Showing papers by "Marek Malik published in 1993"

Components of heart rate variability--what they really mean and what we really measure

Abstract: I n 1981, Akselrod et al’ examined the frequency components of heart rate variability (HRV) in dogs at physiologic rest, and under parasympathetic and total autonomic blockade. That study, which was later reproduced in humans,2 showed that the so-called highfrequency components of physiologic HRV (i.e., spectral components in the band of 0.15 to 0.5 Hz [approximate]) are predominantly modulated by the parasympathetic nervous system, whereas the lower frequency components (spectral band 0.05 to 0.!5 Hz) are under the iniluence of both the parasympathetic and sympathetic systems. Parasympathetic predominance of the autonomic system associated with increase of the high-frequency components of HRV has been achieved by both maneuvers, such as controlled respiration and cold stimulation of the face, and p-adrenergic receptor blockade.3,4 However, sympathetic excitation, which was reflected by increased low-frequency components of HRV, has most frequently been achieved with baroreceptor unloading.5 Thus, the highand low-frequency components of HRV were fumly associated with parasympathetic and sympathetic intluences, respectively, because of many studies that investigated the effects of different maneuvers and pharmacologic interventions on HRV After these investigations, many researchers took for granted that the spec& spectral components of HRV can be used not only as markers of the vagal and sympathetic influences on the modulations of heart rate, but also as measures of the tone of the parasympathetic and sympathetic nervous systems under various conditions. The same concept is frequently applied to some timedomain methods for HRV assessment, which are known to provide results similar to those of the speciiic spectral components. However, the idea that in all different circumstances, the HRV components closely reflect the degree of autonomic tone has no solid basis, and the purpose of this short editorial is to point out the underlying misunderstanding of this concept. The cardiac parasympathetic tone manifests in efferent vagal impulses. These impulses and their effects are very short and discrete, and their intrinsic frequency is much faster than that of high-frequency components of HRY6,7 The high-frequency componenCs of HRV correspond to the modulation of vagal tone, which is linked, for example, to respiration. These modulations of vagal efferent activity cause short-term alterations of the cycle length of sinus rhythm. Thus, the increase of highfrequency components of HRV reflects increased mod-

Do patients with neurally mediated syncope have augmented vagal tone

Abstract: Head-up tilt testing is now recognized as a valuable diagnostic tool for identifying patients with neurally mediated syncope. However, the causes of individual susceptibility to such orthostatic stress have not been well characterized in this patient population. At the time of syncope, there is evidence to suggest both withdrawal of sympathetic tone as well as increased vagal activity. The latter is manifest by bradycardia, increased high-frequency spectral power of heart rate variability and release of pancreatic polypeptide. 1,2 The purpose of this study was to assess the importance of resting autonomic tone assessed by temporal and spectral measures of heart rate variability and vagal reserve assessed by baroreceptor sensitivity in patients with neurally mediated syncope and in control subjects.

Influence of recognition errors of computerised analysis of 24-hour electrocardiograms on the measurement of spectral components of heart rate variability

Abstract: Spectral methods for the assessment of heart rate variability (HRV) in 24-h electrocardiogram (ECG) are believed to require visual verification and manual editing of the computerised recognition of the ECG. This study investigated the effect of the recognition errors of computerised ECG recognition on two methods providing spectral HRV indices: (a) Fast Fourier Transformation (FFT); and (b) peak-to-trough analysis (PTA). Both methods were used to measure HRV spectra in 24-h ECGs recorded in 557 survivors of acute myocardial infarction. Each ECG was analysed using the Marquette 8000 Holter system and spectral HRV analyses were performed both prior to and after manual verification of the automatic ECG analysis. The FFT and PTA methods were used to calculate the low (0.04-0.15 Hz), medium (0.15-0.40 Hz) and high (0.40-1.00 Hz) HRV spectral components. For each method and for each spectral component, the rank correlations between the results obtained from unedited and edited ECG recognition were calculated. The correlations between the corresponding spectral components provided by the FFT and PTA methods applied to the edited recognitions were also calculated. Both methods were substantially affected by recognition errors. The FFT method was more sensitive to the misrecognition than the PTA method. The inter-method correlations were higher for the high and medium spectral components than for the low spectral component. The study suggests that spectral HRV analysis should be performed only on carefully verified and manually corrected recognitions of long-term electrocardiograms.

Frequency Versus Time Domain Analysis of the Signal‐Averaged Electrocardiogram: Reproducibility of the Spectral Turbulence Analysis

Abstract: Reproducibility of the Spectral Turbulence Analysis Spectral turbulence analysis (STA) of the signal-averaged electrocardiogram (ECG) is a new frequency domain method that analyzes the total high gain QRS complex and not only its terminal portion This study examined the qualitative and quantitative short-term reproducibility of this technique (three recordings made within 25 min) in 68 subjects: 16 healthy volunteers; 22 patients with ventricular tachycardia and no evidence of heart disease; and 30 postinfarction patients with sustained ventricular tachycardia The reproducibility of diagnosis of the STA was compared with that of the conventional time domain analysis of the signal-averaged ECG using standard criteria of abnormality The reproducibility of numeric values of the spectral turbulence and of the time domain indices was performed by computing the ratios between standard deviation of measurements in individual subjects and standard deviations of all measurements The reproducibility of diagnostic conclusions of the time domain analysis was slightly better than that of the STA but the differences were not significant (88%-91% of consistent time domain results vs 84% of consistent STA results) The numeric reproducibility of three STA parameters was slightly but not significantly inferior to that of the time domain indices whereas the reproducibility of the fourth STA variable, the intersegment correlation standard deviation (ISCSD), was significantly worse than that of the other indices Of the two different ECG segments analyzed, the reproducibility of the STA variables calculated for the total QRS region was significantly better than that of the terminal low power QRS region In conclusion, the qualitative and quantitative reproducibility of the STA is slightly but not significantly worse than that of the time domain analysis with the exception of the ISCSD, which is significantly less reproducible than all other parameters

Improved identification of late potentials by adjustment of the number of analyzed segments of the spectral temporal mapping of the signal-averaged electrocardiogram

Abstract: Late potentials (LP), microvolt oscillations occurring at the end and after the QRS complex, identify patients at risk of ventricular tachycardia and sudden death. 1,2 They can be detected by the time domain analysis of the surface signal-averaged electrocardiogram (SAECG). 1 LP can also be identified by the frequency domain analysis of the SAECG because they are characterized by higher frequencies than the ST segment. 3 This technique offers some advantages over time domain analysis: patients with bundle branch block need not be excluded, a noise-dependent algorithm for detection of LP offset is not applied, and high-pass filters, distorting the signal, are not used. Spectral temporal mapping (STM) of the SAECG is a new frequency domain technique that uses fast Fourier transform analysis. 4 Routinely, 25 electrocardiographic segments are analyzed, first starting 20 ms before the standard QRS offset. The frequency content in the most distal 5 segments, which are located well within the ST segment (where LP are not likely to be) is used as a reference spectrum, and compared with the spectra of earlier segments (where LP are often present) in order to calculate the result of the STM. It is crucial for correct analysis to avoid the presence of high frequency components in the last 5 reference segments. However, when the total QRS duration exceeds the standard QRS duration by >20 ms owing to the presence of a long LP, the reference segments include LP (Figure 1A). Therefore, a new formula is needed to calculate the number of segments to be analyzed in such patients.

Concepts of the compartmental analysis.

Abstract: Biomedical applications of computers and of mathematics in general are diverse. Many theories of applied mathematics and many computational approaches and algorithms, which were originally developed for a completely different use (e.g., in physics or economics), have later been modified or adapted in order to he used in hiomedical projects. In fewer instances, a new mathematical theory originated directly from biomedical problems. One of these instances is the so-called compartmental analysis that has been developed in order to study metabolic systems. As the results ohtained by the means of compartmental modeling are from time to time reported in medical publications, this article will review the elementary principles of compartmental analysis in order to give a basic understanding of this mathematical and computational tool and of its applications.

Computing Survival and Relative Risk: Some Basics

Abstract: Introduction Survival analyses are frequently reported in clinical literature. This form of analysis is used for many types of data including events that are not necessarily fatal, such as the recurrence of arrhythmia or the inappropriate firing of an implanted defibrillator. The computation of survival curves is supported hy a number of statistical packages. This article in the current series of discussions on computing, statistics, and data handling looks at how survival data is presented in Kaplan-Meier (K-M) plots and at the quantification of relative risks, which may he associated with differential diagnostic findings and treatment choices.

A Few Simple t‐Tests

Abstract: In 1908 W.S. Gossef̂ published a method of comparing tv̂ ro sets of data, which later became known as the \"Student's t-test.\" At that time, clinical trials were not practiced, and so it is most likely that the paper went unnoticed at first by the medical profession. Eighty-five years later, the test is used daily by hundreds, probably thousands, of scientists and other investigators. The formula is simple enough for the calculations to be done by hand, or on a pocket calculator, but more often the test will be done on a computer, using a package of statistical programs. Does the availability of statistical packages do away with the need for help from a statistician? Leaving aside the situations where statistical advice in the planning phase might avoid inefficient or unproductive experiments, and the situations where more sophisticated methods of analysis are needed, we look just at the case of a few simple t-tests.