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

Kšela, Juš; Avbelj, Viktor; Kališnik, Jurij Matija

doi:10.1016/j.compbiomed.2015.02.012

Cited by 12 publications

(14 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Multifractal analysis, which produces a range of exponents (Fig. 6c), has been used to distinguish between healthy and diseased heart signals in heart failure and coronary artery disease64, 65, and to measure the effect of percutaneous coronary intervention and open-heart surgery on the behaviour of the human heartbeat66.…”

Section: Fractal Applications In Cardiologymentioning

confidence: 99%

“…For fractal analysis of time series in patients, similar challenges exist. For heart-rate variability analysis, some fractal techniques still require the preprocessing or editing of premature beats in the recordings68, and particular methods remain sensitive to artefacts and alterations in recording conditions (such as duration, body temperature, body position, free-breathing versus controlled-breathing and physical activities69, and effect of drug therapy and dosage alteration66). These factors can all substantially affect short-term metrics, making comparisons between studies challenging.…”

Section: Practical Challengesmentioning

confidence: 99%

See 1 more Smart Citation

The fractal heart — embracing mathematics in the cardiology clinic

et al. 2016

View full text Add to dashboard Cite

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.

show abstract

Section: Fractal Applications In Cardiologymentioning

confidence: 99%

Section: Practical Challengesmentioning

confidence: 99%

The fractal heart — embracing mathematics in the cardiology clinic

et al. 2016

View full text Add to dashboard Cite

show abstract

“…It was evidenced that the complexity degree of normal cardiac dynamics was higher than the dynamic with acute pathologies for all Holters, showing quantitatively how the cardiac dynamics can be sharpen. This new methodology constitutes a new way to assess the complexity degree of cardiac dynamics, which simplify other methods of assessment [33] [34]. This work is based on the theoretical physics method [35], in which from inductions with few cases, a simplification of the phenomenon studied is achieved and general principles that characterize the phenomenon are found, for subsequently establishing a general methodology for all cases of universe.…”

Section: Discussionmentioning

confidence: 99%

Physical Mathematical Evaluation of the Cardiac Dynamic Applying the Zipf-Mandelbrot Law

Rodríguez¹,

Prieto²,

Correa³

et al. 2015

JMP

View full text Add to dashboard Cite

Introduction: The law of Zipf-Mandelbrot is a power law, which has been observed in natural languages. A mathematical diagnosis of fetal cardiac dynamics has been developed with this law. Objective: To develop a methodology for diagnostic aid to assess the degree of complexity of adult cardiac dynamics by Zipf-Mandelbrot law. Methodology: A mathematical induction was done for this; two groups of Holter recordings were selected: 11 with normal diagnosis and 11 with acute disease of each group, one Holter of each group was chosen for the induction, the law of ZipfMandelbrot was applied to evaluate the degree of complexity of each Holter, searching similarities or differences between the dynamics. A blind study was done with 20 Holters calculating sensitivity, specificity and the coefficient kappa. Results: The complexity grade of a normal cardiac dynamics varied between 0.9483 and 0.7046, and for an acute dynamic between 0.6707 and 0.4228. Conclusions: A new physical mathematical methodology for diagnostic aid was developed; it showed that the degree of complexity of normal cardiac dynamics was higher than those with acute disease, showing quantitatively how cardiac dynamics can evolve to acute state.

show abstract

“…Surgical stress induces alterations of blood pressure variability as result of neurohumoral and autonomic reactions to stress (Souza Neto et al, 2004 ). Perioperative blood pressure variability has been associated with 30-day mortality after cardiac surgery (Aronson et al, 2011 ), possible mechanisms including autonomic imbalance (Pantoni et al, 2014 ), sympathetic overdrive, and parasympathetic withdrawal (Patron et al, 2014 ; Ksela et al, 2015 ).…”

Section: Introductionmentioning

confidence: 99%

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

Costa

Lima

et al. 2016

Front. Neurosci.

View full text Add to dashboard Cite

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.

show abstract

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

Cited by 12 publications

References 39 publications

The fractal heart — embracing mathematics in the cardiology clinic

The fractal heart — embracing mathematics in the cardiology clinic

Physical Mathematical Evaluation of the Cardiac Dynamic Applying the Zipf-Mandelbrot Law

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

Contact Info

Product

Resources

About