Realtime Multichannel System for Beat to Beat QT Interval Variability

The measurement of beat-to-beat QT interval variability (QTV) shows clinical promise for identifying several types of cardiac pathology. However, until now, there has been no device capable of displaying, in real time on a beattobeat basis, changes in QTV in all 12 conventional leads in a continuously monitored patient. While several software programs have been designed to analyze QTV, heretofore, such programs have all involved only a few channels (at most) and/or have required laborious user interaction or offline calculations and postprocessing, limiting their clinical utility. This paper describes a PC-based ECG software program that in real time, acquires, analyzes and displays QTV and also PQ interval variability (PQV) in each of the eight independent channels that constitute the 12lead conventional ECG. The system also processes certain related signals that are derived from singular value decomposition and that help to reduce the overall effects of noise on the realtime QTV and PQV results

Reliability and Reproducibility of Advanced ECG Parameters in Month-to-Month and Year-to-Year Recordings in Healthy Subjects

Advanced resting ECG parameters such the spatial mean QRS-T angle and the QT variability index (QTVI) have important diagnostic and prognostic utility, but their reliability and reproducibility (R&R) are not well characterized. We hypothesized that the spatial QRS-T angle would have relatively higher R&R than parameters such as QTVI that are more responsive to transient changes in the autonomic nervous system. The R&R of several conventional and advanced ECG para-meters were studied via intraclass correlation coefficients (ICCs) and coefficients of variation (CVs) in: (1) 15 supine healthy subjects from month-to-month; (2) 27 supine healthy subjects from year-to-year; and (3) 25 subjects after transition from the supine to the seated posture. As hypothesized, for the spatial mean QRS-T angle and many conventional ECG parameters, ICCs we-re higher, and CVs lower than QTVI, suggesting that the former parameters are more reliable and reproducible

Coronary Artery Disease Alters Ventricular Repolarization Dynamics in Type 2 Diabetes

Ventricular repolarization dynamics (VRD) is an important predictor of outcome in diabetes. We examined the potential impact of coronary artery disease (CAD) on VRD in type 2 diabetic patients. We recorded 5-min high-resolution resting electrocardiograms (ECG) in 38 diabetic patients undergoing elective coronary angiography, and in 38 age- and gender- matched apparently healthy subjects (Controls). Using leads I and II, time-domain indices of VRD were calculated. Coronary angiography was regarded as positive if a 350% stenosis was found. Angiography was positive in 21 diabetic patients (55%). Patients with CAD had a significantly higher degree of VRD than Controls (SDNN(QT): 15.81+/-7.22 ms vs. 8.94+/-6.04 ms; P <0.001, rMSSD(QT): 21.02k7.07 ms vs. 11.18k7.45 ms; P <0.001). VRD in diabetic patients with negative angiograms did not differ from VRD in Controls (SDNN(QT): 8.94+/-6.04 ms vs. 7.44+/-5.72 ms; P=0.67, rMSSD(QT): 11.18+/-7.45 ms vs. 10.22+/-5.35 ms; P=O. 82). CAD increases VRD in patients with type 2 diabetes. Therefore, changes in ventricular repolarization in diabetic patients may be due to silent CAD rather than to diabetes per se

Construction of a Resting High Fidelity ECG "SuperScore" for Management and Screening of Heart Disease

Resting conventional ECG is notoriously insensitive for detecting coronary artery disease (CAD) and only nominally useful in screening for cardiomyopathy (CM). Similarly, conventional exercise stress test ECG is both time- and labor-consuming and its accuracy in identifying CAD is suboptimal for use in population screening. We retrospectively investigated the accuracy of several advanced resting electrocardiographic (ECG) parameters, both alone and in combination, for detecting CAD and cardiomyopathy (CM)

Conventional QT variability measurement vs. template matching techniques: comparison of performance using simulated and real ECG

Increased beat-to-beat variability in the QT interval (QTV) of ECG has been associated with increased risk for sudden cardiac death, but its measurement is technically challenging and currently not standardized. The aim of this study was to investigate the performance of commonly used beat-to-beat QT interval measurement algorithms. Three different methods (conventional, template stretching and template time shifting) were subjected to simulated data featuring typical ECG recording issues (broadband noise, baseline wander, amplitude modulation) and real short-term ECG of patients before and after infusion of sotalol, a QT interval prolonging drug. Among the three algorithms, the conventional algorithm was most susceptible to noise whereas the template time shifting algorithm showed superior overall performance on simulated and real ECG. None of the algorithms was able to detect increased beat-to-beat QT interval variability after sotalol infusion despite marked prolongation of the average QT interval. The QTV estimates of all three algorithms were inversely correlated with the amplitude of the T wave. In conclusion, template matching algorithms, in particular the time shifting algorithm, are recommended for beat-to-beat variability measurement of QT interval in body surface ECG. Recording noise, T wave amplitude and the beat-rejection strategy are important factors of QTV measurement and require further investigation.Mathias Baumert, Vito Starc and Alberto Port

Accuracy of advanced versus strictly conventional 12-lead ECG for detection and screening of coronary artery disease, left ventricular hypertrophy and left ventricular systolic dysfunction

<p>Abstract</p> <p>Background</p> <p>Resting conventional 12-lead ECG has low sensitivity for detection of coronary artery disease (CAD) and left ventricular hypertrophy (LVH) and low positive predictive value (PPV) for prediction of left ventricular systolic dysfunction (LVSD). We hypothesized that a ~5-min resting 12-lead <it>advanced </it>ECG test ("A-ECG") that combined results from both the advanced and conventional ECG could more accurately screen for these conditions than strictly conventional ECG.</p> <p>Methods</p> <p>Results from nearly every conventional and advanced resting ECG parameter known from the literature to have diagnostic or predictive value were first retrospectively evaluated in 418 healthy controls and 290 patients with imaging-proven CAD, LVH and/or LVSD. Each ECG parameter was examined for potential inclusion within multi-parameter A-ECG scores derived from multivariate regression models that were designed to optimally screen for disease in general or LVSD in particular. The performance of the best retrospectively-validated A-ECG scores was then compared against that of optimized pooled criteria from the strictly conventional ECG in a test set of 315 additional individuals.</p> <p>Results</p> <p>Compared to optimized pooled criteria from the strictly conventional ECG, a 7-parameter A-ECG score validated in the training set increased the sensitivity of resting ECG for identifying disease in the test set from 78% (72-84%) to 92% (88-96%) (P < 0.0001) while also increasing specificity from 85% (77-91%) to 94% (88-98%) (P < 0.05). In diseased patients, another 5-parameter A-ECG score increased the PPV of ECG for LVSD from 53% (41-65%) to 92% (78-98%) (P < 0.0001) without compromising related negative predictive value.</p> <p>Conclusion</p> <p>Resting 12-lead A-ECG scoring is more accurate than strictly conventional ECG in screening for CAD, LVH and LVSD.</p

Pair-wise comparison of algorithms.

<p>Left: Scatter plots comparing QTV obtained with three different algorithms from real ECG recordings of patients before and after sotalol infusion (line of identity in grey). The overall agreement between all three algorithms (intra-class correlation coefficient) was 0.31. Right: Bland-Altman plots of absolute QTV differences observed between of algorithms.</p

Accuracy of QT measurement algorithms.

<p>Data are expressed as standard deviation of beat-to-beat QT interval as a function of T amplitude acquisition range measured during simulated broadband noise (A), periodic baseline wander (B) and periodic amplitude modulations (C), using a conventional QT measurement algorithm (black dots), the template stretching algorithm (red diamonds) and template time shifting algorithm (blue squares).</p

Relation between QTV and T wave amplitude.

<p>Results were obtained with the conventional (A), template stretching (B) and template time shifting (C) algorithms and show a significant negative correlation between QTV and T wave amplitude, contributing between 10% and 30% to the overall variance in QTV that was observed across patient ECGs.</p