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Updated: Jun 15, 2025
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Point-of-Care Ultrasound: A Review of Ultrasound Parameters for Predicting Difficult Airways
Published on: April 7, 2023
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Artificial intelligence for difficult airway assessment: a protocol for a systematic review with meta-analysis
Weiyi Zhang1, Li Du2, Yujie Huang1,3
1Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
BMJ Open
|June 11, 2025
Summary
This systematic review protocol outlines a plan to evaluate artificial intelligence (AI) for difficult airway assessment. The goal is to determine AI
Area of Science:
- Medical Informatics
- Anesthesiology
- Artificial Intelligence in Medicine
Background:
- Accurate difficult airway assessment is critical for patient safety during airway management.
- Artificial intelligence (AI) shows promise in predicting difficult airways, but its diagnostic performance is unclear.
- Existing studies often suffer from small sample sizes and inconsistent methodologies.
Purpose of the Study:
- To systematically review and meta-analyze the diagnostic value of AI algorithms for difficult airway assessment.
- To provide a comprehensive evaluation of AI's accuracy in identifying patients with difficult airways.
Main Methods:
- A systematic search of multiple English and Chinese databases and clinical trial registries up to January 2025.
- Meta-analysis of diagnostic accuracy indicators including sensitivity, specificity, and AUC.
- Assessment of risk of bias, quality of evidence, heterogeneity, and publication bias.
Main Results:
- This section is not applicable as the study is a protocol for a systematic review and meta-analysis.
- Results will be determined after data collection and analysis.
Conclusions:
- This systematic review protocol aims to clarify the diagnostic accuracy of AI in difficult airway assessment.
- The findings will inform the clinical application of AI tools for improved patient safety in airway management.
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