Artificial intelligence for difficult airway assessment: a protocol for a systematic review with meta-analysis.

Journal: BMJ open
Published Date: Jun 10, 2025

Abstract

INTRODUCTION: Identifying difficult airways and avoiding unanticipated difficult airways through difficult airway assessment are crucial for patient safety prior to airway management. Therefore, accurately predicting difficult airways through airway assessment is a fundamental and significant technique in airway management by clinicians. Artificial intelligence (AI) is a rapidly evolving science with greater data processing ability than humans. AI, given its ever-expanding applications in medical diagnosis and disease prediction, has been employed to predict cases with difficult airways. Nevertheless, the diagnostic performance of AI algorithms for difficult airway assessment remains unclear due to the small sample sizes, insufficient image acquisition standards and poor predictive accuracies. Consequently, this study aims to formulate a protocol for a systematic review and meta-analysis to ascertain the diagnostic value of AI in assessing difficult airways.

Authors

  • Weiyi Zhang
    Key Laboratory of Horticultural Plant Biology (MOE), College of Horticulture and Forestry Sciences, Huazhong Agricultural University, Wuhan, 430070, China.
  • Li Du
    Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai, People's Republic of China.
  • Yujie Huang
    Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
  • Dan Liu
    Department of Bioengineering, Temple University, Philadelphia, PA, United States.
  • Tingting Li
    Key Laboratory of Biotechnology and Bioresources Utilization (Dalian Minzu University), Ministry of Education, Dalian, China.
  • Jianqiao Zheng
    Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China zhjq1983@163.com.

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