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 in | Annals of noninvasive electrocardiology Vol. 10; no. 1; pp. 7 - 15 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
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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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ISSN | 1082-720X 1542-474X |
DOI | 10.1111/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. |
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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 |
AuthorAffiliation_xml | – name: 1 3rd Division of Cardiology, Silesian Medical School, Katowice, Poland – name: 2 Division of Cardiovascular and Medical Sciences, Section of Cardiology, Royal Infirmary, University of Glasgow, Scotland, UK |
Author_xml | – sequence: 1 givenname: Maciej surname: Sosnowski fullname: Sosnowski, Maciej organization: 3rd Division of Cardiology, Silesian Medical School, Katowice, Poland – sequence: 2 givenname: Elaine surname: Clark fullname: Clark, Elaine organization: Division of Cardiovascular and Medical Sciences, Section of Cardiology, Royal Infirmary, University of Glasgow, Scotland, UK – sequence: 3 givenname: Shahid surname: Latif fullname: Latif, Shahid organization: Division of Cardiovascular and Medical Sciences, Section of Cardiology, Royal Infirmary, University of Glasgow, Scotland, UK – sequence: 4 givenname: Peter W. surname: Macfarlane fullname: Macfarlane, Peter W. organization: Division of Cardiovascular and Medical Sciences, Section of Cardiology, Royal Infirmary, University of Glasgow, Scotland, UK – sequence: 5 givenname: Michal surname: Tendera fullname: Tendera, Michal organization: 3rd Division of Cardiology, Silesian Medical School, Katowice, Poland |
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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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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 |
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