Comparison of automated interval measurements by widely used algorithms in digital electrocardiographs.

BACKGROUND: Automated measurements of electrocardiographic (ECG) intervals by current-generation digital electrocardiographs are critical to computer-based ECG diagnostic statements, to serial comparison of ECGs, and to epidemiological studies of ECG findings in populations. A previous study demonstrated generally small but often significant systematic differences among 4 algorithms widely used for automated ECG in the United States and that measurement differences could be related to the degree of abnormality of the underlying tracing. Since that publication, some algorithms have been adjusted, whereas other large manufacturers of automated ECGs have asked to participate in an extension of this comparison. METHODS: Seven widely used automated algorithms for computer-based interpretation participated in this blinded study of 800 digitized ECGs provided by the Cardiac Safety Research Consortium. All tracings were different from the study of 4 algorithms reported in 2014, and the selected population was heavily weighted toward groups with known effects on the QT interval: included were 200 normal subjects, 200 normal subjects receiving moxifloxacin as part of an active control arm of thorough QT studies, 200 subjects with genetically proved long QT syndrome type 1 (LQT1), and 200 subjects with genetically proved long QT syndrome Type 2 (LQT2). RESULTS: For the entire population of 800 subjects, pairwise differences between algorithms for each mean interval value were clinically small, even where statistically significant, ranging from 0.2 to 3.6milliseconds for the PR interval, 0.1 to 8.1milliseconds for QRS duration, and 0.1 to 9.3milliseconds for QT interval. The mean value of all paired differences among algorithms was higher in the long QT groups than in normals for both QRS duration and QT intervals. Differences in mean QRS duration ranged from 0.2 to 13.3milliseconds in the LQT1 subjects and from 0.2 to 11.0milliseconds in the LQT2 subjects. Differences in measured QT duration (not corrected for heart rate) ranged from 0.2 to 10.5milliseconds in the LQT1 subjects and from 0.9 to 12.8milliseconds in the LQT2 subjects. CONCLUSIONS: Among current-generation computer-based electrocardiographs, clinically small but statistically significant differences exist between ECG interval measurements by individual algorithms. Measurement differences between algorithms for QRS duration and for QT interval are larger in long QT interval subjects than in normal subjects. Comparisons of population study norms should be aware of small systematic differences in interval measurements due to different algorithm methodologies, within-individual interval measurement comparisons should use comparable methods, and further attempts to harmonize interval measurement methodologies are warranted.

An evaluation of multiple algorithms for the measurement of the heart rate corrected JTpeak interval.

Interest in the effects of drugs on the heart rate-corrected JTpeak (JTpc) interval from the body-surface ECG has spawned an increasing number of scientific investigations in the field of regulatory sciences, and more specifically in the context of the Comprehensive in vitro Proarrhythmia Assay (CiPA) initiative. We conducted a novel initiative to evaluate the role of automatic JTpc measurement technologies by comparing their ability to distinguish multi- from single-channel blocking drugs. A set of 5232 ECGs was shared by the FDA (through the Telemetric and Holter ECG Warehouse) with 3 ECG device companies (AMPS, Mortara, and Philips). We evaluated the differences in drug-concentration effects on these measurements between the commercial and the FDA technologies. We provide a description of the drug-induced placebo-corrected changes from baseline for dofetilide, quinidine, ranolazine, and verapamil, and discuss the various differences across all technologies. The results revealed only small differences between measurement technologies evaluated in this study. It also confirms that, in this dataset, the JTpc interval distinguishes between multi- and single-channel (hERG) blocking drugs when evaluating the effects of dofetilide, quinidine, ranolazine, and verapamil. However, in the case of quinidine and dofetilide, we noticed a poor consistency across technologies because of the lack of standard definitions for the location of the peak of the T-wave (T-apex) when the T-wave morphology is abnormal.

The J to T-peak interval as a biomarker in drug safety studies: A method of accuracy assessment applied to two algorithms.

OBJECTIVES: To evaluate performance of J-to-T-peak (JTP) measurements of 12-lead ECGs, in a five-arm study using drugs with various levels of electrolyte channel block. METHODS: The novel evaluation method distinguishes between different aspects of measurement. "Random noise" is the variability among repeated measurements made without changing the conditions. "Context noise" is the variability of changes in context of the measurement, e.g. T-wave morphology, autonomic nervous system state. RESULTS: The average random noise of our RR-corrected JTPc measurements in standard deviations was 3.0 ms and not dependent on the drug. The average context noise was 4.0 ms for ranolazine, verapamil, and placebo, and 8.8 ms for dofetilide and quinidine. Measurement consistency is corroborated by linear fit confidence intervals of baseline- and placebo-corrected JTPc versus drug concentration. CONCLUSIONS: Systematic differences were found in JTPc drug response between the Mortara method and published data. Residual signal component in the context noise may influence future study design.

Noninvasive quantification of blood potassium concentration from ECG in hemodialysis patients.

Blood potassium concentration ([K+]) influences the electrocardiogram (ECG), particularly T-wave morphology. We developed a new method to quantify [K+] from T-wave analysis and tested its clinical applicability on data from dialysis patients, in whom [K+] varies significantly during the therapy. To elucidate the mechanism linking [K+] and T-wave, we also analysed data from long QT syndrome type 2 (LQT2) patients, testing the hypothesis that our method would have underestimated [K+] in these patients. Moreover, a computational model was used to explore the physiological processes underlying our estimator at the cellular level. We analysed 12-lead ECGs from 45 haemodialysis and 12 LQT2 patients. T-wave amplitude and downslope were calculated from the first two eigenleads. The T-wave slope-to-amplitude ratio (TS/A) was used as starting point for an ECG-based [K+] estimate (KECG). Leave-one-out cross-validation was performed. Agreement between KECG and reference [K+] from blood samples was promising (error: -0.09 ± 0.59 mM, absolute error: 0.46 ± 0.39 mM). The analysis on LQT2 patients, also supported by the outcome of computational analysis, reinforces our interpretation that, at the cellular level, delayed-rectifier potassium current is a main contributor of KECG correlation to blood [K+]. Following a comprehensive validation, this method could be effectively applied to monitor patients at risk for hyper/hypokalemia.

The development and validation of an early warning system to prevent the acquisition of 12-lead resting ECGs with interchanged electrode positions.

BACKGROUND: A fraction of routine resting ECG's are taken with electrode positions interchanged, leading to possible clinical misinterpretation. OBJECTIVE: Develop and test a method to detect and prevent electrode reversals at the electrocardiograph before the ECG is acquired. METHOD: The algorithm is based on QRS axis and P amplitudes for limb electrode reversals, and P-Q-RS amplitude distances to detect chest electrode reversals. The evaluation method involved a large (>18,000) hospital database for which serial ECG's were available and was based on simulated juxtapositions. RESULTS: The 7 most common lead reversals could be detected with a specificity of 99.8% per type and an average sensitivity of 90%, excluding LA-LL reversal (22% sensitivity). DISCUSSION: Results are similar to retrospective studies that used smaller, more homogeneous datasets. CONCLUSION: The early warning system reduces the ECG's recorded with reversal by 80%, at the price of a modest false alert rate of 1.4%.

Comparison of automated measurements of electrocardiographic intervals and durations by computer-based algorithms of digital electrocardiographs.

BACKGROUND AND PURPOSE: Automated measurements of electrocardiographic (ECG) intervals are widely used by clinicians for individual patient diagnosis and by investigators in population studies. We examined whether clinically significant systematic differences exist in ECG intervals measured by current generation digital electrocardiographs from different manufacturers and whether differences, if present, are dependent on the degree of abnormality of the selected ECGs. METHODS: Measurements of RR interval, PR interval, QRS duration, and QT interval were made blindly by 4 major manufacturers of digital electrocardiographs used in the United States from 600 XML files of ECG tracings stored in the US FDA ECG warehouse and released for the purpose of this study by the Cardiac Safety Research Consortium. Included were 3 groups based on expected QT interval and degree of repolarization abnormality, comprising 200 ECGs each from (1) placebo or baseline study period in normal subjects during thorough QT studies, (2) peak moxifloxacin effect in otherwise normal subjects during thorough QT studies, and (3) patients with genotyped variants of congenital long QT syndrome (LQTS). RESULTS: Differences of means between manufacturers were generally small in the normal and moxifloxacin subjects, but in the LQTS patients, differences of means ranged from 2.0 to 14.0 ms for QRS duration and from 0.8 to 18.1 ms for the QT interval. Mean absolute differences between algorithms were similar for QRS duration and QT intervals in the normal and in the moxifloxacin subjects (mean ≤6 ms) but were significantly larger in patients with LQTS. CONCLUSIONS: Small but statistically significant group differences in mean interval and duration measurements and means of individual absolute differences exist among automated algorithms of widely used, current generation digital electrocardiographs. Measurement differences, including QRS duration and the QT interval, are greatest for the most abnormal ECGs.