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Reliability and validity of methods in the assessment of cold-induced shivering thermogenesis

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 (V̇O(2)), electromyography (EMG),...

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Detalles Bibliográficos
Autores principales: Arnold, Josh T., Hemsley, Zach, Hodder, Simon G., Havenith, George, Lloyd, Alex B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7042274/
https://www.ncbi.nlm.nih.gov/pubmed/31955279
http://dx.doi.org/10.1007/s00421-019-04288-2
Descripción
Sumario: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 (V̇O(2)), 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. V̇O(2), 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 (T(re)). 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 V̇O(2) 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 V̇O(2). CONCLUSIONS: Segmental regression provides a successful analytical method for identifying shivering onset. Good-to-excellent reliability can be seen across V̇O(2), EMG, MMG, and BSAS, yet given the observed lag times, SNRs, 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.