↓ Skip to main content

High Altitude Affects Nocturnal Non-linear Heart Rate Variability: PATCH-HA Study

Overview of attention for article published in Frontiers in Physiology, April 2018
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

Mentioned by

twitter
4 X users

Citations

dimensions_citation
15 Dimensions

Readers on

mendeley
34 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
High Altitude Affects Nocturnal Non-linear Heart Rate Variability: PATCH-HA Study
Published in
Frontiers in Physiology, April 2018
DOI 10.3389/fphys.2018.00390
Pubmed ID
Authors

Christopher J. Boos, Kyo Bye, Luke Sevier, Josh Bakker-Dyos, David R. Woods, Mark Sullivan, Tom Quinlan, Adrian Mellor

Abstract

Background: High altitude (HA) exposure can lead to changes in resting heart rate variability (HRV), which may be linked to acute mountain sickness (AMS) development. Compared with traditional HRV measures, non-linear HRV appears to offer incremental and prognostic data, yet its utility and relationship to AMS have been barely examined at HA. This study sought to examine this relationship at terrestrial HA. Methods: Sixteen healthy British military servicemen were studied at baseline (800 m, first night) and over eight consecutive nights, at a sleeping altitude of up to 3600 m. A disposable cardiac patch monitor was used, to record the nocturnal cardiac inter-beat interval data, over 1 h (0200-0300 h), for offline HRV assessment. Non-linear HRV measures included Sample entropy (SampEn), the short (α1, 4-12 beats) and long-term (α2, 13-64 beats) detrend fluctuation analysis slope and the correlation dimension (D2). The maximal rating of perceived exertion (RPE), during daily exercise, was assessed using the Borg 6-20 RPE scale. Results: All subjects completed the HA exposure. The average age of included subjects was 31.4 ± 8.1 years. HA led to a significant fall in SpO2 and increase in heart rate, LLS and RPE. There were no significant changes in the ECG-derived respiratory rate or in any of the time domain measures of HRV during sleep. The only notable changes in frequency domain measures of HRV were an increase in LF and fall in HFnu power at the highest altitude. Conversely, SampEn, SD1/SD2 and D2 all fell, whereas α1 and α2 increased (p < 0.05). RPE inversely correlated with SD1/SD2 (r = -0.31; p = 0.002), SampEn (r = -0.22; p = 0.03), HFnu (r = -0.27; p = 0.007) and positively correlated with LF (r = 0.24; p = 0.02), LF/HF (r = 0.24; p = 0.02), α1 (r = 0.32; p = 0.002) and α2 (r = 0.21; p = 0.04). AMS occurred in 7/16 subjects (43.8%) and was very mild in 85.7% of cases. HRV failed to predict AMS. Conclusion: Non-linear HRV is more sensitive to the effects of HA than time and frequency domain indices. HA leads to a compensatory decrease in nocturnal HRV and complexity, which is influenced by the RPE measured at the end of the previous day. HRV failed to predict AMS development.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 18%
Student > Master 5 15%
Student > Bachelor 3 9%
Student > Doctoral Student 3 9%
Professor 2 6%
Other 6 18%
Unknown 9 26%
Readers by discipline Count As %
Sports and Recreations 7 21%
Medicine and Dentistry 4 12%
Neuroscience 3 9%
Engineering 2 6%
Psychology 1 3%
Other 5 15%
Unknown 12 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 January 2023.
All research outputs
#13,438,659
of 23,202,641 outputs
Outputs from Frontiers in Physiology
#4,404
of 13,955 outputs
Outputs of similar age
#149,708
of 297,114 outputs
Outputs of similar age from Frontiers in Physiology
#178
of 491 outputs
Altmetric has tracked 23,202,641 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,955 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one has gotten more attention than average, scoring higher than 66% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 297,114 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 491 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.