Development and validation of a real-time risk prediction model for acute kidney injury in hospitalized pediatric patients.

Journal: World journal of pediatrics : WJP
Published Date:

Abstract

BACKGROUND: Acute kidney injury is associated with a prolonged hospital stay and high mortality for pediatric patients. The previous prediction models are based on a pre-defined time window which may affect its feasibility in clinical practice. This study aimed to develop and validate a real-time acute kidney injury risk prediction model for hospitalized pediatric patients.

Authors

  • Chao Zhang
    School of Information Engineering, Suqian University, Suqian, Jiangsu, China.
  • Chen Wang
    Department of Cardiovascular Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
  • Qin-Shi Hu
    Big Data Center for Children's Medical Care, Children's Hospital of Chongqing Medical University, Chongqing, China.
  • Xi-Ming Xu
    Big Data Center for Children's Medical Care, Children's Hospital of Chongqing Medical University, Chongqing, China.
  • Ruo-Hua Yan
    Department of Clinical Epidemiology and Evidence-Based Medicine, National Center for Children Health, Beijing Children's Hospital, Capital Medical University, No.56 Nanlishi Road, Xicheng District, Beijing, 100045, China.
  • Xiao-Lu Nie
    Department of Clinical Epidemiology and Evidence-Based Medicine, National Center for Children Health, Beijing Children's Hospital, Capital Medical University, No.56 Nanlishi Road, Xicheng District, Beijing, 100045, China.
  • Ya-Guang Peng
    Department of Clinical Epidemiology and Evidence-Based Medicine, National Center for Children Health, Beijing Children's Hospital, Capital Medical University, No.56 Nanlishi Road, Xicheng District, Beijing, 100045, China.
  • Hai-Ping Yang
    Department of Nephrology, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatric Metabolism and Inflammatory Disease, Children's Hospital of Chongqing Medical University, No. 136 Zhongshan Er Road, Yuzhong District, Chongqing, 400014, China.
  • Yao Song
    The Hong Kong Polytechnic University, Kowloon 999077, Hong Kong.
  • Xue-Jun Yang
    Department of Nephrology, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatric Metabolism and Inflammatory Disease, Children's Hospital of Chongqing Medical University, No. 136 Zhongshan Er Road, Yuzhong District, Chongqing, 400014, China. bonnie_everything@163.com.
  • Xiao-Xia Peng
    Department of Clinical Epidemiology and Evidence-Based Medicine, National Center for Children Health, Beijing Children's Hospital, Capital Medical University, No.56 Nanlishi Road, Xicheng District, Beijing, 100045, China. pengxiaoxia@bch.com.cn.

Keywords

No keywords available for this article.