Predictive value of laboratory indicators for in-hospital death in children with community-onset sepsis: a prospective observational study of 266 patients

• Published in: BMJ paediatrics open Vol. 8; no. 1; p. e002329
• Main Authors: Liu, jing, Hui, Qin, Lu, Xiuxiu, Li, Wei, Li, Ning, Chen, Yuanmei, Zhang, Qi
• Format: Journal Article
• Language: English
• Published: England BMJ Publishing Group Ltd 15.05.2024; BMJ Publishing Group LTD; BMJ Publishing Group
• Series: Original research
• Subjects: Age; Biomarkers; Biomarkers - blood; Child; Child, Preschool; Community-Acquired Infections - blood; Community-Acquired Infections - diagnosis; Community-Acquired Infections - mortality; Congenital diseases; Data Collection; Fatalities; Female; Hospital Mortality; Humans; Infant; Infections; Intensive Care; Intensive Care Units, Pediatric - statistics & numerical data; Laboratories; Male; Mann-Whitney U test; Medical prognosis; Mortality; Multiple organ dysfunction syndrome; Nervous system; Normal distribution; Observational studies; Pediatrics; Predictive Value of Tests; Prognosis; Prospective Studies; Risk Factors; ROC Curve; Sepsis; Sepsis - blood; Sepsis - diagnosis; Sepsis - mortality; Statistics; Triglycerides; Ventilators; Statistics; Mortality; Data Collection
• ISSN: 2399-9772; 2399-9772
• DOI: 10.1136/bmjpo-2023-002329

Background and objectivesThis study aimed to identify predictors of sepsis-associated in-hospital mortality from readily available laboratory biomarkers at onset of illness that include haematological, coagulation, liver and kidney function, blood lipid, cardiac enzymes and arterial blood gas.MethodsChildren with sepsis were enrolled consecutively in a prospective observational study involving paediatric intensive care units (PICUs) of two hospitals in Beijing, between November 2016 and January 2020. The data on demographics, laboratory examinations during the first 24 hours after PICU admission, complications and outcomes were collected. We screened baseline laboratory indicators using the Least Absolute Shrinkage and Selection Operator (LASSO) analysis, then we constructed a mortality risk model using Cox proportional hazards regression analysis. The ability of risk factors to predict in-hospital mortality was evaluated by receiver operating characteristic (ROC) curves.ResultsA total of 266 subjects were enrolled including 44 (16.5%) deaths and 222 (83.5%) survivors. Those who died showed a shorter length of hospitalisation, and a higher proportion of mechanical ventilation, complications and organ failure (p<0.05). LASSO analysis identified 13 clinical parameters related to prognosis, which were included in the final Cox model. An elevated triglyceride (TG) remained the most significant risk factor of death (HR=1.469, 95% CI: 1.010 to 2.136, p=0.044), followed by base excess (BE) (HR=1.131, 95% CI: 1.046 to 1.223, p=0.002) and pH (HR=0.95, 95% CI: 0.93 to 0.97, p<0.001). The results of the ROC curve showed that combined diagnosis of the three indicators—TG+BE+pH—has the best area under the curve (AUC) (AUC=0.77, 95% CI: 0.69 to 0.85, p<0.001), with a 68% sensitivity and 80% specificity.ConclusionLaboratory factors of TG, BE and pH during the first 24 hours after intensive care unit admission are associated with in-hospital mortality in PICU patients with sepsis. The combination of the three indices has high diagnostic value.