Claudia Lerma

Patterns of ectopy leading to increased risk of fatal or near-fatal cardiac arrhythmia in patients with depressed left ventricular function after an acute myocardial infarction.

AIMS To identify potential new markers for assessing the risk of sudden arrhythmic events based on a method that captures features of premature ventricular complexes (PVCs) in relation to sinus RR intervals in Holter recordings (heartprint). METHODS AND RESULTS Holter recordings obtained 6 weeks after acute myocardial infarction from 227 patients with reduced ventricular function (left ventricular ejection fraction ≤ 40%) were used to produce heartprints. Measured indices were: PVCs per hour, standard deviation of coupling interval (SDCI), and the number of occurrences of the most prevalent form of PVCs (SNIB). Predictive values, survival analysis, and Cox regression with adjustment for clinical variables were performed based on primary endpoint, defined as an electrocardiogram-documented fatal or near-fatal arrhythmic event, death from any cause, and cardiac death. High ectopy (PVCs per hour ≥10) was a predictor of all endpoints. Repeating forms of PVCs (SNIB ≥ 83) was a predictor of primary endpoint, hazard ratio = 3.5 (1.3-9.5), and all-cause death, hazard ratio = 2.8 (1.1-7.3), but not cardiac death. SDCI ≤ 80 ms was a predictor of all-cause death and cardiac death, but not of primary endpoint. CONCLUSION High ectopy, prevalence of repeating forms of PVCs, and low coupling interval variability are potentially useful risk markers of fatal or near-fatal arrhythmias after myocardial infarction.

New methods for the analysis of heartbeat behavior in risk stratification.

Developing better methods for risk stratification for tachyarrhythmic sudden cardiac remains a major challenge for physicians and scientists. Since the transition from sinus rhythm to ventricular tachycardia/fibrillation happens by different mechanisms in different people, it is unrealistic to think that a single measure will be adequate to provide a good index for risk stratification. We analyze the dynamical properties of ventricular premature complexes over 24 h in an effort to understand the underlying mechanisms of ventricular arrhythmias and to better understand the arrhythmias that occur in individual patients. Two dimensional density plots, called heartprints, correlate characteristic features of the dynamics of premature ventricular complexes and the sinus rate. Heartprints show distinctive characteristics in individual patients. Based on a better understanding of the natures of transitions from sinus rhythm to sudden cardiac and the mechanisms of arrhythmia prior to cardiac arrest, it should be possible to develop better methods for risk stratification.

Predicting the risk of sudden cardiac death

Sudden cardiac death (SCD) is the result of a change of cardiac activity from normal (typically sinus) rhythm to a rhythm that does not pump adequate blood to the brain. The most common rhythms leading to SCD are ventricular tachycardia (VT) or ventricular fibrillation (VF). These result from an accelerated ventricular pacemaker or ventricular reentrant waves. Despite significant efforts to develop accurate predictors for the risk of SCD, current methods for risk stratification still need to be improved. In this article we briefly review current approaches to risk stratification. Then we discuss the mathematical basis for dynamical transitions (called bifurcations) that may lead to VT and VF. One mechanism for transition to VT or VF involves a perturbation by a premature ventricular complex (PVC) during sinus rhythm. We describe the main mechanisms of PVCs (reentry, independent pacemakers and abnormal depolarizations). An emerging approach to risk stratification for SCD involves the development of individualized dynamical models of a patient based on measured anatomy and physiology. Careful analysis and modelling of dynamics of ventricular arrhythmia on an individual basis will be essential in order to improve risk stratification for SCD and to lay a foundation for personalized (precision) medicine in cardiology.

Response to Active Standing of Heart Beat Interval, Systolic Blood Volume and Systolic Blood Pressure: Recurrence Plot Analysis

Recurrence quantitative analysis (RQA) indexes of beat-to-beat heart-beat interval and systolic blood pressure (SBP) have helped to understand the dynamical response to active standing. The peripheral blood volume is another variable of the cardiovascular control system with a crucial role during active standing since re-distribution of blood volume is necessary to counteract the gravity force and to provide enough blood supply to vital organs. Beat-to-beat photoplethysmographic systolic blood volume (SBV) oscillations may be useful to study the cardiovascular control if it is considered as a regulatory system with relevant local differences compared to blood pressure regulation. There are no previous reports of the SBV dynamical response to active standing. In this work we study simultaneously the dynamical response of heart-beat interval, SBP and SBV to active standing through comparison of RQA indexes evaluated during supine position and during active standing in 19 healthy volunteers. We show that in response to orthostatic stress, SBV oscillations have dynamic changes similar, but not identical, to SBP and the heart-beat interval. This suggests that these three variables are complementary for a better evaluation of the cardiovascular dynamics.

Multifractal Analysis Reveals Decreased Non-linearity and Stronger Anticorrelations in Heart Period Fluctuations of Fibromyalgia Patients

Objective: To characterize the multifractal behavior of the beat to beat heart-period or RR fluctuations in fibromyalgia patients (FM) in comparison with healthy-matched subjects. Methods: Multifractral detrended fluctuation analysis (MDFA) was used to study multifractality in heartbeat times-series from 30 female healthy subjects and 30 female patients with fibromyalgia during day and night periods.The multifractal changes as derived from the magnitude and sign analysis of these RR fluctuations were also assessed. Results: The RR fluctuations dynamics of healthy subjects showed a broad multifractal spectrum. By contrast, a noticeable decrease in multifractality and non-linearity was observed for patients with fibromyalgia. In addition, the spectra corresponding to FM subjects were located on the average to the right of the spectra of healthy individuals, indicating that the local scaling exponents reflect a smoother behavior compared to healthy dynamics. Moreover, the multifractal analysis as applied to the magnitude and sign heartbeat series confirmed that, in addition to a decreased nonlinearity, fibromyalgia patients presented stronger anticorrelation in directionality, which did not remain invariant for small or rather larger fluctuations as it occurred in healthy subjects. Conclusion: When compared to healthy controls, fibromyalgia patients display decreased nonlinearity and stronger anticorrelations in heart period fluctuations. These findings reinforce the hypothesis of the potential role of the dysfunctional autonomic nervous system in the pathogenesis of fibromyalgia.

Intra‐beat Scaling Properties of Cardiac Arrhythmias and Sudden Cardiac Death

We applied detrended fluctuation analysis (DFA) to characterize the intra‐beat scaling dynamics of electrocardiographic (ECG) recordings from the PhysioNet Sudden Cardiac Death Holter Database. The main finding of this contribution is that, in such recordings involving different types of arrhythmias; the ECG waveform, besides showing a less‐random intra‐beat dynamics, becomes more regular during bigeminy, ventricular tachycardia (VT) or even atrial fibrillation (AFIB) and ventricular fibrillation (VF) despite the appearance of erratic traces. Thus, notwithstanding that these cardiac rhythm abnormalities are generally considered as irregular and some of them generated by random impulses or wavefronts, the intra‐beat scaling properties suggest that regularity dominates the underlying mechanisms of arrhythmias. Among other explanations, this may result from shorted or restricted ‐less complex‐ pathways of conduction of the electrical activity within the ventricles.