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Can Heart Rate Variability Parameters Be a Biomarker for Predicting Motor Function Prognosis in Patients with Chronic Stroke?

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Health Information Science (HIS 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11837))

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Abstract

Stroke patients are often associated with lower levels of heart rate variability, suggesting that autonomic dysfunction is very common in stroke patients. Recent studies have shown that heart rate variability (HRV) is an early predictor of prognosis in patients with acute stroke, but the relationship between HRV and functional status in chronic rehabilitation patients is not clear. The purpose of this study was to investigate the clinical value of heart rate variability parameters in predicting motor function assessment in convalescent stroke patients. Methods: Sixty-four patients with strokes admitted to Beijing Bo’ai Hospital from October 2015 to October 2016 were enrolled. Dynamic electrocardiogram was used to continuously record the data of 24-h monitoring and analyze the heart rate variability, including time domain parameters [standard deviation of all NN intervals (SDNN, where NN intervals refer to the RR intervals of sinus beats), standard deviation of the 5-mins average NN intervals (SDANN), percentage of successive NN intervals greater than 50 ms (PNN50), root mean square of differences between adjacent RR intervals (RMSSD)], frequency domain parameters [high frequency component (HF), low frequency component (LF), very low frequency component (VLF), ratio of low frequency to high frequency component (LF/HF)] and heart rate variability triangular index. And by using the Barthel Index for Activities of Daily Living (ADLs) and the Fugl-Meyer Motor Assessment (FMA) simultaneously, the patients’ functional status was assessed. Results: The correlation analysis with related factors controlled showed that the HRV parameters were significantly correlated with the recovery of motor function [time domain indicators RR triangular index (r = 0.252; P = 0.05) and frequency domain indicator VLF (r = 0.302; P = 0.018)] and there was no relationship with HRV parameter and the improvement in activities of daily living of stroke patients in the chronic rehabilitation period. The monitoring of HRV-related parameters of stroke patients in their chronic rehabilitation period has a certain correlation with their motor function outcomes and daily living ability. Non-invasive monitoring of HRV may be an alternative method to judge the prognosis of stroke. In the future, further research is needed to verify the relevance of HRV to clinical outcomes.

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Acknowledgement

Our work was supported by Independent Scientific Research Project of China Rehabilitation Research Center (2016ZX—22). This work was also supported by NSFC(91646202), National Key R&D Program of China(2018YFB1404400,2018YFB1402700).

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Authors and Affiliations

  1. Beijing Boai Hospital, China Rehabilitation Research Center, Rehabilitation Medical College, Capital Medical University, Beijing, 100068, China

    Xiaoyu Zhang

  2. Beijing Tsinghua Changgung Hospital Medical Center, Tsinghua University, Beijing, 100084, China

    Xin Li

  3. Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Haoyang Liu

  4. Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Guigang Zhang

  5. Research Institute of Information Technology, Tsinghua University, Beijing, 100084, China

    Chunxiao Xing

Authors
  1. Xiaoyu Zhang
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  2. Xin Li
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  3. Haoyang Liu
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  4. Guigang Zhang
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  5. Chunxiao Xing
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Corresponding author

Correspondence to Xin Li .

Editor information

Editors and Affiliations

  1. Victoria University, Footscray, VIC, Australia

    Hua Wang

  2. Victoria University, Footscray, VIC, Australia

    Siuly Siuly

  3. Swinburne University of Technology, Hawthorn, VIC, Australia

    Rui Zhou

  4. Instituto de Salud Carlos III, Madrid, Spain

    Fernando Martin-Sanchez

  5. Victoria University, Footscray, VIC, Australia

    Yanchun Zhang

  6. Vrije University, Amsterdam, The Netherlands

    Zhisheng Huang

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Zhang, X., Li, X., Liu, H., Zhang, G., Xing, C. (2019). Can Heart Rate Variability Parameters Be a Biomarker for Predicting Motor Function Prognosis in Patients with Chronic Stroke?. In: Wang, H., Siuly, S., Zhou, R., Martin-Sanchez, F., Zhang, Y., Huang, Z. (eds) Health Information Science. HIS 2019. Lecture Notes in Computer Science(), vol 11837. Springer, Cham. https://doi.org/10.1007/978-3-030-32962-4_10

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  • DOI: https://doi.org/10.1007/978-3-030-32962-4_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-32961-7

  • Online ISBN: 978-3-030-32962-4

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