Heart Rate Variability Fraction-A New Reportable Measure of 24-Hour R-R Interval Variation

Background: The scatterplot of R‐R intervals has several unique features. Its numerical evaluation may produce a new useful index of global heart rate variability (HRV) from Holter recordings. Methods: Two‐hundred and ten middle‐aged healthy subjects were enrolled in this study. The study was repeat...

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Published inAnnals of noninvasive electrocardiology Vol. 10; no. 1; pp. 7 - 15
Main Authors Sosnowski, Maciej, Clark, Elaine, Latif, Shahid, Macfarlane, Peter W., Tendera, Michal
Format Journal Article
LanguageEnglish
Published 350 Main Street , Malden , MA 02148 , USA , and 9600 Garsington Road , Oxford OX4 2XG , UK Blackwell Publishing, Inc 01.01.2005
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ISSN1082-720X
1542-474X
DOI10.1111/j.1542-474X.2005.00579.x

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Abstract Background: The scatterplot of R‐R intervals has several unique features. Its numerical evaluation may produce a new useful index of global heart rate variability (HRV) from Holter recordings. Methods: Two‐hundred and ten middle‐aged healthy subjects were enrolled in this study. The study was repeated the next day in 165 subjects. Each subject had a 24‐hour ECG recording taken. Preprocessed data were transferred into a personal computer and the standard HRV time‐domain indices: standard deviation of total normal R‐R intervals (SDNN), standard deviation of averaged means of normal R‐R intervals over 5‐minute periods (SDANN), triangular index (TI), and pNN50 were determined. The scatterplot area (0.2–1.8 second) was divided into 256 boxes, each of 0.1‐second interval, and the number of paired R‐R intervals was counted. The heart rate variability fraction (HRVF) was calculated as the two highest counts divided by the number of total beats differing from the consecutive beat by <50 ms. The HRVF was obtained by subtracting this fraction from 1, and converting the result to a percentage. Results: The normal value of the HRVF was 52.7 ± 8.6%. The 2–98% range calculated from the normal probability plot was 35.1–70.3%. The HRVF varied significantly with gender (female 48.7 ± 8.4% vs male 53.6 ± 8.6%, P = 0.002). The HRVF correlated with RRI (r = 0.525) and showed a similar or better relationship with SDNN (0.851), SDANN (0.653), and TI (0.845) than did the standard HRV measures with each other. Bland‐Altman plot showed a good day‐by‐day reproducibility of the HRVF, with the intraclass correlation coefficient of 0.839 and a low relative standard error difference (1.8%). Conclusion: We introduced a new index of HRV, which is easy for computation, robust, reproducible, easy to understand, and may overcome the limitations that belong to the standard HRV measures. This index, named HRV fraction, by combining magnitude, distribution, and heart‐rate influences, might become a clinically useful index of global HRV.
AbstractList The scatterplot of R-R intervals has several unique features. Its numerical evaluation may produce a new useful index of global heart rate variability (HRV) from Holter recordings. Two-hundred and ten middle-aged healthy subjects were enrolled in this study. The study was repeated the next day in 165 subjects. Each subject had a 24-hour ECG recording taken. Preprocessed data were transferred into a personal computer and the standard HRV time-domain indices: standard deviation of total normal R-R intervals (SDNN), standard deviation of averaged means of normal R-R intervals over 5-minute periods (SDANN), triangular index (TI), and pNN50 were determined. The scatterplot area (0.2-1.8 second) was divided into 256 boxes, each of 0.1-second interval, and the number of paired R-R intervals was counted. The heart rate variability fraction (HRVF) was calculated as the two highest counts divided by the number of total beats differing from the consecutive beat by <50 ms. The HRVF was obtained by subtracting this fraction from 1, and converting the result to a percentage. The normal value of the HRVF was 52.7 +/- 8.6%. The 2-98% range calculated from the normal probability plot was 35.1-70.3%. The HRVF varied significantly with gender (female 48.7 +/- 8.4% vs male 53.6 +/- 8.6%, P = 0.002). The HRVF correlated with RRI (r = 0.525) and showed a similar or better relationship with SDNN (0.851), SDANN (0.653), and TI (0.845) than did the standard HRV measures with each other. Bland-Altman plot showed a good day-by-day reproducibility of the HRVF, with the intraclass correlation coefficient of 0.839 and a low relative standard error difference (1.8%). We introduced a new index of HRV, which is easy for computation, robust, reproducible, easy to understand, and may overcome the limitations that belong to the standard HRV measures. This index, named HRV fraction, by combining magnitude, distribution, and heart-rate influences, might become a clinically useful index of global HRV.
Background: The scatterplot of R‐R intervals has several unique features. Its numerical evaluation may produce a new useful index of global heart rate variability (HRV) from Holter recordings. Methods: Two‐hundred and ten middle‐aged healthy subjects were enrolled in this study. The study was repeated the next day in 165 subjects. Each subject had a 24‐hour ECG recording taken. Preprocessed data were transferred into a personal computer and the standard HRV time‐domain indices: standard deviation of total normal R‐R intervals (SDNN), standard deviation of averaged means of normal R‐R intervals over 5‐minute periods (SDANN), triangular index (TI), and pNN50 were determined. The scatterplot area (0.2–1.8 second) was divided into 256 boxes, each of 0.1‐second interval, and the number of paired R‐R intervals was counted. The heart rate variability fraction (HRVF) was calculated as the two highest counts divided by the number of total beats differing from the consecutive beat by <50 ms. The HRVF was obtained by subtracting this fraction from 1, and converting the result to a percentage. Results: The normal value of the HRVF was 52.7 ± 8.6%. The 2–98% range calculated from the normal probability plot was 35.1–70.3%. The HRVF varied significantly with gender (female 48.7 ± 8.4% vs male 53.6 ± 8.6%, P = 0.002). The HRVF correlated with RRI (r = 0.525) and showed a similar or better relationship with SDNN (0.851), SDANN (0.653), and TI (0.845) than did the standard HRV measures with each other. Bland‐Altman plot showed a good day‐by‐day reproducibility of the HRVF, with the intraclass correlation coefficient of 0.839 and a low relative standard error difference (1.8%). Conclusion: We introduced a new index of HRV, which is easy for computation, robust, reproducible, easy to understand, and may overcome the limitations that belong to the standard HRV measures. This index, named HRV fraction, by combining magnitude, distribution, and heart‐rate influences, might become a clinically useful index of global HRV.
The scatterplot of R-R intervals has several unique features. Its numerical evaluation may produce a new useful index of global heart rate variability (HRV) from Holter recordings.BACKGROUNDThe scatterplot of R-R intervals has several unique features. Its numerical evaluation may produce a new useful index of global heart rate variability (HRV) from Holter recordings.Two-hundred and ten middle-aged healthy subjects were enrolled in this study. The study was repeated the next day in 165 subjects. Each subject had a 24-hour ECG recording taken. Preprocessed data were transferred into a personal computer and the standard HRV time-domain indices: standard deviation of total normal R-R intervals (SDNN), standard deviation of averaged means of normal R-R intervals over 5-minute periods (SDANN), triangular index (TI), and pNN50 were determined. The scatterplot area (0.2-1.8 second) was divided into 256 boxes, each of 0.1-second interval, and the number of paired R-R intervals was counted. The heart rate variability fraction (HRVF) was calculated as the two highest counts divided by the number of total beats differing from the consecutive beat by <50 ms. The HRVF was obtained by subtracting this fraction from 1, and converting the result to a percentage.METHODSTwo-hundred and ten middle-aged healthy subjects were enrolled in this study. The study was repeated the next day in 165 subjects. Each subject had a 24-hour ECG recording taken. Preprocessed data were transferred into a personal computer and the standard HRV time-domain indices: standard deviation of total normal R-R intervals (SDNN), standard deviation of averaged means of normal R-R intervals over 5-minute periods (SDANN), triangular index (TI), and pNN50 were determined. The scatterplot area (0.2-1.8 second) was divided into 256 boxes, each of 0.1-second interval, and the number of paired R-R intervals was counted. The heart rate variability fraction (HRVF) was calculated as the two highest counts divided by the number of total beats differing from the consecutive beat by <50 ms. The HRVF was obtained by subtracting this fraction from 1, and converting the result to a percentage.The normal value of the HRVF was 52.7 +/- 8.6%. The 2-98% range calculated from the normal probability plot was 35.1-70.3%. The HRVF varied significantly with gender (female 48.7 +/- 8.4% vs male 53.6 +/- 8.6%, P = 0.002). The HRVF correlated with RRI (r = 0.525) and showed a similar or better relationship with SDNN (0.851), SDANN (0.653), and TI (0.845) than did the standard HRV measures with each other. Bland-Altman plot showed a good day-by-day reproducibility of the HRVF, with the intraclass correlation coefficient of 0.839 and a low relative standard error difference (1.8%).RESULTSThe normal value of the HRVF was 52.7 +/- 8.6%. The 2-98% range calculated from the normal probability plot was 35.1-70.3%. The HRVF varied significantly with gender (female 48.7 +/- 8.4% vs male 53.6 +/- 8.6%, P = 0.002). The HRVF correlated with RRI (r = 0.525) and showed a similar or better relationship with SDNN (0.851), SDANN (0.653), and TI (0.845) than did the standard HRV measures with each other. Bland-Altman plot showed a good day-by-day reproducibility of the HRVF, with the intraclass correlation coefficient of 0.839 and a low relative standard error difference (1.8%).We introduced a new index of HRV, which is easy for computation, robust, reproducible, easy to understand, and may overcome the limitations that belong to the standard HRV measures. This index, named HRV fraction, by combining magnitude, distribution, and heart-rate influences, might become a clinically useful index of global HRV.CONCLUSIONWe introduced a new index of HRV, which is easy for computation, robust, reproducible, easy to understand, and may overcome the limitations that belong to the standard HRV measures. This index, named HRV fraction, by combining magnitude, distribution, and heart-rate influences, might become a clinically useful index of global HRV.
Background: The scatterplot of R‐R intervals has several unique features. Its numerical evaluation may produce a new useful index of global heart rate variability (HRV) from Holter recordings. Methods: Two‐hundred and ten middle‐aged healthy subjects were enrolled in this study. The study was repeated the next day in 165 subjects. Each subject had a 24‐hour ECG recording taken. Preprocessed data were transferred into a personal computer and the standard HRV time‐domain indices: standard deviation of total normal R‐R intervals (SDNN), standard deviation of averaged means of normal R‐R intervals over 5‐minute periods (SDANN), triangular index (TI), and pNN50 were determined. The scatterplot area (0.2–1.8 second) was divided into 256 boxes, each of 0.1‐second interval, and the number of paired R‐R intervals was counted. The heart rate variability fraction (HRVF) was calculated as the two highest counts divided by the number of total beats differing from the consecutive beat by <50 ms. The HRVF was obtained by subtracting this fraction from 1, and converting the result to a percentage. Results: The normal value of the HRVF was 52.7 ± 8.6%. The 2–98% range calculated from the normal probability plot was 35.1–70.3%. The HRVF varied significantly with gender (female 48.7 ± 8.4% vs male 53.6 ± 8.6%, P = 0.002). The HRVF correlated with RRI (r = 0.525) and showed a similar or better relationship with SDNN (0.851), SDANN (0.653), and TI (0.845) than did the standard HRV measures with each other. Bland‐Altman plot showed a good day‐by‐day reproducibility of the HRVF, with the intraclass correlation coefficient of 0.839 and a low relative standard error difference (1.8%). Conclusion: We introduced a new index of HRV, which is easy for computation, robust, reproducible, easy to understand, and may overcome the limitations that belong to the standard HRV measures. This index, named HRV fraction, by combining magnitude, distribution, and heart‐rate influences, might become a clinically useful index of global HRV.
Author Latif, Shahid
Tendera, Michal
Sosnowski, Maciej
Clark, Elaine
Macfarlane, Peter W.
AuthorAffiliation 1 3rd Division of Cardiology, Silesian Medical School, Katowice, Poland
2 Division of Cardiovascular and Medical Sciences, Section of Cardiology, Royal Infirmary, University of Glasgow, Scotland, UK
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Kleiger RE, Miller JP, Bigger JT, et al. For the Multicenter Post-Infarction Research Group. Decreased heart rate variability and its association with increased mortality after acute myocardial infarction. Am J Cardiol 1987;59: 256-262.DOI: 10.1016/0002-9149(87)90795-8
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Malik M. Time-domain measurements of heart rate variability. Cardiac Electro-physiol Rev 1997;1: 329-334.DOI: 10.1023/A:1009912905325
Copie X, Hnatkova K, Staunton A, et al. Predictive power of increased heart rate versus depressed left ventricular ejection fraction and heart rate variability for risk stratification after myocardial infarction. Results of a two-year follow-up study. J Am Coll Cardiol 1996;27: 270-276.
Copie X, Le-Heuzey J-Y, Ilion M-C, et al. Correlation between time-domain measures of heart rate variability and scatterplots in postinfarction patients. Pacing Clin Electrophysiol 1996;19: 342-347.
Ewing DJ, Neilson JMM, Traus P. New method for assessing cardiac parasympathetic activity using 24-hour electrocardiograms. Br Heart J 1984;52: 396-402.
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Gilham BA. Application of scatterplots to Holter ECG data. J Electrocardiol 1994;26(Suppl):31-33.
Ponikowski P, Piepoli M, Amadi AA, et al. Reproducibility of heart rate variability measures in patients with chronic heart failure. Clin Sci 1996;91: 391-398.
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Snippet Background: The scatterplot of R‐R intervals has several unique features. Its numerical evaluation may produce a new useful index of global heart rate...
Background: The scatterplot of R‐R intervals has several unique features. Its numerical evaluation may produce a new useful index of global heart rate...
The scatterplot of R-R intervals has several unique features. Its numerical evaluation may produce a new useful index of global heart rate variability (HRV)...
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SourceType Open Access Repository
Aggregation Database
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StartPage 7
SubjectTerms ambulatory ECG monitoring
Analysis of Variance
Electrocardiography, Ambulatory
Female
healthy subjects
heart rate
Heart Rate - physiology
Humans
Linear Models
Male
Middle Aged
Original
Reference Values
reproducibility
Reproducibility of Results
scatterplot
Signal Processing, Computer-Assisted
Title Heart Rate Variability Fraction-A New Reportable Measure of 24-Hour R-R Interval Variation
URI https://api.istex.fr/ark:/67375/WNG-NC4GQW29-6/fulltext.pdf
https://onlinelibrary.wiley.com/doi/abs/10.1111%2Fj.1542-474X.2005.00579.x
https://www.ncbi.nlm.nih.gov/pubmed/15649232
https://www.proquest.com/docview/67367408
https://pubmed.ncbi.nlm.nih.gov/PMC6932143
Volume 10
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