Probability of ventricular fibrillation: allometric model based on the ST deviation

<p>Abstract</p> <p>Background</p> <p>Allometry, in general biology, measures the relative growth of a part in relation to the whole living organism. Using reported clinical data, we apply this concept for evaluating the probability of ventricular fibrillation based on the electrocardiographic ST-segment deviation values.</p> <p>Methods</p> <p>Data collected by previous reports were used to fit an allometric model in order to estimate ventricular fibrillation probability. Patients presenting either with death, myocardial infarction or unstable angina were included to calculate such probability as, <it>VF</it>_{<it>p </it>}<it>= δ + β (ST)</it>, for three different ST deviations. The coefficients <it>δ </it>and <it>β </it>were obtained as the best fit to the clinical data extended over observational periods of 1, 6, 12 and 48 months from occurrence of the first reported chest pain accompanied by ST deviation.</p> <p>Results</p> <p>By application of the above equation in log-log representation, the fitting procedure produced the following overall coefficients: Average <it>β </it>= 0.46, with a maximum = 0.62 and a minimum = 0.42; Average <it>δ </it>= 1.28, with a maximum = 1.79 and a minimum = 0.92. For a 2 mm ST-deviation, the full range of predicted ventricular fibrillation probability extended from about 13% at 1 month up to 86% at 4 years after the original cardiac event.</p> <p>Conclusions</p> <p>These results, at least preliminarily, appear acceptable and still call for full clinical test. The model seems promising, especially if other parameters were taken into account, such as blood cardiac enzyme concentrations, ischemic or infarcted epicardial areas or ejection fraction. It is concluded, considering these results and a few references found in the literature, that the allometric model shows good predictive practical value to aid medical decisions.</p

Estudio de la entropía y complejidad wavelet en la fragmentación del complejo QRS

Hemos evaluado la señal del ECG a partir de su entropía normalizada (H) y la complejidad wavelet (C) de complejos QRS, utilizando la transformada wavelet continua, como un método eficaz para cuantificar alteraciones anormales en la actividad eléctrica-cardiaca en pacientes post IM.Facultad de Ingenierí

Study of QRS-Loop Parameters and Conventional ST-T Indexes for Identification of Ischemic and Healthy Subjects

Abstrac

Spatio-Temporal Analysis of Acute Myocardial Ischaemia Based on Entropy&ndash;Complexity Plane

Myocardial ischaemia is a decompensation of the oxygen supply and demand ratio, often caused by coronary atherosclerosis. During the initial stage of ischaemia, the electrical activity of the heart is disrupted, increasing the risk of malignant arrhythmias. The aim of this study is to understand the differential behaviour of the ECG during occlusion of both the left anterior descending (LAD) and right anterior coronary artery (RCA), respectively, using spatio-temporal quantifiers from information theory. A standard 12-lead ECG was recorded for each patient in the database. The control condition was obtained initially. Then, a percutaneous transluminal coronary angioplasty procedure (PTCA), which encompassed the occlusion/reperfusion period, was performed. To evaluate information quantifiers, the Bandt and Pompe permutation method was used to estimate the probability distribution associated with the electrocardiographic vector modulus. Subsequently, we analysed the positioning in the H&times;C causal plane for the control and ischaemia. In LAD occlusion, decreased entropy and increased complexity can be seen, i.e., the behaviour is more predictable with an increase in the degree of complexity of the system. RCA occlusion had the opposite effects, i.e., the phenomenon is less predictable and exhibits a lower degree of organisation. Finally, both entropy and complexity decrease during the reperfusion phase in LAD and RCA cases

Depolarization spatial variance as a cardiac dyssynchrony descriptor

Ventricular depolarization dispersion refers mainly to heterogeneity in interlead QRS durations. Here, we propose the spatial variance (SVd) to describe depolarization dispersion about a mean QRS morphology. We hypothesize that waveform changes can be more accurate than interval changes at measuring QRS heterogeneity, and less sensitive to delineation errors. To prove this, SVd was computed on 36 dyssyn-chrony patients either in sinus rhythm (SVdB) or under nHB (SVdHB), and on 32 control subjects with native conduction (SVdN). In the normal ECG, there are interlead sets that produce maximal (SVdNmax) and minimal (SVdNmin) spatial variance. In Baseline patients, SVdB significantly increased from controls in the minimal variance situation (p < 0.005), deviating one or more leads from the normal morphology (similar in all the ensemble) and consequently increasing the interlead distance. The opposite held for the maximal variance situation, where it was expected a wide span of morphologies in health, there was a tendency to stacking in morphologies at baseline (p<0.005). In both cases nHB induced QRS normalization, demonstrated by the return of SVdHB towards controls SVdN (p = NS). However, QRS narrowing not always accompanied morphological changes. The average rate of QRS normalization was 84% and 89% for SVdNmax and SVdNmin respectively while the rate of QRS narrowing equaled 71% in a multilead approach and performed worse than SVd at baseline-nHB separation. Ensembles with minimal interlead distance produced the best AUC values (aVR-V1, I-aVF-V6, I-II-aVF-V6). In conclusion, SVd may complement QRS width in the electrocardiographic assessment of dyssynchrony.Fil: Bonomini, Maria Paula. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Saavedra 15. Instituto Argentino de Matemática Alberto Calderón; ArgentinaFil: Ortega, Daniel F.. Clínica San Camilo; Argentina. Universidad Austral. Hospital Universitario Austral; ArgentinaFil: Barja, Luis D.. Universidad Austral. Hospital Universitario Austral; Argentina. Clínica San Camilo; ArgentinaFil: Mangani, Nicolas. Clínica San Camilo; Argentina. Universidad Austral. Hospital Universitario Austral; ArgentinaFil: Arini, Pedro David. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Saavedra 15. Instituto Argentino de Matemática Alberto Calderón; Argentin