Innovative strategies against superbugs: Developing an AI-CDSS for precise Stenotrophomonas maltophilia treatment.

Journal: Journal of global antimicrobial resistance
PMID: 38909685

Abstract

OBJECTIVES: The World Health Organization named Stenotrophomonas maltophilia (SM) a critical multi-drug resistant threat, necessitating rapid diagnostic strategies. Traditional culturing methods require up to 96 h, including 72 h for bacterial growth, identification with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) through protein profile analysis, and 24 h for antibiotic susceptibility testing. In this study, we aimed at developing an artificial intelligence-clinical decision support system (AI-CDSS) by integrating MALDI-TOF MS and machine learning to quickly identify levofloxacin and trimethoprim/sulfamethoxazole resistance in SM, optimizing treatment decisions.

Authors

  • Tai-Han Lin
    Department of Pathology, Division of Clinical Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, Republic of China.
  • Hsing-Yi Chung
    Department of Pathology, Division of Clinical Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, Republic of China; Graduate Institute of Medical Science, National Defense Medical Center, Taipei, Taiwan, Republic of China.
  • Ming-Jr Jian
    Department of Pathology, Division of Clinical Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, Republic of China.
  • Chih-Kai Chang
    Department of Pathology, Division of Clinical Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, Republic of China.
  • Hung-Hsin Lin
    Department of Pathology, Division of Clinical Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, Republic of China.
  • Ching-Mei Yu
    Department of Pathology, Division of Clinical Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, Republic of China.
  • Cherng-Lih Perng
    Department of Pathology, Division of Clinical Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, Republic of China.
  • Feng-Yee Chang
    Department of Internal Medicine, Division of Infectious Diseases and Tropical Medicine, Tri-Service General Hospital, National Defense Medical Centre, Taipei, Taiwan, Republic of China.
  • Chien-Wen Chen
    Department of Internal Medicine, Division of Pulmonary and Critical Care Medicine, Tri-Service General Hospital, National Defense Medical Centre, Taipei, Taiwan, Republic of China.
  • Hung-Sheng Shang
    Department of Pathology, Division of Clinical Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, Republic of China. Electronic address: iamkeith001@gmail.com.

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