Volume 19 Issue 5
May  2021
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Article Navigation >  Chinese Journal of General Practice  > 2021  >  19(5): 798-800,855
YU Fu-hai, SHEN Cai-jie, LU Cao-jie, ZHAO Fu, WANG Jian, ZHANG Dan. Related influencing factors and preventive measures of heart rate variability in patients uffer from chronic kidney disease[J]. Chinese Journal of General Practice, 2021, 19(5): 798-800,855. doi: 10.16766/j.cnki.issn.1674-4152.001920
Citation: YU Fu-hai, SHEN Cai-jie, LU Cao-jie, ZHAO Fu, WANG Jian, ZHANG Dan. Related influencing factors and preventive measures of heart rate variability in patients uffer from chronic kidney disease[J]. Chinese Journal of General Practice, 2021, 19(5): 798-800,855. doi: 10.16766/j.cnki.issn.1674-4152.001920
shu

Related influencing factors and preventive measures of heart rate variability in patients uffer from chronic kidney disease

doi: 10.16766/j.cnki.issn.1674-4152.001920
  • 1.

    Department of Nephrology, People's Hospital of Fenghua District, Ningbo, Zhejiang 315500, China

Funds:

 2019KY642

  • Received Date: 2020-06-02
    Available Online: 2022-02-16
    Abstract
  •   Objective  To analyse changes and influencing factors of heart rate variability (HRV) in patients with chronic kidney disease (CKD) for conducting targeted intervention.  Methods  A total of 138 CKD patients who were admitted to the First Hospital of Ningbo from March 2017 and March 2019 were enrolled as study objects. MARS Holter analysis software and Seer Light ECG box were used to monitor patient' HRV time-domain analysis parameters for 24 h [standard deviation of 5-minute average NN intervals (SDANN), standard deviation of NN intervals (SDNN), the percentage of NN50 in the total number of normal-to-normal intervals (pNN50), square root of the mean of the squared differences between adjacent normal RR (rMSSD)] were detected. The multivariate linear stepwise regression analysis was applied to analyse their influencing factors.  Results  The results of multiple linear stepwise regression showed that interleukin 6 (IL-6) was an influencing factor of SDANN (t=2.243, P=0.029). Haemoglobin (Hb), C-reactive protein (CRP), IL-6, brachial and ankle pulse wave velocity (baPWV) were influencing factors of SDNN (t=2.084, 3.515, 4.594, 5.523, all P < 0.05). Blood phosphorus and baPWV were the influencing factors of pNN50 (t=2.021, 2.536, all P < 0.05). Hb, IL-6 and serum potassium were the influencing factors of Root Mean Square of the Successive Differences (rMSSD, t=2.156, 4.417, 2.642, all P < 0.05).  Conclusion  CKD patients are accompanied with decrease of HRV time-domain analysis parameters, which is related to anaemia, micro-inflammation status, electrolyte imbalance and arteriosclerosis. Clinically, intervention can be conducted aiming at the above risk factors.

     

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