Reliability and validity of methods in the assessment of cold-induced shivering thermogenesis
journal contributionposted on 2020-01-15, 14:13 authored by Josh Arnold, Zach Hemsley, Simon HodderSimon Hodder, George HavenithGeorge Havenith, Alex LloydAlex Lloyd
Purpose: To compare two analytical methods for the estimation of the shivering onset inflection point, segmental regression and visual inspection of data, and to assess the test-retest reliability and validity of four metrics of shivering measurement; oxygen uptake (V̇O2), electromyography (EMG), mechanomyography (MMG) and bedside shivering assessment scale (BSAS). Methods: Ten volunteers attended three identical experimental sessions involving passive deep-body cooling via cold water immersion at 10°C. V̇O2, EMG and MMG were continuously assessed, while the time elapsed at each BSAS stage was recorded. Metrics were graphed as a function of time and rectal temperature (Tre). Inflection points for intermittent and constant shivering were visually identified for every graph and compared to segmental regression. Results: Excellent agreement was seen between segmental regression and visual inspection (ICC, 0.92). All measurement metrics presented good to excellent test-retest reliability (ICC’s > 0.75 and 0.90 respectively), with the exception of visual identification of intermittent shivering for V̇O2 measurement (ICC, 0.73) and segmental regression for EMG measurement (ICC, 0.74). In the assessment of signal-to-noise ratio (SNR), EMG showed the largest SNR at the point of shivering onset, followed by MMG and finally V̇O2. Conclusions: Segmental regression provides a successful analytical method for identifying shivering onset. Good-excellent reliability can be seen across V̇O2, EMG, MMG and BSAS, yet given the observed lag times, SNR’s, along with known advantages/disadvantaged of each metric, it is recommended that no single metric is used in isolation. An integrative, real-time measure of shivering is proposed.
Published inEuropean Journal of Applied Physiology
- AM (Accepted Manuscript)
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Publisher statementThis is an Open Access Article. It is published by Springer under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/