Chinese Medical E-ournals Database

Chinese Journal of Obstetrics & Gynecology and Pediatrics(Electronic Edition) ›› 2023, Vol. 19 ›› Issue (02): 178 -186. doi: 10.3877/cma.j.issn.1673-5250.2023.02.009

Original Article

Analysis of death-related factors in children with sepsis among Pediatric Intensive Care Unit

Shunli Liu, Zhiqing Tian, Yang Cao, Lina Qiao()   

  1. Department of Pediatric Intensive Care Unit, Key Laboratory of Birth Defectsand Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, NHC Key Laboratory of Chronobiology (Sichuan University), Chengdu 610041, Sichuan Province, China
  • Received:2022-10-15 Revised:2023-02-10 Published:2023-04-01
  • Corresponding author: Lina Qiao
  • Supported by:
    National Key R & D Plan Project(2021YFC2701705); Developmental Special Project of Sichuan Provincial Central Leading Local Science and Technology(2021ZYD0105)
Objective

To investigate the death-related factors in children with sepsis among Pediatric Intensive Care Unit (PICU).

Methods

From June 2019 to January 2021, 234 children with sepsis admitted to PICU of West China Second University Hospital, Sichuan University were selected in this study. They were divided into death group (n=44) and survival group (n=190) based on whether they died during PICU stay. Clinical data and laboratory test results within 24 hours of admission were retrospectively analyzed. Based on factors with statistically significant differences (P<0.05) in the univariate analysis and clinical experience, multivariate unconditional logistic regression analysis was conducted to identify the death-related factors of children with sepsis, and a logistic regression equation (predictive model) was established. Receiver operating characteristic (ROC) curves were used to evaluate the predictive value of different indicators for mortality risk in children with sepsis, and the area under the curve (AUC) was calculated. The procedures followed in this study was in line with the World Medical Association Declaration of Helsinki revised in 2013.

Results

① There were statistically significant differences in the age, severity of sepsis, and proportion of patients using vasoactive drugs between two groups (P<0.05). There were also statistically significant differences in the proportion of patients with different levels of sepsis severity between patients aged <5 years and those aged ≥5 years (P<0.05). ② There were statistically significant differences in the levels of serum platelet count (PLT), alanine transaminase (ALT), blood urea nitrogen, serum creatinine (SCr), prothrombin time (PT), serum HCO3-, and lactate between two groups (P<0.05). ③ There were statistically significant differences in the Glasgow score, pediatric sequential organ failure assessment (pSOFA), and pediatric risk of mortality Ⅲ(PRISM Ⅲ) scores between two groups (P<0.05), but no statistically significant difference in the pediatric critical illness score (PCIS) score (P>0.05). ④Multivariate unconditional logistic regression analysis showed that age (OR=1.011, 95%CI: 1.005-1.018, P<0.001) and lactate level (OR=1.132, 95%CI: 1.005-1.275, P=0.041) were independent risk factors for prognosis of children with sepsis. The logistic regression equation (y=0.918-0.312x1+ 0.124x2+ 0.011x3, where x1 is the Glasgow score, x2 is the lactate level, and x3 is age) had good predictive value for mortality risk in children with sepsis, with the ROC-AUC of 0.84 (95%CI: 0.775-0.904, P<0.05). Its sensitivity was 86.4%, and its specificity was 68.4%.

Conclusions

The logistic regression equation established in this study has higher sensitivity and comprehensive value in predicting mortality risk in children with sepsis than the pSOFA score and PRISMⅢ score, and are suitable for early screening of poor prognosis in children with sepsis.

表1 不同年龄段脓毒症患儿严重程度比较[例数(%)]
表2 2组脓毒症患儿一般临床资料比较
表3 2组脓毒症患儿PICU治疗24 h内实验室检查指标比较[M(Q1Q3)]
表4 2组脓毒症患儿危重程度评分比较[分,M(Q1Q3)]
表5 脓毒症患儿预后相关影响因素的多因素非条件logistics回归分析
表6 预测脓毒症患儿预后相关影响因素的ROC曲线分析结果
图1 预测脓毒症患儿死亡风险增高的ROC曲线图注:a本研究建立的预测脓毒症患儿死亡相关影响因素的logistic回归方程(预测模型)为y=0.918-0.312x1+0.124x2+0.011x3,其中,x1为Glasgow评分,x2为血清乳酸浓度,x3为年龄。ROC为受试者特征曲线。PRISMⅢ评分为第3代小儿死亡危险评分,pSOFA儿童序贯器官衰竭评分,PCIS为小儿危重病例评分
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