Evidence map›Paper›PMID 42056947›Full record

ArticleBMC pediatrics2026

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

Shouxing Hu, Qinlan Liu, Xiaoqing Li, Lili Luo

Abstract readValidation Study
In one paragraph

Article in BMC pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Shouxing HuRehabilitation Medicine Center, Institute of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, 610041, China.
Qinlan LiuWest China Second Hospital, Sichuan University, Chengdu, Sichuan Province, 610041, China.
Xiaoqing LiWest China Second Hospital, Sichuan University, Chengdu, Sichuan Province, 610041, China. 439614013@qq.com.
Lili LuoWest China Second Hospital, Sichuan University, Chengdu, Sichuan Province, 610041, China. 1220297792@qq.com.

Funding

Sichuan Provincial Science and Technology Support Program 2023ZYD0124
6 · The paper itself

Abstract

objectiveThis 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.

methodsData 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.

resultsAmong the 42 variables examined, LASSO regression analysis identified six significant predictors: urea, P/F ratio, mechanical ventilation, HCO

conclusion(1) The inclusion of P/F ratio, mechanical ventilation, HCO

Indexed as

Hospital MortalityNomogramsSepsisChildChild, PreschoolChinaFemaleHumansInfantIntensive Care Units, PediatricLogistic ModelsMaleRetrospective StudiesRisk AssessmentROC CurveChildrenNomogramPhoenixPrognosisSepsis

Identifiers

PMID42056947
PMCPMC13348149

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