Mirja Peltola

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Eric S . Kim (UBC)

University of British Columbia

Todor Cooklev

Purdue University Fort Wayne

Lagouge Tartibu

University of Johannesburg, South Africa

Hamid Soori

Shahid Beheshti University of Medical Sciences

Helen Gurgel

Universidade de Brasília - UnB

Olukemi Amodu

University of Ibadan Nigeria

Henry Pfister

Duke University

J. Chamberland

Texas A&M University

Colleen Myles (formerly Hiner)

Texas State University

sandhya supalkar

University of Mumbai

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Role of editing of R–R intervals in the analysis of heart

Respiratory sinus arrhythmia as a predictor of sudden cardiac death after myocardial infarction

Annals of Medicine, 2008

Measurement of high-frequency (HF) spectral power of heart rate (HR) variability has not been abl... more Measurement of high-frequency (HF) spectral power of heart rate (HR) variability has not been able to identify the patients at risk of sudden cardiac death (SCD) despite the experimental evidence of protective role of vagal activity for fatal arrhythmias. We developed a novel respiratory sinus arrhythmia (RSA) analysis method and tested its ability to predict SCD after an acute myocardial infarction. The RSA analysis method was developed in 13 subjects from simultaneous recordings of respiration and R-R intervals. An adaptive threshold was computed based on the zero-phase forward and reverse digital filtering in the analysis of RSA. With this method, only respiration-related R-R interval fluctuations are included. The prognostic power of RSA, analyzed from 24-hour electrocardiographic recordings, was subsequently assessed in a large postinfarction population including 1631 patients with mean follow-up of 40 +/- 17 months. Depressed RSA was a strong predictor of SCD (hazard ratio 7.4; 95% CI 3.6-15.1; P 0.0001) but only a weak predictor of non-SCD. The RSA index remained an independent predictor of SCD after adjustments for ejection fraction and other clinical risk variables (RR 4.7; 95% CI 2.28-9.85). Reduced respiratory-related HR dynamics, detected by RSA index, are a specific marker of an increased risk of SCD among postinfarction patients.

Heart rate recovery after exercise as a predictor of mortality among survivors of acute myocardial infarction

The American Journal of Cardiology, 2003

no-reflow phenomenon" using technetium-99m macroaggregated albumin scintigraphy in patients with ... more

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Ectopic Beats in Heart Rate Variability Analysis: Effects of Editing on Time and Frequency Domain Measures

Annals of Noninvasive Electrocardiology, 2001

Background: Various methods can be used to edit biological and technical artefacts in heart rate ... more Background: Various methods can be used to edit biological and technical artefacts in heart rate variability (HRV), but there is relatively little information on the effects of such editing methods on HRV. Methods: The effects of editing on HRV analysis were studied using R-R interval data of 10 healthy subjects and 10 patients with a previous myocardial infarction (MI). R-R interval tachograms of verified sinus beats were analyzed from short-term (-5 min) and long-term (-24 hours) recordings by eliminating different amounts of real R-R intervals. Three editing methods were applied to these segments: (1) interpolation of degree zero, (2) interpolation of degree one, and (3) deletion without replacement. Results: In time domain analysis of short-term data, the standard deviation of normal-to-normal intervals (SDANN) was least affected by editing, and 30%-50% of the data could be edited by all the three methods without a significant error (< 5%). In the frequency domain analysis, the method of editing resulted in remarkably different changes and errors for both the high-frequency (HF) and the low-frequency (LF) spectral components. The editing methods also yielded in different results in healthy subjects and AM1 patients. In 24-hour HRV analysis, up to 50% could be edited by all methods without an error larger than 5% in the analysis of the standard deviation of normal to normal intervals (SDNN). Both interpolation methods also performed well in the editing of the long-term power spectral components for 24-hour data, but with the deletion method, only 5% of the data could be edited without a significant error. Conclusions: The amount and type of editing R-R interval data have remarkably different effects on various HRV indices. There is no universal method for editing ectopic beats that could be used heart rate variability; editing; deletion; interpolation; R-R intervals in both the time-domain and the frequency-domain analysis of HRV.

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Effects and Significance of Premature Beats on Fractal Correlation Properties of R-R Interval Dynamics

Annals of Noninvasive Electrocardiology, 2004

Background: Premature beats (PBs) have been considered as artifacts producing a bias in the tradi... more Background: Premature beats (PBs) have been considered as artifacts producing a bias in the traditional analysis of heart rate (HR) variability. We assessed the effects and significance of PBs on fractal scaling exponents in healthy subjects and patients with a recent myocardial infarction (AMI). Methods: Artificial PBs were first generated into a time series of pure sinus beats in 20 healthy subjects and 20 post-AMI patients. Thereafter, a case-control approach was used to compare the prognostic significance of edited and nonedited fractal scaling exponents in a random elderly population and in a post-AMI population. Detrended fluctuation analysis (DFA) was used to measure the short-term (α 1) and long-term (α 2) fractal scaling exponents. Results: Artificial PBs caused a more pronounced reduction of α 1 value among the post-AMI patients than the healthy subjects, for example, if >0.25% of the beats were premature a >25% decrease in the α 1 was observed in post-AMI patients, but 4% of the premature beats were needed to cause a 25% reduction in α 1 in healthy subjects. Both edited (1.01 ± 0.31 vs 1.19 ± 0.27, P < 0.01) and unedited α 1 (0.71 ± 0.33 vs 0.89 ± 0.36, P < 0.05) differed between the patients who died (n = 42) and those who survived (n = 42) after an AMI. In the general population, only unedited α 1 differed significantly between survivors and those who died (0.96 ± 0.19 vs 0.83 ± 0.27, P < 0.05). Conclusions: Unedited premature beats result in an increase in the randomness of short-term R-R interval dynamics, particularly in post-AMI patients. Premature beats must not necessarily be edited when fractal analysis is used for risk stratification.

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Analysis of heart rate variability from 24-hour ambulatory electrocardiographic recordings. Significance of preprocessing of R-R interval time series

Heart rate variability (HRV) is used in the assessment of cardiovascular health. However, often c... more Heart rate variability (HRV) is used in the assessment of cardiovascular health. However, often contradictory results have impeded the efficient use of HRV in clinical practice. HRV signals can contain artifacts leading to errors in the interpretation of HRV results. Various methods have been used for artifact editing, but there is relatively little information on how the actual editing can influence the HRV measures. The main aim of this thesis was to improve the reliability of HRV analysis by concentrating on the HRV signal preprocessing methods. The effects of three editing methods on the HRV of short (512 R-R) and long-term (24-hour) R-R interval data were studied with non-edited and edited data from healthy subjects (n=10) and patients with acute myocardial infarction (AMI) (n=10). The effects of ectopic beats on short (α 1 ) and long-term (α 2 ) fractal scaling exponents were studied by inserting artificial ectopic beats into the HRV signals of 20 healthy subjects and 20 AMI patients. The prognostic significance of edited and non-edited α 1 and α 2 was studied in random elderly (n=84) and post-AMI (n=84) populations. A new method to quantify respiratory sinus arrhythmia (RSA) was developed based on the HRV signals of 13 healthy subjects. A new measure, the RSA index, was defined to evaluate the risk to sudden cardiac death (SCD) in 1631 AMI patients. Lastly, a new algorithm was developed in order to edit heart rate (HR) turbulence occurring immediately after a ventricular premature beat (VPB). The effects of HR turbulence editing on the HRV analysis were studied in 267 AMI patients. Editing had distinct effects on the HRV analysis depending on the editing method and data type. Deletion editing was found to be unsuitable for the HRV spectrum analysis. There was no universal editing method for the time and frequency domain HRV analyses. Unedited ectopic beats increased the randomness of short-term R-R interval dynamics, especially in AMI patients. However, unedited α 1 differed significantly between survivors and those who died during the follow-up. Ectopic beats do not necessarily need to be edited if fractal analysis is used in the risk evaluation. A depressed RSA index was found to be a strong predictor of SCD but a weak predictor of non-SCD in AMI patients. Editing of HR turbulence affected differently the various HRV measures. ULF and VLF components were most clearly influenced by HR turbulence removal. The amount of VBPs had an important impact on the results. When the VBPs/hour were >50, ULF and VLF were >30% lower after turbulence removal. The results of this thesis highlight the importance of editing the erroneous or irrelevant R-R interval oscillation in an HRV analysis. The careful choice of preprocessing method is essential if one wishes to obtain reliable HRV analyses for clinical purposes.

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Role of editing of R-R intervals in the analysis of heart rate variability

Frontiers in physiology, 2012

This paper reviews the methods used for editing of the R-R interval time series and how this edit... more This paper reviews the methods used for editing of the R-R interval time series and how this editing can influence the results of heart rate (HR) variability analyses. Measurement of HR variability from short and long-term electrocardiographic (ECG) recordings is a non-invasive method for evaluating cardiac autonomic regulation. HR variability provides information about the sympathetic-parasympathetic autonomic balance. One important clinical application is the measurement of HR variability in patients suffering from acute myocardial infarction. However, HR variability signals extracted from R-R interval time series from ambulatory ECG recordings often contain different amounts of artifact. These false beats can be either of physiological or technical origin. For instance, technical artifact may result from poorly fastened electrodes or be due to motion of the subject. Ectopic beats and atrial fibrillation are examples of physiological artifact. Since ectopic and other false beats a...

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Heart Rate Variability Density Analysis (Dyx) and Prediction of Long-Term Mortality after Acute Myocardial Infarction

Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc, Jan 11, 2015

The density HRV parameter Dyx is a new heart rate variability (HRV) measure based on multipole an... more The density HRV parameter Dyx is a new heart rate variability (HRV) measure based on multipole analysis of the Poincaré plot obtained from RR interval time series, deriving information from both the time and frequency domain. Preliminary results have suggested that the parameter may provide new predictive information on mortality in survivors of acute myocardial infarction (MI). This study compares the prognostic significance of Dyx to that of traditional linear and nonlinear measures of HRV. In the Nordic ICD pilot study, patients with an acute MI were screened with 2D echocardiography and 24-hour Holter recordings. The study was designed to assess the power of several HRV measures to predict mortality. Dyx was tested in a subset of 206 consecutive Danish patients with analysable Holter recordings. After a median follow-up of 8.5 years 70 patients had died. Of all traditional and multipole HRV parameters, reduced Dyx was the most powerful predictor of all-cause mortality (HR 2.4; C...

Respiratory sinus arrhythmia in Chagas disease

Journal of Electrocardiology, 2013

ABSTRACT We applied the respiratory sinus arrhythmia (RSA) quantification algorithm to 24-hour EC... more ABSTRACT We applied the respiratory sinus arrhythmia (RSA) quantification algorithm to 24-hour ECG recordings of Chagas disease (ChD) patients with (G1, n=148) and without left ventricular dysfunction (LVD) (G2, n=33), and in control subjects (G0, n=28). Both ChD groups displayed a reduced RSA index; G1=299 (144-812); G2=335 (162-667), p=0.011, which was correlated with vagal indexes of heart rate variability analysis. RSA index is a marker of vagal modulation in ChD patients.

AB28-4

by Mirja Peltola and Tapio Seppanen

Heart Rhythm, 2006

Determinants and Prognostic Value of Cardiovascular Autonomic Function in Coronary Artery Disease Patients With and Without Type 2 Diabetes

Diabetes Care, 2014

OBJECTIVE Cardiovascular autonomic dysfunction is a common finding among patients with coronary a... more OBJECTIVE Cardiovascular autonomic dysfunction is a common finding among patients with coronary artery disease (CAD) and type 2 diabetes (T2D). The reasons and prognostic value of autonomic dysfunction in CAD patients with T2D are not well known. RESEARCH DESIGN AND METHODS We examined the association between heart rate recovery (HRR), 24-h heart rate (HR) variability (SD of normal R-R interval [SDNN]), and HR turbulence (HRT), and echocardiographic parameters, metabolic, inflammatory, and coronary risk variables, exercise capacity, and the presence of T2D among 1,060 patients with CAD (mean age 67 ± 8 years; 69% males; 50% patients with T2D). Second, we investigated how autonomic function predicts a composite end point of cardiovascular death, acute coronary event, stroke, and hospitalization for heart failure during a 2-year follow-up. RESULTS In multiple linear regression model, exercise capacity was a strong predictor of HRR (R = 0.34, P &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt; 0.001), SDNN (R = 0.33, P &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt; 0.001), and HRT (R = 0.13, P = 0.001). In univariate analyses, a composite end point was predicted by reduced HRR (hazard ratio 1.7 [95% CI 1.1-2.6]; P = 0.020), reduced SDNN (2.0 [95% CI 1.2-3.1]; P = 0.005), and blunted HRT (2.1 [1.3-3.4]; P = 0.003) only in patients with T2D. After multivariate adjustment, none of the autonomic markers predicted the end point, but high-sensitivity C-reactive protein (hs-CRP) remained an independent predictor. CONCLUSIONS Cardiovascular autonomic function in CAD patients is associated with several variables, including exercise capacity. Autonomic dysfunction predicts short-term cardiovascular events among CAD patients with T2D, but it is not as strong an independent predictor as hs-CRP.

Effects of Postectopic Heart Rate Turbulence on Measures of Heart Rate Variability in Patients after an Acute Myocardial Infarction

Annals of Noninvasive Electrocardiology, 2011

Heart rate (HR) turbulence lasting up to 15 beats after ventricular premature beats (VPBs) may ha... more Heart rate (HR) turbulence lasting up to 15 beats after ventricular premature beats (VPBs) may have profound effects on HR variability measures. Aim of this study was to examine the effects of HR turbulence on HR variability measures. We developed an algorithm, which deletes 15 consecutive RR intervals after VPBs and examined the effects of the HR turbulence removal on the HR variability measures in patients after an acute myocardial infarction (AMI). Two hundred and sixty seven patients with left ventricular ejection fraction (LVEF) ≤ 0.40 and occurrence of VPBs were included in the study. Differences (%) between original HR data and HR turbulence edited data were compared. HR turbulence editing had variable effects on different HR variability indexes. Ultra low (ULF) and very low frequency (VLF) spectral components were mostly affected by the HR turbulence removal. Both ULF and VLF decreased significantly both at baseline Holter recordings (ULF: P = 0.006, VLF: P = 0.031) and at 6 weeks from AMI (ULF: P &amp;amp;amp;amp;amp;amp;amp;amp;lt; 0.001, VLF: P = 0.001). The number of VPBs had a marked influence on results, e.g., when the number of VPBs exceeded the highest decile (≈50 VPBs/hour), the ULF and VLF spectral component were &amp;amp;amp;amp;amp;amp;amp;amp;gt;30% lower after removal of turbulence. In addition, the prediction of arrhythmic events by ULF component improved after turbulence removal (AUC: 0.69 -&amp;amp;amp;amp;amp;amp;amp;amp;gt;0.74). HR turbulence affects HR variability measures, especially the ULF and VFL spectral components. Editing of the HR turbulence should be considered when HR variability is measured from Holter recordings.

Effects and Significance of Premature Beats on Fractal Correlation Properties of R-R Interval Dynamics

by Mirja Peltola and Tapio Seppanen

Annals of Noninvasive Electrocardiology, 2004

Premature beats (PBs) have been considered as artifacts producing a bias in the traditional analy... more Premature beats (PBs) have been considered as artifacts producing a bias in the traditional analysis of heart rate (HR) variability. We assessed the effects and significance of PBs on fractal scaling exponents in healthy subjects and patients with a recent myocardial infarction (AMI). Artificial PBs were first generated into a time series of pure sinus beats in 20 healthy subjects and 20 post-AMI patients. Thereafter, a case-control approach was used to compare the prognostic significance of edited and nonedited fractal scaling exponents in a random elderly population and in a post-AMI population. Detrended fluctuation analysis (DFA) was used to measure the short-term (alpha1) and long-term (alpha2) fractal scaling exponents. Artificial PBs caused a more pronounced reduction of alpha1 value among the post-AMI patients than the healthy subjects, for example, if &amp;amp;amp;amp;amp;amp;gt; 0.25% of the beats were premature a &amp;amp;amp;amp;amp;amp;gt; 25% decrease in the alpha1 was observed in post-AMI patients, but 4% of the premature beats were needed to cause a 25% reduction in alpha1 in healthy subjects. Both edited (1.01 +/- 0.31 vs 1.19 +/- 0.27, P &amp;amp;amp;amp;amp;amp;lt; 0.01) and unedited alpha1 (0.71 +/- 0.33 vs 0.89 +/- 0.36, P &amp;amp;amp;amp;amp;amp;lt; 0.05) differed between the patients who died (n = 42) and those who survived (n = 42) after an AMI. In the general population, only unedited alpha1 differed significantly between survivors and those who died (0.96 +/- 0.19 vs 0.83 +/- 0.27, P &amp;amp;amp;amp;amp;amp;lt; 0.05). Unedited premature beats result in an increase in the randomness of short-term R-R interval dynamics, particularly in post-AMI patients. Premature beats must not necessarily be edited when fractal analysis is used for risk stratification.

Ectopic Beats in Heart Rate Variability Analysis: Effects of Editing on Time and Frequency Domain Measures

by Mirja Peltola and Tapio Seppanen

Annals of Noninvasive Electrocardiology, 2001

Various methods can be used to edit biological and technical artefacts in heart rate variability ... more Various methods can be used to edit biological and technical artefacts in heart rate variability (HRV), but there is relatively little information on the effects of such editing methods on HRV. The effects of editing on HRV analysis were studied using R-R interval data of 10 healthy subjects and 10 patients with a previous myocardial infarction (MI). R-R interval tachograms of verified sinus beats were analyzed from short-term ( approximately 5 min) and long-term ( approximately 24 hours) recordings by eliminating different amounts of real R-R intervals. Three editing methods were applied to these segments: (1) interpolation of degree zero, (2) interpolation of degree one, and (3) deletion without replacement. In time domain analysis of short-term data, the standard deviation of normal-to-normal intervals (SDANN) was least affected by editing, and 30%-50% of the data could be edited by all the three methods without a significant error (&lt; 5%). In the frequency domain analysis, the method of editing resulted in remarkably different changes and errors for both the high-frequency (HF) and the low-frequency (LF) spectral components. The editing methods also yielded in different results in healthy subjects and AMI patients. In 24-hour HRV analysis, up to 50% could be edited by all methods without an error larger than 5% in the analysis of the standard deviation of normal to normal intervals (SDNN). Both interpolation methods also performed well in the editing of the long-term power spectral components for 24-hour data, but with the deletion method, only 5% of the data could be edited without a significant error. The amount and type of editing R-R interval data have remarkably different effects on various HRV indices. There is no universal method for editing ectopic beats that could be used in both the time-domain and the frequency-domain analysis of HRV.

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Respiratory sinus arrhythmia as a predictor of sudden cardiac death after myocardial infarction

by Tapio Seppanen and Mirja Peltola

Annals of Medicine, 2008

AB28-4: Respiratory sinus arrhythmia as a predictor of sudden cardiac death after myocardial infarction

by Mirja Peltola and Tapio Seppanen

Heart rate recovery after exercise as a predictor of mortality among survivors of acute myocardial infarction

by Tapio Seppanen and Mirja Peltola

The American Journal of Cardiology, 2003

Yadav JS, Stertzer S. Prevention of distal embolization during coronary angioplasty in saphenous ... more Yadav JS, Stertzer S. Prevention of distal embolization during coronary angioplasty in saphenous vein grafts and native vessels using porous filter protection. Circulation 2001;104:2436 -2441. 17. Mak KH, Challapalli R, Eisenberg MJ, Anderson KM, Califf RM, Topol EJ. Effect of platelet glycoprotein IIb/IIIa receptor inhibition on distal embolization during percutaneous revascularization of aortocoronary saphenous vein grafts. Am J Cardiol 1997;80:985-988. 18. Neumann FJ, Blasini R, Schmitt C, Alt E, Dirschinger J, Gawaz M, Kastrati A, Schomig A. Effect of glycoprotein IIb/IIIa receptor blockade on recovery of coronary flow and left ventricular function after the placement of coronary-artery stents in acute myocardial infarction. 1. Kleiger RE, Miller JP, Bigger JT Jr, Moss AJ, and the Multicenter Post-Infarction Research Group. Decreased heart rate variability and its association with increased mortality after acute myocardial infaction. Am J Cardiol 1987; 89:256 -262. 2. La Rovere MT, Bigger JT Jr, Marcus FI, Mortara A, Schwartz PJ. Baroreflex sensitivity and heart-rate variability in prediction of total cardiac mortality after myocardial infarction. ATRAMI (Autonomic Tone and Reflexes After Myocardial Infarction) Investigators. Lancet 1998;351:487-494. 3. Huikuri HV, Mäkikallio TH, Airaksinen KEJ, Mitrani R, Castellanos A, Myerburg RJ. Measurement of heart rate variability: a clinical tool or a research toy? J Am Coll Cardiol 1999;34:1878 -1883.

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Role of editing of R–R intervals in the analysis of heart

Respiratory sinus arrhythmia as a predictor of sudden cardiac death after myocardial infarction

Annals of Medicine, 2008

Heart rate recovery after exercise as a predictor of mortality among survivors of acute myocardial infarction

The American Journal of Cardiology, 2003

no-reflow phenomenon" using technetium-99m macroaggregated albumin scintigraphy in patients with ... more

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Ectopic Beats in Heart Rate Variability Analysis: Effects of Editing on Time and Frequency Domain Measures

Annals of Noninvasive Electrocardiology, 2001

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Effects and Significance of Premature Beats on Fractal Correlation Properties of R-R Interval Dynamics

Annals of Noninvasive Electrocardiology, 2004

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Analysis of heart rate variability from 24-hour ambulatory electrocardiographic recordings. Significance of preprocessing of R-R interval time series

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Role of editing of R-R intervals in the analysis of heart rate variability

Frontiers in physiology, 2012

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Heart Rate Variability Density Analysis (Dyx) and Prediction of Long-Term Mortality after Acute Myocardial Infarction

Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc, Jan 11, 2015

Respiratory sinus arrhythmia in Chagas disease

Journal of Electrocardiology, 2013

AB28-4

by Mirja Peltola and Tapio Seppanen

Heart Rhythm, 2006

Determinants and Prognostic Value of Cardiovascular Autonomic Function in Coronary Artery Disease Patients With and Without Type 2 Diabetes

Diabetes Care, 2014

Effects of Postectopic Heart Rate Turbulence on Measures of Heart Rate Variability in Patients after an Acute Myocardial Infarction

Annals of Noninvasive Electrocardiology, 2011

Effects and Significance of Premature Beats on Fractal Correlation Properties of R-R Interval Dynamics

by Mirja Peltola and Tapio Seppanen

Annals of Noninvasive Electrocardiology, 2004

Ectopic Beats in Heart Rate Variability Analysis: Effects of Editing on Time and Frequency Domain Measures

by Mirja Peltola and Tapio Seppanen

Annals of Noninvasive Electrocardiology, 2001

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Respiratory sinus arrhythmia as a predictor of sudden cardiac death after myocardial infarction

by Tapio Seppanen and Mirja Peltola

Annals of Medicine, 2008

AB28-4: Respiratory sinus arrhythmia as a predictor of sudden cardiac death after myocardial infarction

by Mirja Peltola and Tapio Seppanen

Heart rate recovery after exercise as a predictor of mortality among survivors of acute myocardial infarction

by Tapio Seppanen and Mirja Peltola

The American Journal of Cardiology, 2003

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