A Heart Rate Based Algorithm to Estimate Core Temperature Responses in Elite Athletes Exercising in the Heat

Johannus Q de Korte; Bertil J Veenstra; Mark van Rijswick; Eline J K Derksen; Maria T E Hopman; Coen C W G Bongers; Thijs M H Eijsvogels

doi:10.3389/fspor.2022.882254

A Heart Rate Based Algorithm to Estimate Core Temperature Responses in Elite Athletes Exercising in the Heat

Front Sports Act Living. 2022 Jun 22:4:882254. doi: 10.3389/fspor.2022.882254. eCollection 2022.

Authors

Johannus Q de Korte¹, Bertil J Veenstra², Mark van Rijswick², Eline J K Derksen¹, Maria T E Hopman¹, Coen C W G Bongers¹, Thijs M H Eijsvogels¹

Affiliations

¹ Department of Physiology, Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, Netherlands.
² Institute of Training Medicine & Training Physiology, TGTF, Royal Netherlands Army, Utrecht, Netherlands.

Abstract

Purpose: Non-invasive non-obtrusive continuous and real-time monitoring of core temperature (T_c) may enhance pacing strategies, the efficacy of heat mitigation measures, and early identification of athletes at risk for heat-related disorders. The Estimated Core Temperature (ECTemp™) algorithm uses sequential heart rate (HR) values to predict T_c. We examined the validity of ECTemp™ among elite athletes exercising in the heat.

Methods: 101 elite athletes performed an exercise test in simulated hot and humid environmental conditions (ambient temperature: 31.6 ± 1.0°C, relative humidity: 74 ± 5%). T_c was continuously measured using a validated ingestible telemetric temperature capsule system. In addition, HR was continuously measured and used to compute the estimated core temperature (T_c-est) using the ECTemp™ algorithm.

Results: Athletes exercised for 44 ± 10 min and n = 5,025 readouts of T_c (range: 35.8-40.4°C), HR (range: 45-207 bpm), and T_c-est (range: 36.7-39.9°C) were collected. T_c-est demonstrated a small yet significant bias of 0.15 ± 0.29°C (p < 0.001) compared to T_c, with a limit of agreement of ±0.45°C and a root mean square error of 0.35 ± 0.18°C. Utilizing the ECTemp™ algorithm as a diagnostic test resulted in a fair to excellent sensitivity (73-96%) and specificity (72-93%) for T_c-est thresholds between 37.75 and 38.75°C, but a low to very-low sensitivity (50-0%) for T_c-est thresholds >39.0°C, due to a high prevalence of false-negative observations.

Conclusion: ECTemp™ provides a valuable and representative indication of thermal strain in the low- to mid-range of T_c values observed during exercise in the heat. It may, therefore, be a useful non-invasive and non-obtrusive tool to inform athletes and coaches about the estimated core temperature during controlled hyperthermia heat acclimation protocols. However, the ECTemp™ algorithm, in its current form, should not solely be used to identify athletes at risk for heat-related disorders due to low sensitivity and high false-negative rate in the upper end of the T_c spectrum.

Keywords: physiological thermal strain; prediction; real-time monitoring; sports; validity.