A Machine Learning-Based Prediction Model for Acute Kidney Injury in Patients With Community-Acquired Pneumonia: Multicenter Validation Study.

Journal: Journal of medical Internet research
PMID:

Abstract

BACKGROUND: Acute kidney injury (AKI) is common in patients with community-acquired pneumonia (CAP) and is associated with increased morbidity and mortality.

Authors

  • Mengqing Ma
    Department of Nephrology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
  • Caimei Chen
    Department of Nephrology, Wuxi People's Hospital Affiliated with Nanjing Medical University, Wuxi, China.
  • Dawei Chen
    Department of Nephrology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
  • Hao Zhang
    College of Mechanical and Electrical Engineering, Henan Agricultural University, Zhengzhou, 450002, China.
  • Xia Du
    Department of Nephrology, Sir Run Run Hospital, Nanjing Medical University, Nanjing, China.
  • Qing Sun
    a State Key Laboratory of Food Science and Technology, Jiangnan University , Jiangsu , China.
  • Li Fan
    Department of Radiology, Second Affiliated Hospital of Naval Medical University, Shanghai, China.
  • Huiping Kong
    Department of Nephrology, Sir Run Run Hospital, Nanjing Medical University, Nanjing, China.
  • Xueting Chen
    Department of Nephrology, Xinyi people's Hospital, Xuzhou, China.
  • Changchun Cao
    Department of Nephrology, Sir Run Run Hospital, Nanjing Medical University, Nanjing, China.
  • Xin Wan
    SCNU Environmental Research Institute, Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety & MOE Key Laboratory of Theoretical Chemistry of Environment, School of Environment, South China Normal University, Guangzhou, 510006, PR China; SCNU Qingyuan Institute of Science and Technology Innovation Co, Ltd, Qingyuan 511517, PR China.