A procedure to correct the effect of heart rate on heart rate variability indices: description and assessment

Estévez‐Báez, Mario; Machado, Calixto; Leisman, Gerry; Brown-Martínez, Martha; Jas-García, Javier Denis; Montes-Brown, Julio; Machado-García, Andrés; Carricarte-Naranjo, Claudia

doi:10.1515/ijdhd-2015-0014

Cited by 8 publications

(5 citation statements)

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“…This procedure, adapted to our particular analysis, seems effective and recommendable, and allowed a probabilistic means to assess the real significant differences of HRV indices between groups, making possible a more realistic clinical and physiological assessment. Second, the distortion of HRV indices produced by the mathematical relationship between the heart rate and HRV indices described in different reports [40,41,[94][95][96][97][98] can modify the predicting potentialities of HRV indices, although it has only been acknowledged by few authors that have studied the potentialities of HRV indices for predicting outcomes in patients with brain injury [37]. In the current study those deleterious influences were avoided correspondingly.…”

Section: Discussionmentioning

confidence: 91%

Autonomic impairment of patients in coma with different Glasgow coma score assessed with heart rate variability

et al. 2019

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Primary objective: To assess and compare the functional state of the autonomic nervous system in healthy individuals with patients in coma using measures of heart rate variability (HRV), and to evaluate its efficiency in predicting mortality. Research design: Retrospective group comparison study of patients in coma, classified into two subgroups, according to their Glasgow coma score, with a healthy control group. Methods and procedures: HRV indices were calculated from 7 minutes of free of artifacts electrocardiograms using the Hilbert-Huang method in the spectral range 0.02-0.6 Hz. A special procedure was applied to avoid the effect of confounding factors. Stepwise multiple regression logistic analysis (SMLRA), followed by ROC curve analysis were applied to evaluate predictions. Results: Progressive reduction of HRV associated with deepening of coma was confirmed and a mortality score model including three spectral HRV indices: absolute power values of the very low, low frequency, and the power in normalized units of the very high frequency bands (0.4-0.6 Hz). The SMLRA model showed sensitivity of 95.65%, specificity of 95.83%, positive predictive value of 95.65%, and overall efficiency of 95.74%. Conclusions: HRV is a reliable method to assess the integrity of the neural control of the caudal brainstem centres upon the heart, of patients in coma, and predict mortality.

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Section: Discussionmentioning

confidence: 91%

Autonomic impairment of patients in coma with different Glasgow coma score assessed with heart rate variability

et al. 2019

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“…The mathematical determination is caused by the non-linear (inverse) relationship between R-R intervals and HRs—consequently, the same changes of HR cause much higher fluctuations of R-R intervals for the slow average HR than for the fast one (Sacha and Pluta, 2008 ; Sacha, 2013 , 2014a , b , c ; Sacha et al, 2013a , b , c , 2014 ; Billman et al, 2015 ). Recently, several methods of the HRV correction for HR have been proposed (Sacha et al, 2013a , c ; Monfredi et al, 2014 ; Estévez-Báez et al, 2015 ) and the study employing one of them has demonstrated a significant improvement in the reproducibility of corrected HRV (Sacha et al, 2013c ). Moreover, other studies have shown that a complete removal of the HR impact on HRV may increase the HRV prognostic power for non-cardiac death in patients after myocardial infarction (Sacha et al, 2013b , 2014 ).…”

Section: Discussionmentioning

confidence: 99%

Heart Rate and Respiratory Rate Influence on Heart Rate Variability Repeatability: Effects of the Correction for the Prevailing Heart Rate

et al. 2016

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Background: Since heart rate variability (HRV) is associated with average heart rate (HR) and respiratory rate (RespRate), alterations in these parameters may impose changes in HRV. Hence the repeatability of HRV measurements may be affected by differences in HR and RespRate. The study aimed to evaluate HRV repeatability and its association with changes in HR and RespRate.Methods: Forty healthy volunteers underwent two ECG examinations 7 days apart. Standard HRV indices were calculated from 5-min ECG recordings. The ECG-derived respiration signal was estimated to assess RespRate. To investigate HR impact on HRV, HRV parameters were corrected for prevailing HR.Results: Differences in HRV parameters between the measurements were associated with the changes in HR and RespRate. However, in multiple regression analysis only HR alteration proved to be independent determinant of the HRV differences—every change in HR by 1 bpm changed HRV values by 16.5% on average. After overall removal of HR impact on HRV, coefficients of variation of the HRV parameters significantly dropped on average by 26.8% (p < 0.001), i.e., by the same extent HRV reproducibility improved. Additionally, the HRV correction for HR decreased association between RespRate and HRV.Conclusions: In stable conditions, HR but not RespRate is the most powerful factor determining HRV reproducibility and even a minimal change of HR may considerably alter HRV. However, the removal of HR impact may significantly improve HRV repeatability. The association between HRV and RespRate seems to be, at least in part, HR dependent.

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“…Consequently, a comparison of HRV corresponding to different HR may be biased ( Sacha and Grzeszczak, 2001 ; Nieminen et al, 2007 ; Sacha and Pluta, 2008 ). Mathematical methods removing the HRV dependence on HR (i.e., the HRV correction for prevailing HR) ( Hayano et al, 1990 , 1991 ; Sacha and Grzeszczak, 2001 ; Sacha and Pluta, 2008 ; Sacha et al, 2013b , c ; Monfredi et al, 2014 ; Estévez-Báez et al, 2015 ; van Roon et al, 2016 ) should allow to draw objective conclusions when comparing HRV associated with various HR ( Sacha, 2013 , 2014a , b , c ; Monfredi et al, 2014 ; Billman et al, 2015 ). So far, only one study dealing with normal ranges of HRV employed the HRV correction for HR, however, authors presented normal values only for two time domain HRV markers derived from 10-s ECGs ( van den Berg et al, 2018 ).…”

Section: Introductionmentioning

confidence: 99%

Normative Values for Heart Rate Variability Parameters in School-Aged Children: Simple Approach Considering Differences in Average Heart Rate

et al. 2018

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Background: Heart rate variability (HRV) analysis is a clinical tool frequently used to characterize cardiac autonomic status. The aim of this study was to establish normative values for short-term HRV parameters by considering their main determinants in school-aged children.Methods: Five-minute electrocardiograms were taken from 312 non-athlete children (153 boys) at age of 6 to 13 years for computation of conventional time- and frequency-domain HRV parameters. Heart rate (HR), respiratory rate, age, body mass index, and sex were considered as their potential determinants. Multiple regression analysis revealed that HR was the principal predictor of all standard HRV indices. To develop their universal normative limits, standard HRV parameters were corrected for prevailing HR.Results: The HRV correction for HR yielded the parameters which became independent on both sex and HR, and only poorly dependent on age (with small effect size). Normal ranges were calculated for both time- and frequency-domain indices (the latter computed with either fast Fourier transform and autoregressive method). To facilitate recalculation of standard HRV parameters into corrected ones, a calculator was created and attached as a Supplementary Material that can be downloaded and used for both research and clinical purposes.Conclusion: This study provides HRV normative values for school-aged children which have been developed independently of their major determinants. The calculator accessible in the Supplementary Material can considerably simplify determination if HRV parameters accommodate within normal limits.

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A procedure to correct the effect of heart rate on heart rate variability indices: description and assessment

Cited by 8 publications

References 50 publications

Autonomic impairment of patients in coma with different Glasgow coma score assessed with heart rate variability

Autonomic impairment of patients in coma with different Glasgow coma score assessed with heart rate variability

Heart Rate and Respiratory Rate Influence on Heart Rate Variability Repeatability: Effects of the Correction for the Prevailing Heart Rate

Normative Values for Heart Rate Variability Parameters in School-Aged Children: Simple Approach Considering Differences in Average Heart Rate

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