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Characteristics and Risk Factors for pediatric sepsis

Current Medical Science 2024年第3期44卷 648-656页

作者： Yong-bing ZHU Tong-lin LIU Qi DAI Shu-fan LIU Peng XIONG Hao HUANG Yi YUAN Tian-nan ZHANG Yu CHEN Department of pediatric Intensive Care Unit Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan430030China

Objective sepsis is considered a major cause of health loss in children and had high mortality and ***,there is no reliable model for predicting the prognosis of pediatric patients with *** 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 *** 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,*** factors for sepsis were identified by logistic regression *** 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 *** them,there were 255 patients(71.8%)in the sepsis group,and 100 patients(28.2%)in the severe sepsis *** length of hospital stay in the poor prognosis group was longer than that in the good prognosis group(P0.05),and the platelet(PLT),albumin(ALB),and hemoglobin(Hb)levels were lower in the poor prognosis group(Psepsis group were higher than those in the sepsis group(Psepsis.

关键词： pediatric sepsis inflammation severity prognosis risk factors

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Prediction of pediatric sepsis Using a Deep Encoding Network with Cross Features

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Journal of Shanghai Jiaotong university(Science) 2024年第1期29卷 131-140页

作者：陈潇张瑞汤心溢钱娟 University of Chinese Academy of Sciences Beijing 100084China Shanghai Institute of Technical Physics of the Chinese Academy of Sciences Key Laboratory of Infrared Detection and Imaging TechnologyShanghai 200083China Shanghai Children's Medical Center Shanghai Jiao Tong University School of MedicineShanghai 200127China

sepsis poses a serious threat to health of children in pediatric intensive care *** mortality from pediatric sepsis can be effectively reduced through in-time diagnosis and therapeutic *** bacilliculture detection method is too time-consuming to receive timely *** this research,we propose a new framework:a deep encoding network with cross features(CF-DEN)that enables accurate early detection of *** features are automatically constructed via the gradient boosting decision tree and distilled into the deep encoding network(DEN)we *** DEN is aimed at learning sufficiently effective representation from clinical test *** layer of the DEN fltrates the features involved in computation at current layer via attention mechanism and outputs the current prediction which is additive layer by layer to obtain the embedding feature at last *** framework takes the advantage of tree-based method and neural network method to extract effective representation from small clinical dataset and obtain accurate prediction in order to prompt patient to get timely *** evaluate the performance of the framework on the dataset collected from Shanghai Children's Medical *** with common machine learning methods,our method achieves the increase on F1-score by 16.06%on the test set.

关键词： pediatric sepsis gradient boosting decision tree cross feature neural network deep encoding network with cross features(CF-DEN)

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