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AI-Assisted Anaerobic Threshold Interpretation in Cardiopulmonary Exercise Testing
Sponsor: Shanghai Zhongshan Hospital
Summary
This prospective randomized two-period crossover reader study will evaluate whether assistance from a frozen artificial intelligence model improves physicians' interpretation of the anaerobic threshold (AT) in cardiopulmonary exercise testing (CPET). Sixteen physicians, including 8 senior and 8 junior readers, will each interpret 150 de-identified CPET examinations once without AI assistance and once with AI assistance. The primary outcome is the within-physician difference in absolute AT localization error between the assisted and unassisted conditions. Secondary outcomes include signed timing error, agreement on whether AT is present, estimates within 15 and 30 seconds of the reference, inter-reader reliability, interpretation time, and whether the effect of AI assistance differs by physician seniority.
Official title: A Randomized Two-Period Crossover Reader Study of Artificial Intelligence-Assisted Anaerobic Threshold Interpretation in Cardiopulmonary Exercise Testing
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
INTERVENTIONAL
Enrollment
16
Start Date
2026-09-25
Completion Date
2026-11-25
Last Updated
2026-09-22
Healthy Volunteers
Yes
Interventions
AI-Assisted Anaerobic Threshold Interpretation
A frozen PACE-Former model provides a predicted anaerobic threshold time within the CPET review interface. Physicians retain responsibility for the final classification and AT time annotation. No other model output or reference label is displayed.
Unassisted Cardiopulmonary Exercise Test Interpretation
The physician reviews the same de-identified CPET data using the study interface without display of any model prediction or AI-generated suggestion and independently classifies AT status and records the AT time when confirmed.
Locations (1)
Zhongshan Hospital, Fudan University
Shanghai, Shanghai Municipality, China