepsis admitted to pediatric intensive care unit (PICU). Additionally, it sought to evaluate the applicability of the most recent international diagnostic criteria for pediatric sepsis, the Phoenix diagnostic criteria.

Methods

Data were collected from electronic medical records of pediatric sepsis patients admitted to the PICU at West China Second Hospital, Sichuan University, between January 1, 2021, and August 31, 2023, within the first 24 h of admission. A total of 539 children were randomly assigned to two groups: a training set (n = 458, 85%) and a validation set (n = 80, 15%). The LASSO regression was employed for variable selection. Multivariable logistic regression analysis was used to construct a predictive model incorporating the predictors selected through LASSO regression. A nomogram was constructed based on the selected variables for visual representation. Model validation was performed using a calibration plot, ROC curve, and DCA. The AUC of this model were compared with those of the SIRS, PELODS-2, pSOFA, PMODS, and Phoenix criteria. Subsequently, the pSOFA, SIRS, and Phoenix criteria were applied to data collected within the first 24 h of PICU admission to compare mortality rates based on these criteria in patients with suspected sepsis.

Results

Among the 42 variables examined, LASSO regression analysis identified six significant predictors: urea, P/F ratio, mechanical ventilation, HCO3− levels, vasoactive medications, and neurological. The model, incorporating these six predictors, demonstrated excellent predictive performance, with an AUC of 0.983 in the training set and 0.979 in the validation set. And it was confirmed by the DCA that the model has some clinical utility in terms of the risk of in-hospital mortality. ROC-AUC values and 95% CI of Phoenix, pSOFA, PMODS, SIRS and PELODS-2 scoring systems are 0.958 (0.941–0.976), 0.941 (0.916–0.966), 0.839 (0.787–0.891), 0.662 (0.597–0.726) and 0.918 (0.878–0.958), respectively.

Conclusion

(1) The inclusion of P/F ratio, mechanical ventilation, HCO3− levels, vasoactive medications, neurological, and urea in the risk nomogram enhanced its ability to predict mortality risk in sepsis patients. (2) The Phoenix diagnostic criteria exhibited superior discriminative power compared to pSOFA and SIRS.