Development and validation of a mortality risk model for pediatric sepsis

被引:17
|
作者
Chen, Mengshi [1 ,2 ]
Lu, Xiulan [1 ]
Hu, Li [2 ,3 ]
Liu, Pingping [1 ]
Zhao, Wenjiao [1 ]
Yan, Haipeng [1 ]
Tang, Liang [1 ]
Zhu, Yimin [1 ]
Xiao, Zhenghui [1 ]
Chen, Lizhang [2 ]
Tan, Hongzhuan [2 ]
机构
[1] Hunan Childrens Hosp, Ziyuan RD, Changsha, Hunan, Peoples R China
[2] Cent South Univ, Sch Publ Hlth, Dept Epidemiol & Hlth Stat, Changsha, Hunan, Peoples R China
[3] Beijing Ctr Dis Prevent & Control, Beijing, Peoples R China
关键词
mortality; model; pediatric; sepsis; C-REACTIVE PROTEIN; SEPTIC SHOCK; PROCALCITONIN; INFECTION; SCORE; EPIDEMIOLOGY; PROGRESSION; CHILDREN; OUTCOMES;
D O I
10.1097/MD.0000000000006923
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Pediatric sepsis is a burdensome public health problem. Assessing the mortality risk of pediatric sepsis patients, offering effective treatment guidance, and improving prognosis to reduce mortality rates, are crucial. We extracted data derived from electronic medical records of pediatric sepsis patients that were collected during the first 24 hours after admission to the pediatric intensive care unit (PICU) of the Hunan Children's hospital from January 2012 to June 2014. A total of 788 children were randomly divided into a training (592, 75%) and validation group (196, 25%). The risk factors for mortality among these patients were identified by conducting multivariate logistic regression in the training group. Based on the established logistic regression equation, the logit probabilities for all patients (in both groups) were calculated to verify the model's internal and external validities. According to the training group, 6 variables (brain natriuretic peptide, albumin, total bilirubin, D-dimer, lactate levels, and mechanical ventilation in 24 hours) were included in the final logistic regression model. The areas under the curves of the model were 0.854 (0.826, 0.881) and 0.844 (0.816, 0.873) in the training and validation groups, respectively. The Mortality Risk Model for Pediatric Sepsis we established in this study showed acceptable accuracy to predict the mortality risk in pediatric sepsis patients.
引用
收藏
页数:5
相关论文
共 50 条
  • [21] External validation of the Pediatric Extracorporeal Membrane Oxygenation Prediction model for risk adjusting mortality
    Bailly, David K.
    Furlong-Dillard, Jamie M.
    Winder, Melissa
    Lavering, Mark
    Barbaro, Ryan P.
    Meert, Kathleen L.
    Bratton, Susan L.
    Dalton, Heidi
    Reeder, Ron W.
    PERFUSION-UK, 2021, 36 (04): : 407 - 414
  • [22] Validation of a Risk Prediction Model for In-hospital Mortality Following Pediatric Heart Transplantation
    Almond, C. S.
    Gauvreau, K.
    Canter, C.
    Piercey, G. E.
    Singh, T. P.
    JOURNAL OF HEART AND LUNG TRANSPLANTATION, 2010, 29 (02): : S36 - S36
  • [23] VALIDATION OF A RISK PREDICTION MODEL FOR IN-HOSPITAL MORTALITY FOLLOWING PEDIATRIC HEART TRANSPLANTATION
    Almond, Christoher S. d.
    Gauvreau, Kimberlee
    Canter, Charles E.
    Piercey, Gary E.
    Singh, T. P.
    JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY, 2010, 55 (10)
  • [24] Development and Validation of the Phoenix Criteria for Pediatric Sepsis and Septic Shock
    Sanchez-Pinto, L. Nelson
    Bennett, Tellen D.
    DeWitt, Peter E.
    Russell, Seth
    Rebull, Margaret N.
    Martin, Blake
    Akech, Samuel
    Albers, David J.
    Alpern, Elizabeth R.
    Balamuth, Fran
    Bembea, Melania
    Chisti, Mohammod Jobayer
    Evans, Idris
    Horvat, Christopher M.
    Jaramillo-Bustamante, Juan Camilo
    Kissoon, Niranjan
    Menon, Kusum
    Scott, Halden F.
    Weiss, Scott L.
    Wiens, Matthew O.
    Zimmerman, Jerry J.
    Argent, Andrew C.
    Sorce, Lauren R.
    Schlapbach, Luregn J.
    Watson, R. Scott
    JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 2024, 331 (08): : 675 - 686
  • [25] Development and Validation of Risk Prediction Model on Novel Clinical Sepsis Phenotype for Personalized Management and Precise Care for Sepsis
    Lee, Y.
    Lee, J.
    Kim, D.
    Kim, K.
    Lee, S.
    Lee, H.
    Song, C.
    Yu, H.
    Park, J.
    Moon, S.
    Jeon, E.
    Yon, D.
    Heo, J.
    AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, 2020, 201
  • [26] Development and Validation of an Automated Sepsis Risk Assessment System
    Back, Ji-Sun
    Jin, Yinji
    Jin, Taixian
    Lee, Sun-Mi
    RESEARCH IN NURSING & HEALTH, 2016, 39 (05) : 317 - 327
  • [27] Development and validation of a sepsis diagnostic scoring model for neonates with suspected sepsis
    Sokou, Rozeta
    Ioakeimidis, Georgios
    Piovani, Daniele
    Parastatidou, Stavroula
    Konstantinidi, Aikaterini
    Tsantes, Andreas G.
    Lampridou, Maria
    Houhoula, Dimitra
    Iacovidou, Nicoletta
    Kokoris, Styliani
    Vaiopoulos, Aristeidis G.
    Gialeraki, Argyri
    Kopterides, Petros
    Bonovas, Stefanos
    Tsantes, Argirios E.
    FRONTIERS IN PEDIATRICS, 2022, 10
  • [28] Development and validation of prognosis model of mortality risk in patients with COVID-19
    Ma, Xuedi
    Ng, Michael
    Xu, Shuang
    Xu, Zhouming
    Qiu, Hui
    Liu, Yuwei
    Lyu, Jiayou
    You, Jiwen
    Zhao, Peng
    Wang, Shihao
    Tang, Yunfei
    Cui, Hao
    Yu, Changxiao
    Wang, Feng
    Shao, Fei
    Sun, Peng
    Tang, Ziren
    EPIDEMIOLOGY AND INFECTION, 2020, 148
  • [29] Development and validation of a multivariable mortality risk prediction model for COPD in primary care
    Shah, Syed A.
    Nwaru, Bright, I
    Sheikh, Aziz
    Simpson, Colin R.
    Kotz, Daniel
    NPJ PRIMARY CARE RESPIRATORY MEDICINE, 2022, 32 (01)
  • [30] Development and validation of a multivariable mortality risk prediction model for COPD in primary care
    Syed A. Shah
    Bright I. Nwaru
    Aziz Sheikh
    Colin R. Simpson
    Daniel Kotz
    npj Primary Care Respiratory Medicine, 32