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Updated: Apr 2, 2026

A Preclinical Model of Exertional Heat Stroke in Mice
Published on: July 1, 2021
Thermal Response Patterns Provide Early Sign of Exertional Heat Stroke during Intense Activity
Emma Atkinson1, Nisha Charkoudian1, Kyla Driver1
1Thermal and Mountain Medicine Division, U.S Army Research Institute of Environmental Medicine, Natick, MA.
Objective:
Exertional heat stroke (EHS) remains a stubborn challenge for active communities globally, but it is difficult to study in humans because it is a relatively rare occurrence. Severe EHS can lead to long-term organ damage and death without rapid treatment. Physiological monitoring may provide early warning that an individual is at risk of EHS. The purpose of this work was to compare heart rate (HR) and thermal (skin and core temperature) response patterns of individuals who experienced EHS with those of others completing the same training event, who did not.
Methods:
Heart Rate (HR), chest skin temperature (Tsk), three-axis accelerometry, and estimated core temperature (Tect) were collected using a chest-mounted physiological monitor on seven individuals who experienced an EHS (age = 22 ± 4 yr, ht = 1.8 ± 0.1 m, wt = 86.1 ± 11.3 kg, 1-mile run = 7:20 ± 0:43, Tr = 41.6 ± 0.6°C at collapse) during a loaded military ruck march. Similar data were collected on three controls for each EHS case, matched for age, height, weight, and fitness (N = 21, age = 21 ± 3 yr, ht = 1.8 ± 0.1 m, wt = 85.5 ± 10.8 kg, 1-mile run = 7:09 ± 0:42 min). Each ruck march was divided into four quartiles based on event completion percentage. Mean HR, Tsk, the Gait Instability Index (GINI), and Tect were computed for each quartile. These profiles were compared between groups by two-way analysis of variance.
Results:
Tect increased faster over time ( P = 0.001) in EHS. HR and Tsk showed different patterns over time and were higher in EHS during the second, third, and fourth quartile, resulting in a narrower Tsk-Tc gradient in the EHS group. The GINI was higher in EHS only during the fourth quartile.
Conclusions:
We report for the first time an early detection method for EHS in prolonged military events, incorporating patterns of HR, Tsk, and Tect.
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