Characteristics and Risk Factors for Pediatric Sepsis

Objective Sepsis is considered a major cause of health loss in children and had high mortality and morbidity.Currently,there is no reliable model for predicting the prognosis of pediatric patients with sepsis.This study aimed to analyze the clinical characteristics of sepsis in children and assess the risk factors associated with poor prognosis in pediatric sepsis patients to identify timely interventions and improve their outcomes.Methods This study analyzed the clinical indicators and laboratory results of septic patients hospitalized in the Pediatric Intensive Care Unit of Tongji Hospital,Tongji Medical College,Huazhong University of Science and Technology,China,from January 1,2019,to December 31,2021.Risk factors for sepsis were identified by logistic regression analyses.Results A total of 355 children with sepsis were enrolled,with 333 children(93.8%)in the good prognosis group,and 22 children(6.2%)in the poor prognosis group.Among them,there were 255 patients(71.8%)in the sepsis group,and 100 patients(28.2%)in the severe sepsis group.The length of hospital stay in the poor prognosis group was longer than that in the good prognosis group(P<0.01).The levels of interleukin 1β(IL-1β)in the poor prognosis group were higher than those in the good prognosis group(P>0.05),and the platelet(PLT),albumin(ALB),and hemoglobin(Hb)levels were lower in the poor prognosis group(P<0.01).The IL-8 levels in the severe sepsis group were higher than those in the sepsis group(P<0.05).Multiple logistic regression analysis suggested that lower Hb levels,ALB levels,peak PLT counts,and higher IL-1βlevels were independent risk factors for poor prognosis in children with sepsis.Conclusion Lower Hb,ALB,and PLT counts and elevated IL-1βare independent risk factors for poor prognosis in children with sepsis.

Artificial intelligence in pediatrics

The rapid development of information technology has involved advances in artificial intelligence(AI),big data processing,and cloud computing,with significant and farreaching effects on the structure and efficiency of the traditional healthcare industry,as well as the establishment and maintenance of modern medical management information systems.AI solutions for handling data in the medical field,such as electronic medical records,medical imaging technology,medical big data,intelligent drug design,and smart health management systems have emerged,which improve the standardization and accuracy of clinical decision making,while providing more dimensions of data accumulation for medical knowledge-based systems.These developments can also support physicians and researchers in the optimization of treatment plans,and decision making about optimal treatment options.This review aims to summarize recent advances in the research and clinical use of AI in pediatrics.