Time, frequency and information domain analysis of heart period and QT variability in asymptomatic long QT syndrome type 2 patients.

none8siThis study was designed to characterize in time, frequency and information domains heart period (HP) and QT interval variabilities in asymptomatic (ASYMP) long QT syndrome type 2 (LQT2) subjects. HP, approximated as the temporal distance between two consecutive R-wave peaks, and QT, approximated as the temporal distance between the R-wave peak and the T-wave offset, were automatically derived from 24h Holter recordings in 10 ASYMP LQT2 patients and 13 healthy non mutation carriers (NMC) subjects. All analyses were carried out during DAY (from 2 to 6 PM) and NIGHT (from 12 to 4 AM). Mean, variance, spectral power and complexity indices at short, medium and long time scales were assessed over HP and QT beat-to-beat series. Circadian rhythmicity was evident in both NMC and ASYMP LQT2 but ASYMP LQT2 subjects were characterized by higher HP, QT interval and HP variability during both DAY and NIGHT. In addition, multiscale complexity analysis was able to differentiate the groups by showing a higher HP complexity and a lower QT complexity at long time scales in ASYMP LQT2 during DAY. ASYMP LQT2 exhibited a different autonomic control compared to NMC and such a differentiation could be protective and assure them a lower risk profile.Bari V, 11.; Girardengo, G; Marchi, A; De Maria, B; Brink, Pa; Crotti, L; Schwartz, Pj; Porta, ABari V, 1. 1.; Girardengo, Giulia; Marchi, A; De Maria, B; Brink, Pa; Crotti, Lia; Schwartz, Peter; Porta, A

Multiscale complexity analysis of the cardiac control identifies asymptomatic and symptomatic patients in long QT syndrome type 1

Abstract The study assesses complexity of the cardiac control directed to the sinus node and to ventricles in long QT syndrome type 1 (LQT1) patients with KCNQ1-A341V mutation. Complexity was assessed via refined multiscale entropy (RMSE) computed over the beat-to-beat variability series of heart period (HP) and QT interval. HP and QT interval were approximated respectively as the temporal distance between two consecutive R-wave peaks and between the R-wave apex and T-wave end. Both measures were automatically taken from 24-hour electrocardiographic Holter traces recorded during daily activities in non mutation carriers (NMCs, n = 14) and mutation carriers (MCs, n = 34) belonging to a South African LQT1 founder population. The MC group was divided into asymptomatic (ASYMP, n = 11) and symptomatic (SYMP, n = 23) patients according to the symptom severity. Analyses were carried out during daytime (DAY, from 2PM to 6PM) and nighttime (NIGHT, from 12PM to 4AM) off and on beta-adrenergic blockade (BBoff and BBon). We found that the complexity of the HP variability at short time scale was under vagal control, being significantly increased during NIGHT and BBon both in ASYMP and SYMP groups, while the complexity of both HP and QT variability at long time scales was under sympathetic control, being smaller during NIGHT and BBon in SYMP subjects. Complexity indexes at long time scales in ASYMP individuals were smaller than those in SYMP ones regardless of therapy (i.e. BBoff or BBon), thus suggesting that a reduced complexity of the sympathetic regulation is protective in ASYMP individuals. RMSE analysis of HP and QT interval variability derived from routine 24-hour electrocardiographic Holter recordings might provide additional insights into the physiology of the cardiac control and might be fruitfully exploited to improve risk stratification in LQT1 population

Computational Analysis of Complex Beat-to-Beat Dynamics in Heart Cells

Contrary to the popular belief that the heart maintains a regular rhythm, healthy heartbeats fluctuate in a chaotic way. We now know that the fluctuations do not display uncorrelated randomness, but they contain long-range correlations and can be characterized by a fractal. This behavior supports the adaptability of the heart and may thus protect it from external stress. The fractal complexity is also found in the smallest parts of the heart: the cells. In the dawn of advanced pluripotent stem cell technology, producing independently beating cardiomyocytes in a laboratory, the beat-rate fluctuations of heart cells can be directly studied. In this thesis, we investigate the complex fluctuations in the field potentials generated by clusters of human cardiomyocytes. We show that the heart cells exhibit similar correlation properties in the beat-to-beat intervals and field potential durations comparable to RR and QT intervals, i.e., time between consecutive R waves and time from Q wave to the end of T wave, respectively, in an electrocardiogram of a heart. The cells are studied under conditions resembling real-life situations such as cardiac disorders, application of cardioactive drugs, and injuries. The results show significant alteration of the scaling properties in the beat rates, reflecting the changes in the intrinsic mechanism at the cellular level. By employing a set of nonlinear time series analysis tools, we explore their powerful applicability as well as their limitations. Our main method of choice throughout the work is detrended fluctuation analysis, which is designed to detect the degree of correlation in nonstationary time series. We demonstrate that detrended fluctuation analysis and its extensions are extremely useful in dealing with the field potential data of the heart cells despite the presence of abnormalities and irregular trends. The study of heartbeat dynamics at the cellular level using computational methods has important advantages. In particular, the methods provide non-invasive and versatile ways to improve our understanding of the intrinsic firing patterns of the heart cells, which play a crucial role in the future applications of in vitro human cardiomyocytes

On the standardization of approximate entropy: multidimensional approximate entropy index evaluated on short-term HRV time series

Background. Nonlinear heart rate variability (HRV) indices have extended the description of autonomic nervous system (ANS) regulation of the heart. One of those indices is approximate entropy, ApEn, which has become a commonly used measure of the irregularity of a time series. To calculate ApEn, a priori definition of parameters like the threshold on similarity and the embedding dimension is required, which has been shown to be critical for interpretation of the results. Thus, searching for a parameter-free ApEn-based index could be advantageous for standardizing the use and interpretation of this widely applied entropy measurement. Methods. A novel entropy index called multidimensional approximate entropy, , is proposed based on summing the contribution of maximum approximate entropies over a wide range of embedding dimensions while selecting the similarity threshold leading to maximum ApEn value in each dimension. Synthetic RR interval time series with varying levels of stochasticity, generated by both MIX(P) processes and white/pink noise, were used to validate the properties of the proposed index. Aging and congestive heart failure (CHF) were characterized from RR interval time series of available databases. Results. In synthetic time series, values were proportional to the level of randomness; i.e., increased for higher values of P in generated MIX(P) processes and was larger for white than for pink noise. This result was a consequence of all maximum approximate entropy values being increased for higher levels of randomness in all considered embedding dimensions. This is in contrast to the results obtained for approximate entropies computed with a fixed similarity threshold, which presented inconsistent results for different embedding dimensions. Evaluation of the proposed index on available databases revealed that aging was associated with a notable reduction in values. On the other hand, evaluated during the night period was considerably larger in CHF patients than in healthy subjects. Conclusion. A novel parameter-free multidimensional approximate entropy index, , is proposed and tested over synthetic data to confirm its capacity to represent a range of randomness levels in HRV time series. values are reduced in elderly patients, which may correspond to the reported loss of ANS adaptability in this population segment. Increased values measured in CHF patients versus healthy subjects during the night period point to greater irregularity of heart rate dynamics caused by the disease

Quantification of Beat-To-Beat Variability of Action Potential Durations in Langendorff-Perfused Mouse Hearts

Background: Beat-to-beat variability in action potential duration (APD) is an intrinsic property of cardiac tissue and is altered in pro-arrhythmic states. However, it has never been examined in mice.Methods: Left atrial or ventricular monophasic action potentials (MAPs) were recorded from Langendorff-perfused mouse hearts during regular 8 Hz pacing. Time-domain, frequency-domain and non-linear analyses were used to quantify APD variability.Results: Mean atrial APD (90% repolarization) was 23.5 ± 6.3 ms and standard deviation (SD) was 0.9 ± 0.5 ms (n = 6 hearts). Coefficient of variation (CoV) was 4.0 ± 1.9% and root mean square (RMS) of successive differences in APDs was 0.3 ± 0.2 ms. The peaks for low- and high-frequency were 0.7 ± 0.5 and 2.7 ± 0.9 Hz, respectively, with percentage powers of 39.0 ± 20.5 and 59.3 ± 22.9%. Poincaré plots of APDn+1 against APDn revealed ellipsoid shapes. The ratio of the SD along the line-of-identity (SD2) to the SD perpendicular to the line-of-identity (SD1) was 8.28 ± 4.78. Approximate and sample entropy were 0.57 ± 0.12 and 0.57 ± 0.15, respectively. Detrended fluctuation analysis revealed short- and long-term fluctuation slopes of 1.80 ± 0.15 and 0.85 ± 0.29, respectively. When compared to atrial APDs, ventricular APDs were longer (ANOVA, P < 0.05), showed lower mean SD and CoV but similar RMS of successive differences in APDs and showed lower SD2 (P < 0.05). No difference in the remaining parameters was observed.Conclusion: Beat-to-beat variability in APD is observed in mouse hearts during regular pacing. Atrial MAPs showed greater degree of variability than ventricular MAPs. Non-linear techniques offer further insights on short-term and long-term variability and signal complexity

Quantification of beat-to-beat variability of action potential durations in Langendorff-perfused mouse hearts

Beat-to-beat variability in action potential duration (APD) is an intrinsic property of cardiac tissue and is altered in pro-arrhythmic states. However, it has never been examined in mice. Methods: Left atrial or ventricular monophasic action potentials (MAPs) were recorded from Langendorff-perfused mouse hearts during regular 8 Hz pacing. Time-domain, frequency-domain and non-linear analyses were used to quantify APD variability. Results: Mean atrial APD (90% repolarization) was 26.6±3.8 ms and standard deviation (SD) was 1.4±0.8 ms (n=6 hearts). Coefficient of variation (CoV) was 5.9±3.2% and root mean square (RMS) of successive differences in APDs was 0.5±0.2 ms. The peaks for low- and high-frequency were 0.8±0.6 and 2.7±1.1 Hz, respectively, with percentage powers of 37.8±14.5 and 61.5±15.1%. Poincaré plots of APDn+1 against APDn revealed ellipsoid shapes. The ratio of the SD along the line-of-identity (SD2) to the SD perpendicular to the line-of-identity (SD1) was 5.96±1.44. Approximate and sample entropy were 0.45±0.05 and 0.54±0.11, respectively. Detrended fluctuation analysis revealed short- and long-term fluctuation slopes of 1.73±0.17 and 0.68±0.20, respectively. When compared to atrial APDs, ventricular APDs were longer (ANOVA, P<0.05) and showed lower mean SD, CoV and RMS of successive differences in APDs, lower LF power, high HF power and lower SD1 and SD2 (P<0.05) but no difference in the remaining parameters. Conclusion: Beat-to-beat variability in APD is observed in mouse hearts during regular pacing. Atrial MAPs showed greater degree of variability than ventricular MAPs. Non-linear techniques offer further insights on short-term and long-term variability and signal complexity

Novel Framework for Nonlinear HRV Analysis and its Physiological Interpretation

La inclusión de métodos no lineales aplicados a señales de variabilidad del ritmo cardiaco (HRV, del inglés Heart Rate Variability) proporciona una nueva visión en la caracterización de anomalías en el contexto de las enfermedades cardiacas o patologías como la insuficiencia cardiaca o la fibrilación auricular, por nombrar algunas. Se ha demostrado que alteraciones en el sistema nervioso autónomo (ANS, del inglés Autonomic Nervous System), el cuál modula el ritmo cardiaco, conllevan a cambios en los patrones no lineales de la HRV. Sin embargo, la incertidumbre, todavía presente, en los mecanismos que subyacen a variaciones fisiológicas o patofisiológicas en los índices no lineales de la HRV, junto con el alto tiempo que requieren los algoritmos para la estimación de estos índices, representan el cuello de botella para su aplicación en la práctica clínica.Después de una breve introducción sobre los temas abordados en esta la tesis en el capítulo 1, el segundo capítulo, el capítulo 2, está dedicado a la primera gran contribución de esta tesis, que consiste en la propuesta y desarrollo de una metodología con el fin de reducir el coste computacional asociado a la caracterización no lineal de la HRV. El esquema propuesto es muy eficaz, reduciendo el tiempo de cálculo a unos pocos segundos para el análisis no lineal de señales de HRV de corta longitud (5 minutos). Con respecto a la interpretación del análisis no lineal de la HRV, es importante señalar que hay una serie de factores que afectan a su cálculo y deben tenerse en cuenta al comparar diferentes estudios de la literatura. Las características de las series de HRV, como la frecuencia de muestreo, así como la selección de valores de parámetros en los métodos no lineales, tienen un impacto en los resultados de los índices no lineales de la HRV y, en algunas circunstancias, pueden dar lugar a interpretaciones erróneas. Uno de los principales objetivos del capítulo 3 es estudiar la influencia de la tasa de muestreo en los índices no lineales de la HRV y proponer alternativas para atenuar esta influencia. Los métodos propuestos incluyen, por una parte, la corrección de la frecuencia cardiaca de las estimaciones de la HRV mediante fórmulas de regresión individuales o basadas en la población y, por otra, el preprocesamiento de las series temporales de HRV mediante modelos de interpolación o de point-process. El capítulo 4 se centra en investigar el efecto de la selección del valor de los parámetros requeridos para el cálculo de ciertos índices no lineales de la HRV (por ejemplo, la entropía aproximada) y proponiendo un nuevo índice independiente de la definición del valor de éstos parámetros a-priori. Este novedoso índice se denomina entropía multidimensional aproximada. El análisis no lineal de la HRV, incluido el nuevo índice propuesto, se aplica al estudio de afecciones asociadas a alteraciones de la modulación cardiaca del ANS, como el envejecimiento y la insuficiencia cardiaca congestiva (CHF, del inglés Congestive Heart Failure). Por un lado, todos los índices no lineales de la HRV evaluados ven disminuidos significativamente sus valores en las personas mayores en comparación con los jóvenes ambos grupos en condiciones de reposo en posición de decubito supino. Por otro lado, los pacientes con insuficiencia cardiaca muestran valores más altos de los índices no lineales significativamente con respecto al grupo de sujetos sanos, en ambos casos analizando el período nocturno. Además, el análisis no lineal de la HRV es evaluada en respuesta a provocaciones simpáticas, inducidas por el cambio de la posición supina a la posición de pie o por la administración de atropina, donde se observa una disminución en todos los índicesno lineales estimados.El capítulo 5 está dedicado a la evaluación del rendimiento del análisis no lineal de la HRV en el triaje de la administración profiláctica con el fin de prevenir los episodios de hipotension causados por la anestesia espinal durante el parto por cesárea. El estudio se realiza en colaboración con el Servicio de Anestesia del Hospital Universitario Miguel Servet (Zaragoza, España). Debido a que la profilaxis puede producir efectos secundarios en el feto, el desafío consiste en predecir los casos normotensos para los cuales se puede prescindir del tratamiento profilactico. La hipótesis de esta tesis se basa en el hecho de que la alteración de la regulación del ANS causada por el último período de embarazo y la proximidad a la cirugía podría reflejarse en los índices no lineales de la HRV, lo que podría ayudar a predecir los casos que deriven en hipotension y normotension con mayor precisión que cuando se utilizan solamente variables demográficas. Es importante destacar que las propuestas metodológicas para el análisis no lineal de la HRV desarrolladas en la tesis se aplican en la caracterización de otras señales cardiovasculares, como la señal fotopletismografica de pulso. Las series temporales derivadas de esta señal, que incluyen información del sistema vascular periférico, se incorporan en un clasificador basado en la regresión logística junto con los índices no lineales de la HRV. El clasificador propuesto alcanza un 76,5% de sensibilidad y un 72,2% de precisión en la detección de los casos normotensos, proporcionando así información pertinente y objetiva respaldando la decisión final del equipo médico.En el capítulo 6 se presentan las principales conclusiones derivadas de la tesis y se consideran futuras ampliaciones en base a las investigaciones llevadas a cabo. Se hace hincapié en la contribución de la tesis al desarrollo de metodologías novedosas para caracterizar de manera más robusta los índices no lineales de la HRV e interpretar con fiabilidad los resultados correspondientes. Basándose en las metodologías desarrolladas, se investigan las condiciones o patologías asociadas con alteraciones en la modulación autonómica de la actividad cardiaca y se destaca la contribución del análisis no lineal de la HRV para su caracterización. En conclusión, entre los objetivos metodológicos desarrollados en esta tesis se encuentran: i) la propuesta de un esquema de trabajo para incrementar la fiabilidad de la estimación de la dimensión de correlación, usando un algoritmo que reduce la carga computacional, facilitando su aplicabilidad en la práctica clínica; ii) el desarrollo de métodos alternativos para atenuar la dependencia de los índices no lineales de la HRV con el ritmo cardiaco medio; iii) la propuesta de un índice no lineal de la HRV multidimensional independiente de la definición a priori de parámetros para su estimación. Además, los objetivos relacionados con la aplicación clínica de lascontribuciones metodológicas son: i) la caracterización del efecto del envejecimiento en los índices no lineales de la HRV; ii) la evaluación de la complejidad e irregularidad del ritmo cardiaco en pacientes que sufren de insuficiencia cardiaca comparada con sujetos sanos; iii) la mejora de la eficacia de la profilaxis para la prevención de eventos de hipotensión después de anestesia espinal durante parto programado por cesárea.<br /

The Application of Computer Techniques to ECG Interpretation

This book presents some of the latest available information on automated ECG analysis written by many of the leading researchers in the field. It contains a historical introduction, an outline of the latest international standards for signal processing and communications and then an exciting variety of studies on electrophysiological modelling, ECG Imaging, artificial intelligence applied to resting and ambulatory ECGs, body surface mapping, big data in ECG based prediction, enhanced reliability of patient monitoring, and atrial abnormalities on the ECG. It provides an extremely valuable contribution to the field