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Heart Rate Variability: A Novel Modality for Diagnosing Neuropathic Pain after Spinal Cord Injury

Overview of attention for article published in Frontiers in Physiology, July 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

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Title
Heart Rate Variability: A Novel Modality for Diagnosing Neuropathic Pain after Spinal Cord Injury
Published in
Frontiers in Physiology, July 2017
DOI 10.3389/fphys.2017.00495
Pubmed ID
Authors

Jay Karri, Larry Zhang, Shengai Li, Yen-Ting Chen, Argyrios Stampas, Sheng Li

Abstract

Background: Heart rate variability (HRV), the physiological variance in the heart's R-R interval length, can be analyzed to produce various parameters reflective of one's autonomic balance. HRV analysis may be used to capture those autonomic aberrations associated with chronic neuropathic pain (NP) in spinal cord injury (SCI). This study assesses the capacity of HRV parameters to diagnose NP in an SCI cohort. Methods: An electrocardiogram (ECG) was collected at rest from able bodied participants (AB, n = 15), participants with SCI only (SCI-NP, n = 11), and those with SCI and NP (SCI+NP, n = 20). HRV parameters were analyzed using conventional time and frequency analysis. Results: At rest, there were no heart rate differences amongst groups. However, SCI+NP participants demonstrated lower overall HRV, as determined by the SDNN time domain parameter, compared to either AB (p < 0.01) or SCI-NP (p < 0.05) groups. Moreover, AB and SCI-NP participants were statistically comparable for all HRV time and frequency domain parameters. Additional analyses demonstrated no differences in HRV parameters between T4, above vs. T5, below SCI groups (for all parameters: p > 0.15) or between C8, above vs. T1, below SCI groups (p > 0.30). Conclusions: Participants with SCI and NP exhibit a lower overall HRV, which can be determined by HRV time domain parameter SDNN. HRV analysis is an innovative modality with the capacity for objective quantification of chronic NP in participants with SCI.

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The data shown below were collected from the profiles of 17 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 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 63 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 21%
Student > Ph. D. Student 7 11%
Other 5 8%
Student > Master 4 6%
Student > Doctoral Student 3 5%
Other 9 14%
Unknown 22 35%
Readers by discipline Count As %
Medicine and Dentistry 11 17%
Neuroscience 10 16%
Engineering 4 6%
Nursing and Health Professions 3 5%
Biochemistry, Genetics and Molecular Biology 2 3%
Other 7 11%
Unknown 26 41%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 21 August 2018.
All research outputs
#2,782,681
of 23,652,325 outputs
Outputs from Frontiers in Physiology
#1,471
of 14,330 outputs
Outputs of similar age
#52,319
of 315,775 outputs
Outputs of similar age from Frontiers in Physiology
#42
of 271 outputs
Altmetric has tracked 23,652,325 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 14,330 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one has done well, scoring higher than 89% 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 315,775 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 271 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.