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Area of Science:

  • Medical Education
  • Artificial Intelligence in Medicine
  • Trauma Surgery

Background:

  • Artificial intelligence language models like ChatGPT show promise as accessible educational tools in orthopaedic surgery.
  • However, the accuracy of references provided by AI models is a critical concern for medical content integrity.
  • This study focuses on the reliability of ChatGPT-4's references for the ABCDE trauma protocol.

Purpose of the Study:

  • To evaluate the accuracy of references generated by ChatGPT-4 for the Airway, Breathing, Circulation, Disability, Exposure (ABCDE) approach in trauma surgery.
  • To assess the reliability and reproducibility of AI-generated medical references.

Main Methods:

  • Two independent reviewers assessed 30 ChatGPT-4 generated references for the ABCDE trauma protocol.
  • References were graded as nonexistent, inaccurate, or accurate.
  • Cohen's Kappa coefficient and descriptive statistics were used to analyze inter-rater agreement and mean accuracy.

Main Results:

  • ChatGPT-4 achieved an average reference accuracy score of 66.7%.
  • Only 43.3% of the 30 references were accurate; 56.7% were inaccurate or nonexistent.
  • Reference accuracy was consistent across the five trauma protocol categories (p = 0.437).

Conclusions:

  • ChatGPT-4's high rate of inaccurate or nonexistent references (57%) raises safety concerns for professional medical decision-making without verification.
  • The AI model can serve as an adjunct learning tool if used cautiously with cross-referencing to enhance knowledge rehearsal.