Systolic and diastolic time intervals during spontaneous angina

Ferro, G; Piscione, Federico; Carella, G; Betocchi, Sandro; Spinelli, Lorenzo; Chiariello, Massimo

doi:10.1002/clc.4960071106

Cited by 11 publications

(3 citation statements)

References 11 publications

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“…Systole (heart contraction) and diastole (heart relaxation), apart from heartbeat which primarily reflects the electrical activity of the heart, are fundamental mechanical cardiac activities. In addition to heartbeat interval (RRI), the systole time interval (STI) and diastole time interval (DTI) are also potentially applicable for examining cardiovascular conditions, as evidenced by a couple of publications [7][8][9][10][11][12][13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Measuring Electromechanical Coupling in Patients with Coronary Artery Disease and Healthy Subjects

Ji¹,

Liu

et al. 2016

Entropy

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Coronary artery disease (CAD) is the most common cause of death globally. To detect CAD noninvasively at an early stage before clinical symptoms occur is still nowadays challenging. Analysis of the variation of heartbeat interval (RRI) opens a new avenue for evaluating the functional change of cardiovascular system which is accepted to occur at the subclinical stage of CAD. In addition, systolic time interval (STI) and diastolic time interval (DTI) also show potential. There may be coupling in these electromechanical time series due to their physiological connection. However, to the best of our knowledge no publication has systematically investigated how can the coupling be measured and how it changes in CAD patients. In this study, we enrolled 39 CAD patients and 36 healthy subjects and for each subject the electrocardiogram (ECG) and photoplethysmography (PPG) signals were recorded simultaneously for 5 min. The RRI series, STI series, and DTI series were constructed, respectively. We used linear cross correlation (CC), coherence function (CF), as well as nonlinear mutual information (MI), cross conditional entropy (XCE), cross sample entropy (XSampEn), and cross fuzzy entropy (XFuzzyEn) to analyse the bivariate RRI-DTI coupling, RRI-STI coupling, and STI-DTI coupling, respectively. Our results suggest that the linear CC and CF generally have no significant difference between the two groups for all three types of bivariate coupling. The MI only shows weak change in RRI-DTI coupling. By comparison, the three entropy-based coupling measurements show significantly decreased coupling in CAD patients except XSampEn for RRI-DTI coupling (less significant) and XCE for STI-DTI and RRI-STI coupling (not significant). Additionally, the XFuzzyEn performs best as it was still significant if we further applied the Bonferroni correction in our statistical analysis. Our study indicates that the intrinsic electromechanical coupling is most probably nonlinear and can better be measured by nonlinear entropy-based measurements especially the XFuzzyEn. Besides, CAD patients are accompanied by a loss of electromechanical coupling. Our results suggest that cardiac electromechanical coupling may potentially serve as a noninvasive diagnostic tool for CAD.

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Section: Introductionmentioning

confidence: 99%

Measuring Electromechanical Coupling in Patients with Coronary Artery Disease and Healthy Subjects

Ji¹,

Liu

et al. 2016

Entropy

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“…of DP was also found in spontaneous angina [6], dilated cardiomyopathy [7], and exercise-induced increased pulmonary artery pressure [8]. In addition to these wellstudied cardiac electrical and mechanical time intervals, there is yet another time interval characterizing the delay between the onset of the electrical activation of the ventricle and the onset of its contraction-the electro-mechanical delay (EMD) [9], [10].…”

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confidence: 96%

Variability of Cardiac Electromechanical Delay With Application to the Noninvasive Detection of Coronary Artery Disease

Wang

Liu

et al. 2019

IEEE Access

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Heart rate variability (HRV), systolic period variability (SPV), and diastolic period variability (DPV) have shown potential for assessing cardiac function. It is unknown whether the time delay between the myocardial electrical and mechanical activities (i.e., electromechanical delay, EMD) also possesses variability, and if it does, whether this EMD variability (EMDV) could render additional value for cardiac function assessment. In this paper, we extracted the beat-to-beat EMD from 5-min simultaneously recorded electrocardiogram and phonocardiogram signals in 30 patients with coronary artery disease (CAD) and 30 healthy control subjects, and studied its variability using the same methods as applied for HRV including time-domain measures [mean and standard deviation (SD)], frequency-domain measures [normalized lowand high-frequency (LFn, HFn) and LF/HF)], and nonlinear measures [sample entropy (SampEn), permutation entropy (PE), and dynamical patterns]. In addition, we examined whether the addition of EMDV could offer improved performance for distinguishing between the two groups compared to using the HRV, SPV, and DPV features. Support vector machine with 10-fold cross-validation was used for classification. Results showed increased SD of SPV, increased mean, SD and decreased SampEn of EMDV in CAD patients. Besides, the dynamical pattern analysis showed that CAD patients had significantly increased fluctuated patterns and decreased monotonous patterns in EMDV. In particular, the addition of EMDV indices dramatically increased the classification accuracy from 0.729 based on HRV, SPV, and DPV features to 0.958. Our results suggest promising of the EMDV analysis that could potentially be helpful for detecting CAD noninvasively. INDEX TERMS Electromechanical delay (EMD), heart rate variability (HRV), systolic period variability (SPV), diastolic period variability (DPV), dynamical patterns, noninvasive detection, coronary artery disease (CAD). I. INTRODUCTION Electrocardiogram (ECG) and phonocardiogram (PCG) measurements are two commonly-used non-invasive and non-intrusive methods for diagnosing cardiac diseases. ECG reflects the cardiac electrical activity while PCG records heart sounds produced by myocardial mechanical The associate editor coordinating the review of this manuscript and approving it for publication was György Eigner. activities (i.e., contraction and relaxation). One cardiac cycle is composed of two mechanical intervals, namely, systolic period (SP) and diastolic period (DP). Previous studies have found reduced mean cardiac cycle (i.e., mean RR intervals in ECG) in diabetes [1] and patients with chronic congestive heart failure [2]. Besides, researchers also found that abnormal SP and DP could indicate mechanical abnormalities of ventricular function [3]. Prolonged SP and shortened DP were found in children with heart failure [4], [5], and the shortening

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“…However, few data are available regarding its effects on cardiomechanical events. A transient paradoxical splitting of the second heart sound may oc cur during angina, suggesting a prolongation of left ventricular contraction related to asyn ergy [8], Furthermore, it has been observed that during spontaneous angina, accompa-nied by an increase in heart rate and blood pressure, the electromechanical systole is prolonged; this leads to a decrease in dia stolic perfusion time which, in turn, could be responsible for a self-maintaining worsening of ischemia [9], The effects of autonomic mechanisms and particularly of increased vagal tone on time intervals is not yet com pletely understood. The present study was undertaken to determine the relative effects on electromechanical events and electrocar diographic changes of acute episodes of tran sient myocardial ischemia.…”

Section: Introductionmentioning

confidence: 99%

Electromechanical Events during Spontaneous Angina

et al. 1988

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The electromechanical events occurring during acute myocardial ischemia were assessed in 10 patients who developed spontaneous angina during cardiac catheterization. Aortic pressure and electrocardiogram were recorded, and heart rate and systolic and diastolic time intervals were measured under control conditions, at the onset of angina and during the relief of chest pain. In 5 patients spontaneous angina was accompanied by an increase in heart rate and systemic arterial pressure and by ST segment changes in anterior or anterolateral precordial leads. Diastolic time, expressed as percent of cardiac cycle, shortened from 48.8 ± 3.6% at rest to 33.6 ± 4.8% (p < 0.01) at the onset of angina, as a consequence of a significant increase in both electromechanical systole and heart rate, and returned to control values within 10 min after sublingual nitroglycerin. In the remaining 5 patients, spontaneous angina was accompanied by a decrease in heart rate and systemic arterial pressure and by ST segment changes in the inferior or inferolateral leads. The diastolic time increased significantly (p < 0.05) from 39.4 ± 6.1 % at rest to 47.8 ± 9% at the onset of angina, as a consequence of a significant decrease in heart rate and a slight decrease in electromechanical systole. Since coronary perfusion takes place mainly during diastole, our results suggest that the reflex increase in adrenergic tone may worsen myocardial ischemia by affecting diastolic perfusion time. In contrast, the increase in vagal tone may contribute to spontaneous relief of angina by prolonging diastolic perfusion time.

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Systolic and diastolic time intervals during spontaneous angina

Cited by 11 publications

References 11 publications

Measuring Electromechanical Coupling in Patients with Coronary Artery Disease and Healthy Subjects

Measuring Electromechanical Coupling in Patients with Coronary Artery Disease and Healthy Subjects

Variability of Cardiac Electromechanical Delay With Application to the Noninvasive Detection of Coronary Artery Disease

Electromechanical Events during Spontaneous Angina

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