Multifractality in heartbeat dynamics in patients undergoing beating-heart myocardial revascularization

Altered Heart Rate Turbulence and Variability Parameters Predict 1-Year Mortality in Heart Failure with Preserved Ejection Fraction

BACKGROUND

Heart failure with preserved ejection fraction (HFpEF) is a complex and heterogeneous clinical syndrome. In the absence of effective and potent treatment strategies, the main challenge in HFpEF management remains the availability of strong predictors of unfavourable outcomes. In our study, we sought to evaluate the potential prognostic value of heart rate turbulence (HRT) and variability (HRV) parameters on mortality in ambulatory HFpEF patients.

METHODS

This was a case-control study comparing HRT and HRV parameters in HFpEF survivors vs. non-survivors. Patients from the RESPOND Heart Failure Registry with HFpEF who underwent 24 h ECG monitoring (Holter) were included; HRT parameters (i.e., turbulence onset (TO) and turbulence slope (TS)) and HRV parameters (i.e., standard deviation of NN intervals (SDNN)) derived from 24 h Holter ECGs were calculated in patients who died within 12 months, and compared to their age-, gender-, LVEF-, ECHO-, aetiology-, and therapy-matched alive controls.

RESULTS

A total of 22 patients (mean age 80 ± 7 years, 18% female, mean LVEF 57 ± 9%) were included in the final analysis. In deceased patients, values of TO were significantly higher, and values of TS and SDNN were significantly lower as compared to survivors.

CONCLUSIONS

HRT and HRV parameters have the ability to differentiate individuals with HFpEF who are at the greatest risk of unfavourable outcomes. The extent of autonomic disbalance as determined by HRT and HRV could potentially assist in the prognostic assessment and risk stratification of HFpEF patients.

The fractal heart - embracing mathematics in the cardiology clinic

For clinicians grappling with quantifying the complex spatial and temporal patterns of cardiac structure and function (such as myocardial trabeculae, coronary microvascular anatomy, tissue perfusion, myocyte histology, electrical conduction, heart rate, and blood-pressure variability), fractal analysis is a powerful, but still underused, mathematical tool. In this Perspectives article, we explain some fundamental principles of fractal geometry and place it in a familiar medical setting. We summarize studies in the cardiovascular sciences in which fractal methods have successfully been used to investigate disease mechanisms, and suggest potential future clinical roles in cardiac imaging and time series measurements. We believe that clinical researchers can deploy innovative fractal solutions to common cardiac problems that might ultimately translate into advancements for patient care.

A System for the Comprehensive Quantification of Real-Time Heartbeat Activity

Heartbeat can reflect the dynamics of the heart control system, and it is also a commonly used index in health monitoring, exercise load calculation and psycho-physiological arousal quantification. This paper fuses three heartbeat measures, i.e. the running mean, the range of local Hurst exponents and the relative fluctuation, to construct a system that can automatically quantify the heartbeat activity both from its static aspect and from its dynamic aspect in a real-time manner. Experiments show that the system can reveal the heartbeat arousal difference between physically relaxed status and exercise-loaded status. When the affective heartbeat data in literature are quantified by this system, the results also show the capability of the system to illustrate psycho-physiological arousal.

ICU Blood Pressure Variability May Predict Nadir of Respiratory Depression After Coronary Artery Bypass Surgery

Objectives: Surgical stress induces alterations on sympathovagal balance that can be determined through assessment of blood pressure variability. Coronary artery bypass graft surgery (CABG) is associated with postoperative respiratory depression. In this study we aimed at investigating ICU blood pressure variability and other perioperative parameters that could predict the nadir of postoperative respiratory function impairment.

Methods: This prospective observational study evaluated 44 coronary artery disease patients subjected to coronary artery bypass surgery (CABG) with cardiopulmonary bypass (CPB). At the ICU, mean arterial pressure (MAP) was monitored every 30 min for 3 days. MAP variability was evaluated through: standard deviation (SD), coefficient of variation (CV), variation independent of mean (VIM), and average successive variability (ASV). Respiratory function was assessed through maximal inspiratory (MIP) and expiratory (MEP) pressures and peak expiratory flow (PEF) determined 1 day before surgery and on the postoperative days 3rd to 7th. Intraoperative parameters (volume of cardioplegia, CPB duration, aortic cross-clamp time, number of grafts) were also monitored.

Results: Since, we aimed at studying patients without confounding effects of postoperative complications on respiratory function, we had enrolled a cohort of low risk EuroSCORE (European System for Cardiac Operative Risk Evaluation) with < 2. Respiratory parameters MIP, MEP, and PEF were significantly depressed for 4–5 days postoperatively. Of all MAP variability parameters, the ASV had a significant good positive Spearman correlation (rho coefficients ranging from 0.45 to 0.65, p < 0.01) with the 3-day nadir of PEF after cardiac surgery. Also, CV and VIM of MAP were significantly associated with nadir days of MEP and PEF. None of the intraoperative parameters had any correlation with the postoperative respiratory depression.

Conclusions: Variability parameters ASV, CV, and VIM of the MAP monitored at ICU may have predictive value for the depression of respiratory function after cardiac surgery as determined by peak expiratory flow and maximal expiratory pressure.

ClinicalTrials.gov Identifier: NCT02074371.