Enhancing the accuracy and effectiveness of diagnosis of spontaneous bacterial peritonitis in cirrhotic patients: A machine learning approach utilizing clinical and laboratory data.

Journal: Advances in medical sciences
PMID: 39419440

Abstract

PURPOSE: Spontaneous bacterial peritonitis (SBP) is a bacterial infection of ascitic fluid that develops naturally, without being triggered by any surgical conditions or procedures, and is a common complication of cirrhosis. With a potential mortality rate of 40 ​%, accurate diagnosis and prompt initiation of appropriate antibiotic therapy are crucial for optimizing patient outcomes and preventing life-threatening complications. This study aimed to expand the use of computational models to improve the diagnostic accuracy of SBP in cirrhotic patients by incorporating a broader range of data, including clinical variables and laboratory values.

Authors

  • Babak Khorsand
    Department of Neurology, University of California, Irvine, CA, USA.
  • Mohsen Rajabnia
    Non-Communicable Diseases Research Center, Alborz University of Medical Sciences, Karaj, Iran. Electronic address: dr.rajabnia@outlook.com.
  • Ali Jahanian
    Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Mobin Fathy
    Students Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Somayye Taghvaei
    Department of Medical Biotechnology, National Institute of Genetic Engineering and Biotechnology, Tehran, Iran.
  • Hamidreza Houri
    Foodborne and Waterborne Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran. Electronic address: hr.houri@sbmu.ac.ir.

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