Estratificación del riesgo y prevención de la muerte súbita en pacientes con insuficiencia cardíaca

On the Robustness of Multiscale Indices for Long-Term Monitoring in Cardiac Signals

The identification of patients with increased risk of Sudden Cardiac Death (SCD) has been widely studied during recent decades, and several quantitative measurements have been proposed from the analysis of the electrocardiogram (ECG) stored in 1-day Holter recordings. Indices based on nonlinear dynamics of Heart Rate Variability (HRV) have shown to convey predictive information in terms of factors related with the cardiac regulation by the autonomous nervous system, and among them, multiscale methods aim to provide more complete descriptions than single-scale based measures. However, there is limited knowledge on the suitability of nonlinear measurements to characterize the cardiac dynamics in current long-term monitoring scenarios of several days. Here, we scrutinized the long-term robustness properties of three nonlinear methods for HRV characterization, namely, the Multiscale Entropy (MSE), the Multiscale Time Irreversibility (MTI), and the Multifractal Spectrum (MFS). These indices were selected because all of them have been theoretically designed to take into account the multiple time scales inherent in healthy and pathological cardiac dynamics, and they have been analyzed so far when monitoring up to 24 h of ECG signals, corresponding to about 20 time scales. We analyzed them in 7-day Holter recordings from two data sets, namely, patients with Atrial Fibrillation and with Congestive Heart Failure, by reaching up to 100 time scales. In addition, a new comparison procedure is proposed to statistically compare the poblational multiscale representations in different patient or processing conditions, in terms of the non-parametric estimation of confidence intervals for the averaged median differences. Our results show that variance reduction is actually obtained in the multiscale estimators. The MSE (MTI) exhibited the lowest (largest) bias and variance at large scales, whereas all the methods exhibited a consistent description of the large-scale processes in terms of multiscale index robustness. In all the methods, the used algorithms could turn to give some inconsistency in the multiscale profile, which was checked not to be due to the presence of artifacts, but rather with unclear origin. The reduction in standard error for several-day recordings compared to one-day recordings was more evident in MSE, whereas bias was more patently present in MFS. Our results pave the way of these techniques towards their use, with improved algorithmic implementations and nonparametric statistical tests, in long-term cardiac Holter monitoring scenarios.

Sudden Cardiac Risk Stratification with Electrocardiographic Indices - A Review on Computational Processing, Technology Transfer, and Scientific Evidence

Great effort has been devoted in recent years to the development of sudden cardiac risk predictors as a function of electric cardiac signals, mainly obtained from the electrocardiogram (ECG) analysis. But these prediction techniques are still seldom used in clinical practice, partly due to its limited diagnostic accuracy and to the lack of consensus about the appropriate computational signal processing implementation. This paper addresses a three-fold approach, based on ECG indices, to structure this review on sudden cardiac risk stratification. First, throughout the computational techniques that had been widely proposed for obtaining these indices in technical literature. Second, over the scientific evidence, that although is supported by observational clinical studies, they are not always representative enough. And third, via the limited technology transfer of academy-accepted algorithms, requiring further meditation for future systems. We focus on three families of ECG derived indices which are tackled from the aforementioned viewpoints, namely, heart rate turbulence (HRT), heart rate variability (HRV), and T-wave alternans. In terms of computational algorithms, we still need clearer scientific evidence, standardizing, and benchmarking, siting on advanced algorithms applied over large and representative datasets. New scenarios like electronic health recordings, big data, long-term monitoring, and cloud databases, will eventually open new frameworks to foresee suitable new paradigms in the near future.

The effect of streptomycin on stretch-induced electrophysiological changes of isolated acute myocardial infarcted hearts in rats

AIMS

To explore whether the stretch of ischaemic myocardium could modulate the electrophysiological characteristics, especially repolarization via mechanoelectric feedback (MEF), as well as the effect of streptomycin (SM) on these changes. Methods Thirty-six wistar rats were randomly divided into four groups: control group (n = 9), SM group (n = 9), myocardial infarction (MI) group (n = 9), and MI + SM group (n = 9). After perfused on Langendorff, the isolated hearts were stretched for 5s by a ballon inflation of 0.2mL. After being stretched, the effect of the stretch was observed for 30s, including the 20, 20-70, 70, and 90% monophasic action potential duration (MAPD), i.e. MAPD(20), MAPD(20-70), MAPD(70), and MAPD(90), respectively, premature ventricular beats (PVB), and ventricular tachycardia (VT). Results The stretch caused a decrease in MAPD(20-70) (both P <0.01) and an increase in MAPD(90) (both P <0.01) in both control and MI groups. Moreover, the MAPD(90) in the MI group had increased more significantly than that in the control group (P <0.05). A concentration of 200 micromol/L of SM had no influence on both MAPD(20-70) and MAPD(90) of basic state (P > 0.05, except MAPD(20-70) between the control and SM groups, P < 0.01), whereas it had reduced the length of MAPD(90) (P < 0.05) and inhibited the decrease in MAPD(20-70) induced by the inflation. There was a decrease in the tendency of MAPD(70) after the stretch (P = NS) and SM had reversed the tendency, whereas MAPD(20) had no obvious changes after inflation. The incidence rate of PVB and VT in the MI group was higher than that in the control group after inflation (P < 0.01). The 200 micromol/L SM reduced the incidence rate of PVB, and obviously inhibited the occurrence of VT (P < 0.01).

CONCLUSIONS

Stretch could alter the electrophysiological activities of myocardium via MEF, which could enhance in acute myocardial infarction and facilitate the generation and maintenance of malignant arrhythmias. SM could significantly inhibit the occurrence of arrhythmias, which may correlate with the effect on blocking stretch-activated ion channels.