Using Predictive Modeling Technique to Assess Core Temperature Adaptations from Heart Rate, Sweat Rate, and Thermal Sensation in Heat Acclimatization and Heat Acclimation

Assessing the adaptation of rectal temperature (T(rec)) is critical following heat acclimatization (HAz) and heat acclimation (HA) because it is associated with exercise performance and safety; however, more feasible and valid methods need to be identified. The purpose of this study was to predict adaptations in T(rec) from heart rate (HR), sweat rate (SR), and thermal sensation (TS) using predictive modeling techniques. Twenty-five male endurance athletes (age, 36 ± 12 y; VO(2max), 57.5 ± 7.0 mL⋅kg(−1)⋅min(−1)) completed three trials consisting of 60 min running at 59.3 ± 1.7% vVO(2max) in a hot environment. During trials, the highest HR and TS, SR, and T(rec) at the end of trials were recorded. Following a baseline trial, participants performed HAz followed by a post-HAz trial and then completed five days HA, followed by a post-HA trial. A decision tree indicated cut-points of HR (<−13 bpm), SR (>0.3 L·h(−1)), and TS (≤−0.5) to predict lower T(rec). When two or three variables met cut-points, the probability of accuracy of showing lower T(rec) was 95.7%. Greater adaptations in T(rec) were observed when two or three variables met cut-points (−0.71 ± 0.50 °C) compared to one (−0.13 ± 0.36 °C, p < 0.001) or zero (0.0 3 ± 0.38 °C, p < 0.001). Specificity was 0.96 when two or three variables met cut-points to predict lower T(rec). These results suggest using heart rate, sweat rate, and thermal sensation adaptations to indicate that the adaptations in T(rec) is beneficial following heat adaptations, especially in field settings, as a practical and noninvasive method.