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Background: T-wave (TW) morphology indices based on time-warping ($d_{w}$) have shown significant cardiovascular risk stratification value. However, errors in the location of TW boundaries may impact their prognostic power. Our aim was to test the hypothesis that a weighted time-warping function (WF) would reduce the sensitivity of $d_{w}$ to these errors and improve their clinical significance. Methods: The WFs were proportional to (i) the reference TW ($\mathcal {T}$), and (ii) the absolute value of its derivative ($\mathcal {D}$). The index $d_{w}$ was recalculated using these WFs, and its performance was compared to the unweighted control case ($\mathcal {C}$) in four different scenarios: 1) robustness against simulated TW boundaries location errors; 2) ability to retain physiological information in an electrophysiological cardiac model; 3) ability to monitor blood potassium concentration changes ($\Delta [K^+]$) in 29 hemodialysis (HD) patients; 4) and the sudden cardiac death (SCD) risk stratification value of the TW morphology restitution (TMR) index, derived from $d_{w}$ , in 651 chronic heart failure (CHF) patients. Results and Discussion: The WFs led to a reduced sensitivity ($\mathcal {R}$) of $d_{w}$ to TW boundary location errors as compared to $\mathcal {C}$ (median $\mathcal {R}$ =0.19 and 0.22 and 0.35 for $\mathcal {T}$ , $\mathcal {D}$ and $\mathcal {C}$ , respectively). They also preserved the physiological relationship between $d_{w}$ and repolarization dispersion changes at ventricular level. No improvements in $\Delta [K^+]$ tracking were observed for the HD patients (Pearson’s median correlation [ $r$ ] between $\Delta [K^+]$ and $d_{w}$ was $0.86\leq r \leq 0.90$ for $\mathcal {T}$ , $\mathcal {D}$ and $\mathcal {C}$). In CHF patients, the SCD risk stratification value of TMR was improved by applying $\mathcal {T}$ (hazard ratio, HAR, of 2.80), followed by $\mathcal {D}$ (HAR=2.32) and $\mathcal {C}$ (HAR=2.23). Conclusions and Significance: The proposed WFs, with $\mathcal {T}$ showing the best performance, increased the robustness of time-warping based markers against TW location errors preserving their physiological information content and boosting their SCD risk stratification value. Results from this work support the use of $\mathcal {T}$ when deriving $d_{w}$ for future clinical applications. [ABSTRACT FROM AUTHOR]

We investigated the ability of time-warping-based ECG-derived markers of T-wave morphology changes in time ( d w ) and amplitude ( d a ), as well as their non-linear components ( d w NL and d a NL ), and the heart rate corrected counterpart ( d w , c ), to monitor potassium concentration ( [ K + ] ) changes ( Δ [ K + ] ) in end-stage renal disease (ESRD) patients undergoing hemodialysis (HD). We compared the performance of the proposed time-warping markers, together with other previously proposed [ K + ] markers, such as T-wave width ( T w ) and T-wave slope-to-amplitude ratio ( T S / A ), when computed from standard ECG leads as well as from principal component analysis (PCA)-based leads. 48-hour ECG recordings and a set of hourly-collected blood samples from 29 ESRD-HD patients were acquired. Values of d w , d a , d w NL , d a NL and d w , c were calculated by comparing the morphology of the mean warped T-waves (MWTWs) derived at each hour along the HD with that from a reference MWTW, measured at the end of the HD. From the same MWTWs T w and T S / A were also extracted. Similarly, Δ [ K + ] was calculated as the difference between the [ K + ] values at each hour and the [ K + ] reference level at the end of the HD session. We found that d w and d w , c showed higher correlation coefficients with Δ [ K + ] than T S / A —Spearman's (ρ ) and Pearson's (r)—and T w —Spearman's (ρ )—in both SL and PCA approaches being the intra-patient median ρ ≥ 0.82 and r ≥ 0.87 in SL and ρ ≥ 0.82 and r ≥ 0.89 in PCA respectively. Our findings would point at d w and d w , c as the most suitable surrogate of Δ [ K + ] , suggesting that they could be potentially useful for non-invasive monitoring of ESRD-HD patients in hospital, as well as in ambulatory settings. Therefore, the tracking of T-wave morphology variations by means of time-warping analysis could improve continuous and remote [ K + ] monitoring of ESRD-HD patients and flagging risk of [ K + ] -related cardiovascular events. [ABSTRACT FROM AUTHOR]

Background: End-stage renal disease patients undergoing hemodialysis (ESRD-HD) therapy are highly susceptible to malignant ventricular arrhythmias caused by undetected potassium concentration ([ K + ]) variations ( Δ [ K + ] ) out of normal ranges. Therefore, a reliable method for continuous, noninvasive monitoring of [ K + ] is crucial. The morphology of the T-wave in the electrocardiogram (ECG) reflects Δ [ K + ] and two time-warping-based T-wave morphological parameters, d w and its heart-rate corrected version d w , c , have been shown to reliably track Δ [ K + ] from the ECG. The aim of this study is to derive polynomial models relating d w and d w , c with Δ [ K + ] , and to test their ability to reliably sense and quantify Δ [ K + ] values. Methods: 48-hour Holter ECGs and [ K + ] values from six blood samples were collected from 29 ESRD-HD patients. For every patient, d w and d w , c were computed, and linear, quadratic, and cubic fitting models were derived from them. Then, Spearman's (ρ) and Pearson's (r) correlation coefficients, and the estimation error ( e d ) between Δ [ K + ] and the corresponding model-estimated values ( Δ ^ [ K + ] ) were calculated. Results and Discussions: Nonlinear models were the most suitable for Δ [ K + ] estimation, rendering higher Pearson's correlation (median 0.77 ≤ r ≤ 0.92) and smaller estimation error (median 0.20 ≤ e d ≤ 0.43) than the linear model (median 0.76 ≤ r ≤ 0.86 and 0.30 ≤ e d ≤ 0.40), even if similar Spearman's ρ were found across models (median 0.77 ≤ ρ ≤ 0.83). Conclusion: Results support the use of nonlinear T-wave-based models as Δ [ K + ] sensors in ESRD-HD patients. [ABSTRACT FROM AUTHOR]

Presents a quantitative approach to measuring abnormal intra-QRS signals. Use of the high-resolution electrocardiogram (HRECG); Other uses of the HRECG; Objective of the study; Characterization of abnormal intra-QRS potentials.

Purpose: This study was conducted to test, in mountain running route conditions, the accuracy of the Polar V800™ monitor as a suitable device for monitoring the heart rate variability (HRV) of runners.Method: Eighteen healthy subjects ran a route that included a range of running slopes such as those encountered in trail and ultra-trail races. The comparative study of a V800 and a Holter SEER 12 ECG Recorder™ included the analysis of RR time series and short-term HRV analysis. A correction algorithm was designed to obtain the corrected Polar RR intervals. Six 5-min segments related to different running slopes were considered for each subject.Results: The correlation between corrected V800 RR intervals and Holter RR intervals was very high (r = 0.99, p < 0.001), and the bias was less than 1 ms. The limits of agreement (LoA) obtained for SDNN and RMSSD were (- 0.25 to 0.32 ms) and (- 0.90 to 1.08 ms), respectively. The effect size (ES) obtained in the time domain HRV parameters was considered small (ES < 0.2). Frequency domain HRV parameters did not differ (p > 0.05) and were well correlated (r ≥ 0.96, p < 0.001).Conclusion: Narrow limits of agreement, high correlations and small effect size suggest that the Polar V800 is a valid tool for the analysis of heart rate variability in athletes while running high endurance events such as marathon, trail, and ultra-trail races. [ABSTRACT FROM AUTHOR]

Background: The arrhythmogenesis of ventricular myocardial ischemia has been extensively studied, but models of atrial ischemia in humans are lacking. This study aimed at describing the electrophysiological alterations induced by acute atrial ischemia secondary to atrial coronary branch occlusion during elective coronary angioplasty.Methods and Results: Clinical data, 12-lead ECG, 12-hour Holter recordings, coronary angiography, and serial plasma levels of high-sensitivity troponin T and midregional proatrial natriuretic peptide were prospectively analyzed in 109 patients undergoing elective angioplasty of right or circumflex coronary arteries. Atrial coronary branches were identified and after the procedure patients were allocated into two groups: atrial branch occlusion (ABO, n=17) and atrial branch patency (non-ABO, n=92). In comparison with the non-ABO, patients with ABO showed: (1) higher incidence of periprocedural myocardial infarction (20% versus 53%, P=0.01); (2) more frequent intra-atrial conduction delay (19% versus 46%, P=0.03); (3) more marked PR segment deviation in the Holter recordings; and (4) higher incidence of atrial tachycardia (15% versus 41%, P=0.02) and atrial fibrillation (0% versus 12%, P=0.03). After adjustment by a propensity score, ABO was an independent predictor of periprocedural infarction (odds ratio, 3.4; 95% confidence interval, 1.01-11.6, P<0.05) and atrial arrhythmias (odds ratio, 5.1; 95% confidence interval, 1.2-20.5, P=0.02).Conclusions: Selective atrial coronary artery occlusion during elective percutaneous transluminal coronary angioplasty is associated with myocardial ischemic damage, atrial arrhythmias, and intra-atrial conduction delay. Our data suggest that atrial ischemic episodes might be considered as a potential cause of atrial fibrillation in patients with chronic coronary artery disease. [ABSTRACT FROM AUTHOR]

A response from the authors of the article "Electrophysiological Effects of Selective Atrial Coronary Artery Occlusion in Humans" in the 2016;133 issue, is presented.

This paper proposes the integration and analysis of a closed-loop model of the baroreflex and cardiovascular systems, focused on a time-varying estimation of the autonomic modulation of heart rate in Brugada syndrome (BS), during exercise and subsequent recovery. Patient-specific models of 44 BS patients at different levels of risk (symptomatic and asymptomatic) were identified through a recursive evolutionary algorithm. After parameter identification, a close match between experimental and simulated signals (mean error = 0.81%) was observed. The model-based estimation of vagal and sympathetic contributions were consistent with physiological knowledge, enabling to observe the expected autonomic changes induced by exercise testing. In particular, symptomatic patients presented a significantly higher parasympathetic activity during exercise, and an autonomic imbalance was observed in these patients at peak effort and during post-exercise recovery. A higher vagal modulation during exercise, as well as an increasing parasympathetic activity at peak effort and a decreasing vagal contribution during post-exercise recovery could be related with symptoms and, thus, with a worse prognosis in BS. This work proposes the first evaluation of the sympathetic and parasympathetic responses to exercise testing in patients suffering from BS, through the recursive identification of computational models; highlighting important trends of clinical relevance that provide new insights into the underlying autonomic mechanisms regulating the cardiovascular system in BS. The joint analysis of the extracted autonomic parameters and classic electrophysiological markers could improve BS risk stratification. [ABSTRACT FROM AUTHOR]

Ventricular arrhythmias in Brugada syndrome (BS) typically occur at rest and especially during sleep, suggesting that changes in the autonomic modulation may play an important role in arrhythmogenesis. The autonomic response to exercise and subsequent recovery was evaluated on 105 patients diagnosed with BS (twenty-four were symptomatic), by means of a time-frequency heart rate variability (HRV) analysis, so as to propose a novel predictive model capable of distinguishing symptomatic and asymptomatic BS populations. During incremental exercise, symptomatic patients showed higher HFnu values, probably related to an increased parasympathetic modulation, with respect to asymptomatic subjects. In addition, those extracted HRV features best distinguishing between populations were selected using a two-step feature selection approach, so as to build a linear discriminant analysis (LDA) classifier. The final features subset included one third of the total amount of extracted autonomic markers, mostly acquired during incremental exercise and active recovery, thus evidencing the relevance of these test segments in BS patients classification. The derived predictive model showed an improved performance with respect to previous works in the field (AUC = 0.92 ± 0.01; Se = 0.91 ± 0.06; Sp = 0.90 ± 0.05). Therefore, based on these findings, some of the analyzed HRV markers and the proposed model could be useful for risk stratification in Brugada syndrome. [ABSTRACT FROM AUTHOR]

Abstract: We develop a method to quantify the changes in heart rate dynamics during local myocardial ischemia induced by a percutaneous transluminal coronary angioplasty procedure (PTCA). The method introduces an index measuring the nonlinear content of the beat-to-beat (RR) time series by using nonlinear time series techniques such as surrogate data analysis and average mutual information. The index is applied to RR data from 67 subjects obtained before, during, and after the ischemic period and shows an increase in the nonlinearity of the cardiac control dynamics during ischemic and reperfusion stages. The nonlinear index is also used to characterize the effects of performing the coronary occlusion at different arteries and distances. We observe that the effect of ischemia becomes larger as the occlusion distance is reduced, and that most of the changes in the nonlinear content of the dynamics occur at long time scales typically related to sympathetic modulation of the cardiac rhythm (6–25s). [Copyright &y& Elsevier]

In the framework of the electrocardiography (ECG) signals, this paper describes an original approach to identify heartbeat morphologies and to detect R-wave events. The proposed approach is based on a "geometrical matching" rule evaluated using a decision function in a local moving-window procedure. The decision function is a normalized measurement of a similarity criterion comparing the windowed input signal with the reference beat-pattern into a nonlinear-curve space. A polynomial expansion model describes the reference pattern. For the curve space, an algebraic-fitting distance is built according to the canonical equation of the unit circle. The geometrical matching approach operates in two stages, i.e., training and detection ones. In the first stage, a learning-method based on genetic algorithms allows us estimating the decision function from training beat-pattern. In the second stage, a level-detection algorithm evaluates the decision function to establish the threshold of similarity between the reference pattern and the input signal. Finally, the findings for the MIT-BIH Arrhythmia Database present about 98% of sensitivity and 99% of positive predictivity for the R-waves detection, using low-order polynomial models. [ABSTRACT FROM AUTHOR]