Age and Sex Differences in Heart Rate Variability and Vagal Specific Patterns - Baependi Heart Study.

Background: Heart rate variability (HRV) is a noninvasive method for assessing autonomic function. Age, sex, and chronic conditions influence HRV. Objectives: Our aim was to evaluate HRV measures exploring differences by age, sex, and race in a sample from a rural area. Methods: Analytical sample (n = 1,287) included participants from the 2010 to 2016 evaluation period of the Baependi Heart Study, a family-based cohort in Brazil. Participants underwent 24-hour Holter-ECG (Holter) monitoring. To derive population reference values, we restricted our analysis to a 'healthy' subset (i.e. absence of medical comorbidities). A confirmatory analysis was conducted with a subgroup sample that also had HRV derived from a resting ECG 10'-protocol obtained during the same time period. Results: The 'healthy' subset included 543 participants. Mean age was 40 ± 14y, 41% were male, 74% self-referred as white and mean body-mass-index was 24 ± 3kg/m2. Time domain HRV measures showed significant differences by age-decade and by sex. Higher values were observed for males across almost all age-groups. Parasympathetic associated variables (rMSSD and pNN50) showed a U-shaped distribution and reversal increase above 60y. Sympathetic-parasympathetic balance variables (SDNN, SDANN) decreased linearly by age. Race differences were no significant. We compared time domain variables with complete data (Holter and resting ECG) between 'healthy' versus 'unhealthy' groups. Higher HRV values were shown for the 'healthy' subset compared with the 'unhealthy' group. Conclusion: HRV measures vary across age and sex. A U-shaped pattern and a reversal increase in parasympathetic variables may reflect an age-related autonomic dysfunction even in healthy individuals that could be used as a predictor of disease development.

Alternative class III distributed polysomnography system

Abstract Introduction Impairment of sleep quality directly increases the risk of heart attack, obesity, and stroke, among other conditions, which makes polysomnography (PSG) an important public health tool. However, the inherent problems with PSG render the correct diagnosis of sleep diseases a difficult task. As a novel alternative to the class II PSG system, this work presents a distributed system composed of three modules, which together are capable of the simultaneous monitoring of environmental variables and patient signals. This system could reduce the distress of a PSG exam in certain cases, dismiss the need for an overnight sleep in a healthcare/sleep centre, and facilitate self-setup and internet-based diagnosis. Methods Hardware and software capable of synchronously monitoring, processing and logging into a µSD card environmental parameters (temperature, humidity, visible light intensity and audible noise level) and directly measured patient signals (electrocardiogram, electrooculogram, and body and limb posture) were designed and implemented. Results A novel alternative to the class III PSG system was demonstrated with independent boards capable of operating for more than 16 hours powered by a 750 mAh/3.7 V battery with 0.003% data loss during preliminary PSG exams. Additionally, a computer-based library capable of reading, decoding, estimating respiration through ECG, and calculating the heart rate was developed and described. Conclusion This article contributes to PSG research through the development of a new PSG system and the improvement of patient comfort. All software and hardware developed are fully open source and available on GitHub.

Reference values for short-term resting-state heart rate variability in healthy adults: Results from the Brazilian Longitudinal Study of Adult Health-ELSA-Brasil study.

Heart rate variability (HRV) is a psychophysiological phenomenon with broad implications, providing an accessible index of vagal function, underpinning psychological constructs, including the capacity for social engagement and emotion regulation, and may predict future morbidity and mortality. However, the lack of reference values for short-term HRV indices for participants of both sexes across the age spectrum is a limiting factor. This was the objective of the present study. Resting electrocardiographic records were obtained from 13,214 participants (both sexes, 35-74 years), and HRV indices in time and frequency domains (mean ± SD) were determined from 5-min records. Results were based on a subsample of 2,874 nonmedicated, healthy participants stratified by sex across 10-year age groupings. Men showed lower heart rate (HR, 64 ± 8 bpm vs. 68 ± 8 bpm, p < .05) and normalized high frequency (HF; 39.4 ± 18.0 normalized units [n.u.] vs. 50.4 ± 18.5 n.u., p < .05) than women, and higher N-N variance (2,214 ± 1,890 ms2 vs. 1,883 ± 1,635 ms2 , p < .05), standard deviation of all N-N intervals (SDNN; 43.7 ± 17.3 ms vs. 40.3 ± 15.8 ms, p < .05) and LF/HF (2.30 ± 2.68 vs. 1.33 ± 1.82, p < .05). HR and HF (n.u.) were also higher in younger than older women. LF/HF was lower in women than men. Percentile curves showed almost all HRV indices decreasing with aging. The availability of short-term, resting-state HRV reference values in a large sample of healthy and nonmedicated participants from 35-74 years will provide a valuable tool for researchers, clinicians, and those in the quantified-self community.

Heartbeat classification system based on neural networks and dimensionality reduction

Abstract Introduction This paper presents a complete approach for the automatic classification of heartbeats to assist experts in the diagnosis of typical arrhythmias, such as right bundle branch block, left bundle branch block, premature ventricular beats, premature atrial beats and paced beats. Methods A pre-processing step was performed on the electrocardiograms (ECG) for baseline removal. Next, a QRS complex detection algorithm was implemented to detect the heartbeats, which contain the primary information that is employed in the classification approach. Next, ECG segmentation was performed, by which a set of features based on the RR interval and the beat waveform morphology were extracted from the ECG signal. The size of the feature vector was reduced by principal component analysis. Finally, the reduced feature vector was employed as the input to an artificial neural network. Results Our approach was tested on the Massachusetts Institute of Technology arrhythmia database. The classification performance on a test set of 18 ECG records of 30 min each achieved an accuracy of 96.97%, a sensitivity of 95.05%, a specificity of 90.88%, a positive predictive value of 95.11%, and a negative predictive value of 92.7%. Conclusion The proposed approach achieved high accuracy for classifying ECG heartbeats and could be used to assist cardiologists in telecardiology services. The main contribution of our classification strategy is in the feature selection step, which reduced classification complexity without major changes in the performance.

Análise do infarto do miocárdio com ênfase no supradesnivelamento do segmento ST e Escores / Myocardial infarction analysis based on ST-segment elevation and scores

Esta revisão é dedicada às principais questões relativas às alterações do segmento ST durante o infarto agudo do miocárdio (IAM), que podem ser estimadas a partir de eletrocardiograma (ECG). São discutidos o diagnóstico, o prognóstico, o tratamento e as desvantagens associadas a esta metodologia. Por fim, as principais avaliações quantitativas do IAM com base nas modificações do ECG são comparadas e discutidas no contexto dos sistemas de telemedicina.

This review focuses on the major issues regarding ST segment abnormalities during acute myocardial infarction (AMI), which may be estimated from electrocardiogram (ECG) tests. Diagnosis, prognosis, treatment and the drawbacks associated to this methodology are discussed. Finally, the major AMI quantitative assessments based on ECG deviations are compared and discussed in the context of telemedicine systems.

Comparison between symbolic and spectral analyses of short-term heart rate variability in a subsample of the ELSA-Brasil study.

Linear and nonlinear analyses of heart rate variability (HRV) have been largely used to evaluate the autonomic balance directed to the cardiovascular system. However, comparative studies evaluating the agreement between methods are scarce. Therefore, our aim was to examine the relationship between spectral (SPA; linear) and symbolic analyses (SYA; nonlinear) indexes. A subsample of 683 participants of the Brazilian Longitudinal Study of Adult Health was investigated. Linear and nonlinear analyses were obtained from 10 min ECG recording at rest. Reliability and agreement between methods were evaluated by kappa-statistic and proportion of agreement. According to SYA, the most frequent pattern was P1V (sympathovagal balance, without sympathetic or vagal predominance) comprising 62.7% of the sample, followed by P2V (vagal predominance) with 33.2%, and finally P0V pattern (sympathetic predominance) with 4.1%. Overall proportion of agreement between SYA and SPA was 39.68% (95% CI 0.360-0.433), with expected agreement by chance of 30.8%. Kappa value was 0.128 indicating a slight agreement between methods. Proportion of agreement was 7.93% (95% CI 0.032-0.126) for predominant sympathetic modulation, 10.39% (95% CI 0.075-0.132) for sympathovagal modulation, and 40.29% (95% CI 0.361-0.444) for parasympathetic modulation. Our data provide evidence for important differences between SPA and SYA on HRV analysis. More studies are needed to clarify the causes of disagreement between two methods designed to evaluate the autonomic modulation of heart beats.

ECG-based detection of left ventricle hypertrophy

Introduction Left ventricle hypertrophy (LVH) is an important risk factor for cardiovascular morbidity and mortality. It is characterized by a thickening of the walls of the left ventricle. The transthoracic echocardiogram is a very accurate method for LVH detection. However, the electrocardiogram (ECG) offers an alternative method in diagnosing LVH, besides being less expensive and easier to obtain. In this context, this study proposes an ECG based approach for left ventricle hypertrophy (LVH) classification. Methods According to the literature, several indexes have so far been proposed that suggest specific changes in cardiac structure, however, generally speaking there is no consensus about the best criteria. This way, instead of considering only one LVH criterion, a score derived from electrocardiographic traces was employed which explores the complementarity of the best criteria through a fusion strategy. The best criteria are those which discriminate normal and LVH ECGs. Results The experiments were performed in the Monica database with a group of fifty men. Half of the individuals had LVH diagnosed by calculating the left ventricular mass index measured by transthoracic echocardiography. The score fusion proposed achieved a sensitivity of 78.3% and specificity of 91.3%, outperforming all isolated LVH criteria. Discussion Unlike the other methods, our score must be estimated within a computer because of its high complexity. Even with this limitation it is much less expensive than using the echocardiography.

[Medical assessments and measurements in ELSA-Brasil]. / Aferições e exames clínicos realizados nos participantes do ELSA-Brasil.

The article describes assessments and measurements performed in the Brazilian Longitudinal Study for Adult Health (ELSA-Brasil). Some assessments including anthropometric assessment, casual blood pressure measurement, and ankle-brachial index have an established clinical application while others including pulse wave velocity, heart rate variability, and carotid intima-media thickness have no established application and do not have reference values for healthy Brazilian population but may be important predictors of cardiovascular outcomes. Blood pressure measurement following postural change maneuver was included in the ELSA-Brasil because it has not been much tested in epidemiological studies. Innovative approaches were developed for assessing the ankle-brachial index using an automatic device instead of the mercury column to measure blood pressure and for assessing the anterior-posterior diameter of the right lobe of the liver by ultrasound for quantitative assessment of nonalcoholic fatty liver disease. All ELSA-Brasil subjects were younger (35 years or more) than those included in other cohorts studying subclinical atherosclerosis. The inclusion of younger individuals and a variety of assessments make the ELSA-Brasil a relevant epidemiology study nationwide and worldwide.

Afericoes e exames clinicos realizados nos participantes do ELSA-Brasil / Medical assessments and measurements in ELSA-Brasil

Este artigo descreve os exames clínicos realizados no Estudo Longitudinal de Saúde do Adulto (ELSA-Brasil). Alguns deles (antropometria, pressão arterial e índice tornozelo-braquial) já têm uso clínico consolidado. Outros, como a velocidade de onda de pulso, variabilidade da frequência cardíaca e medida da espessura médio-intimal de carótidas, carecem de valor de referência na população brasileira não doente e podem constituir preditores importantes de desfechos cardiovasculares. A medida da pressão arterial após manobra postural foi incluída no ELSA-Brasil porque foi pouco testada em estudos epidemiológicos. O ELSA-Brasil inovou na realização do índice tornozelo-braquial, ao usar um aparelho automático em substituição à coluna de mercúrio na medida da pressão arterial, e também na medida do diâmetro ântero-posterior do lobo direito do fígado pela ultrassonografia, proposta para avaliação quantitativa da doença hepática gordurosa não-alcoólica. Os participantes são indivíduos mais jovens (a partir dos 35 anos) do que em outras coortes focadas no estudo da aterosclerose subclínica. A inclusão de indivíduos mais jovens e a diversidade dos exames realizados tornam o ELSA-Brasil um estudo relevante no contexto da epidemiologia brasileira e internacional.

The article describes assessments and measurements performed in the Brazilian Longitudinal Study for Adult Health (ELSA-Brasil). Some assessments including anthropometric assessment, casual blood pressure measurement, and ankle-brachial index have an established clinical application while others including pulse wave velocity, heart rate variability, and carotid intima-media thickness have no established application and do not have reference values for healthy Brazilian population but may be important predictors of cardiovascular outcomes. Blood pressure measurement following postural change maneuver was included in the ELSA-Brasil because it has not been much tested in epidemiological studies. Innovative approaches were developed for assessing the ankle-brachial index using an automatic device instead of the mercury column to measure blood pressure and for assessing the anterior-posterior diameter of the right lobe of the liver by ultrasound for quantitative assessment of nonalcoholic fatty liver disease. All ELSA-Brasil subjects were younger (35 years or more) than those included in other cohorts studying subclinical atherosclerosis. The inclusion of younger individuals and a variety of assessments make the ELSA-Brasil a relevant epidemiology study nationwide and worldwide.

Spectral analysis of heart rate variability with the autoregressive method: what model order to choose?

This work assessed the influence of the autoregressive model order (ARMO) on the spectral analysis of the heart rate variability (HRV). A sample of 68 R-R series obtained from digital ECG records of young healthy adults in the supine position was used. Normalized spectral indexes for each ARMO were compared by Friedman test followed by the Dunn's procedure and statistical significance was set at P<0.05. The results showed that the AR method using orders from 9 to 25 produces normalized spectral parameters statistically similar and, hence, the algorithms commonly employed to estimate optimum order are not mandatory in this case.

The use of bayesian networks for heart beat classification.

This work proposes to use a static Bayesian network as a tool to support medical decision in the on-line detection of Premature Ventricular Contraction beats (PVC) in electrocardiogram (ECG) records, which is a well known cardiac arrhythmia available for study in standard ECG databases. The main motivation to use Bayesian networks is their capability to deal with the uncertainty embedded in the problem (the medical reasoning itself frequently embeds some uncertainty). Indeed, the probabilistic inference is quite suitable to model this kind of problem, for considering its random character; as a consequence, random variables are used to propagate the uncertainty embedded in the problem. Some topologies of static Bayesian networks are implemented and tested in this work, in order to find out the one more suitable to the problem addressed. The results of such tests are discussed in details along the text, and the conclusions are highlighted.

Salt excretion in normotensive individuals with metabolic syndrome: a population-based study.

The objective of this study was to investigate the association between sodium intake and metabolic syndrome (MS) in individuals free from the confounding effects of increased blood pressure (BP). In all, a total of 1655 individuals (45.8% men) who participated in the MONICA-WHO/Vitoria Project, mean age 45+/-11 years were investigated. According to NCEP-ATP lll criteria, MS prevalence was 32.9 and 85% of these individuals had BP >130/85 mm Hg. Thus, high BP represents the main MS risk factor. Twelve-hour nocturnal urine (1900 to 0700 hours) was used to measure urinary sodium and potassium excretion. Sodium excretion was associated with BP. From the optimal BP level up to stage lll hypertension, the mean (median) sodium excretion increased from 99 (89) to 128 (134) mEq and from 81 (69) to 112 (103) mEq in men and women, respectively (P<0.001 for trend; median). However, when 781 individuals with BP <130/85 mm Hg (including 80 drug-free normotensive individuals with MS) were stratified according to the gender and number of MS components, no significant differences were observed either in the urinary volume or in the sodium or potassium excretion. For each of the four MS components, sodium excretion was 96+/-48, 97+/-53, 108+/-65 and 97+/-49 mEq for men, and 83+/-51, 83+/-58, 80+/-49 and 93+/-45 mEq for women, respectively. No differences were found in urinary sodium excretion in normotensive individuals, regardless of the presence of MS. Therefore, it seems that high sodium intake is not an MS predictor per se as suggested earlier.