A Systematic Method to Detect the Metabolic Threshold from Gas Exchange during Incremental Exercise.

Area of Science:

• Exercise Physiology
• Cardiorespiratory Fitness Assessment

Background:

• The metabolic threshold (V̇O) is a key indicator of aerobic function, derived from gas exchange during incremental exercise.
• Accurate identification of V̇O is crucial for exercise prescription and performance analysis.
• Current methods for V̇O detection show variability, particularly between experienced and novice interpreters and automated algorithms.

Purpose of the Study:

• To compare the variability in V̇O selection between experienced interpreters, novice interpreters, and an automated metabolic cart system.
• To assess the impact of interpreter experience and systematic approaches on V̇O identification reliability.
• To identify shortcomings in current V̇O detection guidelines and propose improvements.

Main Methods:

• Ten healthy men completed three incremental cycle exercise tests with breath-by-breath gas exchange monitoring.
• V̇O was determined independently by two experienced interpreters, four novice interpreters, and a commercial metabolic cart.
• Interpreters documented their methods and confidence levels for V̇O selection.

Main Results:

• Experienced interpreters showed good agreement with each other and the automated system (mean differences of 21 and 23 mL·min⁻¹, respectively).
• Novice interpreters exhibited substantial disagreement among themselves and with experienced interpreters (range of -664 to 364 mL·min⁻¹).
• Despite overall agreement, discrepancies >500 mL·min⁻¹ occurred in 50% of cases between experienced interpreters and the automated system; novices reported higher confidence despite inconsistent results.

Conclusions:

• Interpreter experience and a systematic approach are critical for reliable V̇O identification.
• Existing guidelines lack specific protocols for V̇O detection, potentially leading to inaccurate aerobic function assessments.
• The study proposes systematic strategies to improve consistency and accuracy in V̇O detection for practical application.