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Smartwatch-Based Maximum Oxygen Consumption Measurement for Predicting Acute Mountain Sickness: Diagnostic Accuracy Evaluation Study

BACKGROUND: Cardiorespiratory fitness plays an important role in coping with hypoxic stress at high altitudes. However, the association of cardiorespiratory fitness with the development of acute mountain sickness (AMS) has not yet been evaluated. Wearable technology devices provide a feasible assess...

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Autores principales: Ye, Xiaowei, Sun, Mengjia, Yu, Shiyong, Yang, Jie, Liu, Zhen, Lv, Hailin, Wu, Boji, He, Jingyu, Wang, Xuhong, Huang, Lan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10360014/
https://www.ncbi.nlm.nih.gov/pubmed/37410528
http://dx.doi.org/10.2196/43340
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author Ye, Xiaowei
Sun, Mengjia
Yu, Shiyong
Yang, Jie
Liu, Zhen
Lv, Hailin
Wu, Boji
He, Jingyu
Wang, Xuhong
Huang, Lan
author_facet Ye, Xiaowei
Sun, Mengjia
Yu, Shiyong
Yang, Jie
Liu, Zhen
Lv, Hailin
Wu, Boji
He, Jingyu
Wang, Xuhong
Huang, Lan
author_sort Ye, Xiaowei
collection PubMed
description BACKGROUND: Cardiorespiratory fitness plays an important role in coping with hypoxic stress at high altitudes. However, the association of cardiorespiratory fitness with the development of acute mountain sickness (AMS) has not yet been evaluated. Wearable technology devices provide a feasible assessment of cardiorespiratory fitness, which is quantifiable as maximum oxygen consumption (VO(2)max) and may contribute to AMS prediction. OBJECTIVE: We aimed to determine the validity of VO(2)max estimated by the smartwatch test (SWT), which can be self-administered, in order to overcome the limitations of clinical VO(2)max measurements. We also aimed to evaluate the performance of a VO(2)max-SWT–based model in predicting susceptibility to AMS. METHODS: Both SWT and cardiopulmonary exercise test (CPET) were performed for VO(2)max measurements in 46 healthy participants at low altitude (300 m) and in 41 of them at high altitude (3900 m). The characteristics of the red blood cells and hemoglobin levels in all the participants were analyzed by routine blood examination before the exercise tests. The Bland-Altman method was used for bias and precision assessment. Multivariate logistic regression was performed to analyze the correlation between AMS and the candidate variables. A receiver operating characteristic curve was used to evaluate the efficacy of VO(2)max in predicting AMS. RESULTS: VO(2)max decreased after acute high altitude exposure, as measured by CPET (25.20 [SD 6.46] vs 30.17 [SD 5.01] at low altitude; P<.001) and SWT (26.17 [SD 6.71] vs 31.28 [SD 5.17] at low altitude; P<.001). Both at low and high altitudes, VO(2)max was slightly overestimated by SWT but had considerable accuracy as the mean absolute percentage error (<7%) and mean absolute error (<2 mL·kg(–1)·min(–1)), with a relatively small bias compared with VO(2)max-CPET. Twenty of the 46 participants developed AMS at 3900 m, and their VO(2)max was significantly lower than that of those without AMS (CPET: 27.80 [SD 4.55] vs 32.00 [SD 4.64], respectively; P=.004; SWT: 28.00 [IQR 25.25-32.00] vs 32.00 [IQR 30.00-37.00], respectively; P=.001). VO(2)max-CPET, VO(2)max-SWT, and red blood cell distribution width-coefficient of variation (RDW-CV) were found to be independent predictors of AMS. To increase the prediction accuracy, we used combination models. The combination of VO(2)max-SWT and RDW-CV showed the largest area under the curve for all parameters and models, which increased the area under the curve from 0.785 for VO(2)max-SWT alone to 0.839. CONCLUSIONS: Our study demonstrates that the smartwatch device can be a feasible approach for estimating VO(2)max. In both low and high altitudes, VO(2)max-SWT showed a systematic bias toward a calibration point, slightly overestimating the proper VO(2)max when investigated in healthy participants. The SWT-based VO(2)max at low altitude is an effective indicator of AMS and helps to better identify susceptible individuals following acute high-altitude exposure, particularly by combining the RDW-CV at low altitude. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2200059900; https://www.chictr.org.cn/showproj.html?proj=170253
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spelling pubmed-103600142023-07-22 Smartwatch-Based Maximum Oxygen Consumption Measurement for Predicting Acute Mountain Sickness: Diagnostic Accuracy Evaluation Study Ye, Xiaowei Sun, Mengjia Yu, Shiyong Yang, Jie Liu, Zhen Lv, Hailin Wu, Boji He, Jingyu Wang, Xuhong Huang, Lan JMIR Mhealth Uhealth Original Paper BACKGROUND: Cardiorespiratory fitness plays an important role in coping with hypoxic stress at high altitudes. However, the association of cardiorespiratory fitness with the development of acute mountain sickness (AMS) has not yet been evaluated. Wearable technology devices provide a feasible assessment of cardiorespiratory fitness, which is quantifiable as maximum oxygen consumption (VO(2)max) and may contribute to AMS prediction. OBJECTIVE: We aimed to determine the validity of VO(2)max estimated by the smartwatch test (SWT), which can be self-administered, in order to overcome the limitations of clinical VO(2)max measurements. We also aimed to evaluate the performance of a VO(2)max-SWT–based model in predicting susceptibility to AMS. METHODS: Both SWT and cardiopulmonary exercise test (CPET) were performed for VO(2)max measurements in 46 healthy participants at low altitude (300 m) and in 41 of them at high altitude (3900 m). The characteristics of the red blood cells and hemoglobin levels in all the participants were analyzed by routine blood examination before the exercise tests. The Bland-Altman method was used for bias and precision assessment. Multivariate logistic regression was performed to analyze the correlation between AMS and the candidate variables. A receiver operating characteristic curve was used to evaluate the efficacy of VO(2)max in predicting AMS. RESULTS: VO(2)max decreased after acute high altitude exposure, as measured by CPET (25.20 [SD 6.46] vs 30.17 [SD 5.01] at low altitude; P<.001) and SWT (26.17 [SD 6.71] vs 31.28 [SD 5.17] at low altitude; P<.001). Both at low and high altitudes, VO(2)max was slightly overestimated by SWT but had considerable accuracy as the mean absolute percentage error (<7%) and mean absolute error (<2 mL·kg(–1)·min(–1)), with a relatively small bias compared with VO(2)max-CPET. Twenty of the 46 participants developed AMS at 3900 m, and their VO(2)max was significantly lower than that of those without AMS (CPET: 27.80 [SD 4.55] vs 32.00 [SD 4.64], respectively; P=.004; SWT: 28.00 [IQR 25.25-32.00] vs 32.00 [IQR 30.00-37.00], respectively; P=.001). VO(2)max-CPET, VO(2)max-SWT, and red blood cell distribution width-coefficient of variation (RDW-CV) were found to be independent predictors of AMS. To increase the prediction accuracy, we used combination models. The combination of VO(2)max-SWT and RDW-CV showed the largest area under the curve for all parameters and models, which increased the area under the curve from 0.785 for VO(2)max-SWT alone to 0.839. CONCLUSIONS: Our study demonstrates that the smartwatch device can be a feasible approach for estimating VO(2)max. In both low and high altitudes, VO(2)max-SWT showed a systematic bias toward a calibration point, slightly overestimating the proper VO(2)max when investigated in healthy participants. The SWT-based VO(2)max at low altitude is an effective indicator of AMS and helps to better identify susceptible individuals following acute high-altitude exposure, particularly by combining the RDW-CV at low altitude. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2200059900; https://www.chictr.org.cn/showproj.html?proj=170253 JMIR Publications 2023-07-06 /pmc/articles/PMC10360014/ /pubmed/37410528 http://dx.doi.org/10.2196/43340 Text en ©Xiaowei Ye, Mengjia Sun, Shiyong Yu, Jie Yang, Zhen Liu, Hailin Lv, Boji Wu, Jingyu He, Xuhong Wang, Lan Huang. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 06.07.2023. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on https://mhealth.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Ye, Xiaowei
Sun, Mengjia
Yu, Shiyong
Yang, Jie
Liu, Zhen
Lv, Hailin
Wu, Boji
He, Jingyu
Wang, Xuhong
Huang, Lan
Smartwatch-Based Maximum Oxygen Consumption Measurement for Predicting Acute Mountain Sickness: Diagnostic Accuracy Evaluation Study
title Smartwatch-Based Maximum Oxygen Consumption Measurement for Predicting Acute Mountain Sickness: Diagnostic Accuracy Evaluation Study
title_full Smartwatch-Based Maximum Oxygen Consumption Measurement for Predicting Acute Mountain Sickness: Diagnostic Accuracy Evaluation Study
title_fullStr Smartwatch-Based Maximum Oxygen Consumption Measurement for Predicting Acute Mountain Sickness: Diagnostic Accuracy Evaluation Study
title_full_unstemmed Smartwatch-Based Maximum Oxygen Consumption Measurement for Predicting Acute Mountain Sickness: Diagnostic Accuracy Evaluation Study
title_short Smartwatch-Based Maximum Oxygen Consumption Measurement for Predicting Acute Mountain Sickness: Diagnostic Accuracy Evaluation Study
title_sort smartwatch-based maximum oxygen consumption measurement for predicting acute mountain sickness: diagnostic accuracy evaluation study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10360014/
https://www.ncbi.nlm.nih.gov/pubmed/37410528
http://dx.doi.org/10.2196/43340
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