Adrian Mellor1,2,3, Josh Bakker-Dyos1, John OʼHara3, David Richard Woods1,3,4,5, David A Holdsworth1,6, Christopher J Boos3,7,8. 1. Defence Medical Services, Lichfield, United Kingdom. 2. Department of Anaesthesia, James Cook University Hospital, Middlesbrough, United Kingdom. 3. Research Institute for Sport, Physical Activity and Leisure, Leeds Beckett University, Leeds, United Kingdom. 4. Department of Endocrine Medicine, Northumbria and Newcastle NHS Trusts, Wansbeck General and Royal Victoria Infirmary, Newcastle, United Kingdom. 5. Academic Department of Medicine, University of Newcastle, Newcastle upon Tyne, United Kingdom. 6. Department of Physiology, University of Oxford, Oxford, United Kingdom. 7. Department of Cardiology, Poole Hospital NHS Foundation Trust, Poole, United Kingdom. 8. Department of Postgraduate Medical Education, Bournemouth University, Bournemouth, United Kingdom.
Abstract
INTRODUCTION: The autonomic system and sympathetic activation appears integral in the pathogenesis of acute mountain sickness (AMS) at high altitude (HA), yet a link between heart rate variability (HRV) and AMS has not been convincingly shown. In this study we investigated the utility of the smartphone-derived HRV score to predict and diagnose AMS at HA. METHODS: Twenty-one healthy adults were investigated at baseline at 1400 m and over 10 days during a trek to 5140 m. HRV was recorded using the ithlete HRV device. RESULTS: Acute mountain sickness occurred in 11 subjects (52.4%) at >2650 m. HRV inversely correlated with AMS Scores (r = -0.26; 95% CI, -0.38 to -0.13: P < 0.001). HRV significantly fell at 3700, 4100, and 5140 m versus low altitude. HRV scores were lower in those with both mild (69.7 ± 14.0) and severe AMS (67.1 ± 13.1) versus those without AMS (77.5 ± 13.1; effect size n = 0.043: P = 0.007). The HRV score was weakly predictive of severe AMS (AUC 0.74; 95% CI, 0.58-0.89: P = 0.006). The change (delta) in the HRV Score (compared with baseline at 1400 m) was a moderate diagnostic marker of severe AMS (AUC 0.80; 95% CI, 0.70-0.90; P = 0.0004). A fall in the HRV score of >5 had a sensitivity of 83% and specificity of 60% to identify severe AMS (likelihood ratio 1.9). Baseline HRV at 1400 m was not predictive of either AMS at higher altitudes. CONCLUSIONS: The ithlete HRV score can be used to help in the identification of severe AMS; however, a baseline score is not predictive of future AMS development at HA.
INTRODUCTION: The autonomic system and sympathetic activation appears integral in the pathogenesis of acute mountain sickness (AMS) at high altitude (HA), yet a link between heart rate variability (HRV) and AMS has not been convincingly shown. In this study we investigated the utility of the smartphone-derived HRV score to predict and diagnose AMS at HA. METHODS: Twenty-one healthy adults were investigated at baseline at 1400 m and over 10 days during a trek to 5140 m. HRV was recorded using the ithlete HRV device. RESULTS: Acute mountain sickness occurred in 11 subjects (52.4%) at >2650 m. HRV inversely correlated with AMS Scores (r = -0.26; 95% CI, -0.38 to -0.13: P < 0.001). HRV significantly fell at 3700, 4100, and 5140 m versus low altitude. HRV scores were lower in those with both mild (69.7 ± 14.0) and severe AMS (67.1 ± 13.1) versus those without AMS (77.5 ± 13.1; effect size n = 0.043: P = 0.007). The HRV score was weakly predictive of severe AMS (AUC 0.74; 95% CI, 0.58-0.89: P = 0.006). The change (delta) in the HRV Score (compared with baseline at 1400 m) was a moderate diagnostic marker of severe AMS (AUC 0.80; 95% CI, 0.70-0.90; P = 0.0004). A fall in the HRV score of >5 had a sensitivity of 83% and specificity of 60% to identify severe AMS (likelihood ratio 1.9). Baseline HRV at 1400 m was not predictive of either AMS at higher altitudes. CONCLUSIONS: The ithlete HRV score can be used to help in the identification of severe AMS; however, a baseline score is not predictive of future AMS development at HA.
Authors: Ka Hou Christien Li; Francesca Anne White; Gary Tse; Timothy Tipoe; Tong Liu; Martin Cs Wong; Aaron Jesuthasan; Adrian Baranchuk; Bryan P Yan Journal: JMIR Mhealth Uhealth Date: 2019-02-15 Impact factor: 4.773
Authors: Christopher J Boos; Kyo Bye; Luke Sevier; Josh Bakker-Dyos; David R Woods; Mark Sullivan; Tom Quinlan; Adrian Mellor Journal: Front Physiol Date: 2018-04-16 Impact factor: 4.566