Martino Vaglio

Impaired T‐Amplitude Adaptation to Heart Rate Characterizes IKr Inhibition in the Congenital and Acquired Forms of the Long QT Syndrome

Introduction: The QTc interval prolongation is not a perfect surrogate marker of the presence of an increased risk for arrhythmic events. In the search for alternative markers, we investigated the T‐amplitude and QT interval adaptation to heart rate (HR) in patients with the congenital long QT syndrome (LQTS) and individuals with sotalol‐induced QT prolongation.

A quantitative assessment of T-wave morphology in LQT1, LQT2, and healthy individuals based on Holter recording technology

BACKGROUND The clinical course and the precipitating risk factors in the congenital long QT syndrome (LQTS) are genotype specific. OBJECTIVES The goal of this study was to develop a computer algorithm allowing for electrocardiogram (ECG)-based identification and differentiation of LQT1 and LQT2 carriers. METHODS Twelve-lead ECG Holter monitor recordings were acquired in 49 LQT1 carriers, 25 LQT2 carriers, and 38 healthy subjects as controls. The cardiac beats were clustered based on heart-rate bin method. Scalar and vectorial repolarization parameters were compared for similar heart rates among study groups. The Q to Tpeak (QTpeak), the Tpeak to Tend interval, T-wave magnitude and T-loop morphology were automatically quantified using custom-made algorithms. RESULTS QTpeak from lead II and the right slope of the T-wave were the most discriminant parameters for differentiating the 3 groups using prespecified heart rate bin (75.0 to 77.5 beats/min). The predictive model utilizing these scalar parameters was validated using the entire spectrum of heart rates. Both scalar and vectorcardiographic models provided very effective identification of tested subjects in heart rates between 60 and 100 beats/min, whereas they had limited performance during tachycardia and slightly better discrimination in bradycardia. In the 60 to 100 beats/min heart rate range, the best 2-variable model identified correctly 89% of healthy subjects, 84% of LQT1 carriers, and 92% of LQT2 carriers. A model including 3 parameters based purely on scalar ECG parameters could correctly identify 90% of the population (89% of healthy subjects, 90% of LQT1 carriers, and 92% of LQT2 carriers). CONCLUSION Automatic algorithm quantifying T-wave morphology discriminates LQT1 and LQT2 carriers and healthy subjects with high accuracy. Such computerized ECG methodology could assist physicians evaluating subjects suspected for LQTS.

Improving the Detection of Subtle IKr-Inhibition : Assessing Electrocardiographic Abnormalities of Repolarization Induced by Moxifloxacin

AbstractBackground: QT prolongation is an incomplete measure of drug-induced changes in repolarization. In this study, we investigated a novel, automatic ECG technique for describing ventricular repolarization morphology and we compared these results to corrected QT (QTc) prolongation for identifying ECGs of healthy individuals on moxifloxacin. Methods: We analysed data from the US FDA ECG Warehouse involving 160 standard ECGs from 40 healthy subjects enrolled in a randomized, parallel, placebo-controlled, ‘thorough QT’ study. Computerized ECG analysis included a series of scalar and vectorial parameters describing duration of repolarization segments and T-wave/loop morphology including its symmetry, amplitude and shape. Binary logistic models for the identification of moxifloxacin-induced abnormalities of the repolarization were developed. Results: Moxifloxacin induced significant changes in several ECG parameters including QT and QT apex and early repolarization duration (ERD)30% T-wave amplitude and slopes of the ascending and descending arm of the T-wave. The logistic model based only on T-wave morphology parameters outperformed the model based on QTc interval for identifying the presence of moxifloxacin. Combining information about repolarization interval duration with T-wave morphology significantly improved the detection of presence of moxifloxacin (p < 0.01). The increased sensitivity of our novel ECG method contributes to a >40% reduction in the sample size required to detect significant QTc prolongation induced by moxifloxacin. Conclusions: Repolarization morphology is significantly altered by moxifloxacin. The computerized ECG technique provides a novel method for quantifying morphological changes of repolarization segment. Our new parameters reflecting the morphology of the T-wave outperformed QTc measurements when identifying moxifloxacin-induced blockade of the outward rapid components of the delayed rectifier repolarizing potassium current (Ikr). These data indicate that the analysis of T-wave morphology could play a role in the assessment of drug toxicity.

Automatic Extraction of ECG Strips from Continuous 12-lead Holter Recordings for QT Analysis at Prescheduled versus Optimized Time Points

Background: Continuous 12‐lead ECG monitoring (Holter) in early‐phase pharmaceutical studies is today widely used as an ideal platform to extract discrete ECGs for analysis. The extraction process is typically performed manually by trained readers using commercial Holter processing systems.

Electrocardiographic method for identifying drug-induced repolarization abnormalities associated with a reduction of the rapidly activating delayed rectifier potassium current.

Several important non-cardiac drugs have been removed from the market after revealing harmful effect that was not identified during prior safety-assessment studies. We developed a new technique for the measurements of repolarization abnormalities from surface ECGs; this method improves sensitivity and specificity of the current technique used to identify the presence of abnormal ion current kinetics in the myocardial cells namely a prolongation of the QT interval on the surface ECG signal. We described in this paper the method and preliminary results, revealing the superiority of our technique that may play a role in the future of drug-safety assessment

Automatic analysis of cardiac repolarization morphology using Gaussian mesa function modeling

A novel fully automated method for wave identification and extraction from electrocardiogram (ECG) waveforms is presented. This approach implements the combined use of a new machine-learning algorithm and of specified parameterized functions called Gaussian mesa functions (GMFs). Individual cardiac cycle waveforms are broken up into GMFs using a generalized orthogonal forward regression algorithm; each individual GMF is subsequently identified (wave labeling) and analyzed for feature and morphologic extraction. The GMF associated with the repolarization waveform of the main vector lead, based on principal components analysis, was analyzed, and a set of morphologic parameters were derived under 2 experimental settings: first, in 100 digital 12-lead ECG Holter recordings acquired during three 24-hour periods (baseline and after 160 and 320 mg of sotalol) from 38 healthy subjects; second, in drug-free 12-lead resting ECGs from 100 genotyped long QT syndrome (LQTS) patients (50 each with LQT1 and LQT2). QT-interval duration was measured using an on-screen method applied to the global representative beats and reviewed by a senior cardiologist. QTci (individual correction) was used for analysis. All parameters in the sotalol test showed highly significant differences between the time of peak plasma concentration (Tmax) and baseline ECGs; however, the dynamic pattern of individual parameters followed different patterns. The LQTS test confirmed the results of the sotalol test, showing that GMF-based repolarization parameters were strongly modified as compared with healthy controls. In particular, T-wave width and descending phase of repolarization were more prolonged in LQT2 compared to LQT1.

Obesity and ECG left ventricular hypertrophy.

Aim: Our aim was to investigate the prevalence and the prognostic significance for fatal and nonfatal cerebrovascular and cardiovascular events of different ECG criteria for left ventricular hypertrophy (LVH) in normal weight, overweight and obese patients in an adult Italian population. Methods: A total of 18 330 adults (mean age 54 ± 11 years, 55% women, 53% hypertensive patients) were analyzed from the Moli-sani cohort. Obesity was defined using the ATPIII criteria. ECG-LVH was defined according to 2013 ESC-ESH guidelines. Results: The age and sex adjusted prevalence of ECG-LVH did not differ from normal weight patients to class 1–3 obesity patients, when Cornell-voltage criterion was used. In overweight and obese patients, as compared with normal weight patients, a progressively lower prevalence of ECG-LVH was observed when the Sokolow–Lyon index was used, whereas a higher prevalence was shown by using the aVL R-wave voltage (>11 and >5.7 mm) and the Cornell-voltage-QRS duration product. The incidence of cardiovascular events was significantly greater in patients with ECG LVH diagnosis by the Cornell voltage [hazard ratio 1.89, 95% confidence interval (CI) 1.05–3.39] and the Cornell product (hazard ratio 1.87, 95% CI 1.31–2.67). After adjusting for different confounders (age, sex, cigarette, hypertension, hypercholesterolemia, diabetes, income, education, occupational class and physical activity) and for BMI categories, only the Cornell product remained significantly associated with a higher incidence of cardiovascular events (hazard ratio 1.66; 95% CI 1.16–2.38). The predictive significance of different LVH criteria was assessed across BMI categories; after adjusting for confounders, no LVH criteria were significantly associated with an increased risk of cardiovascular events in obese patients; Cornell-product LVH remained an independent predictor of events in normal weight and overweight individuals (hazard ratio 2.63; 95% CI 1.10–6.28 and hazard ratio 2.72; 95% CI 1.52–4.25, respectively). Conclusion: Our results confirm that ECG LVH prevalence may differ according to the criteria used across BMI categories in a low cardiovascular risk cohort. The use of different LVH criteria according to BMI categories may improve cardiovascular risk stratification in a general population independently of several confounding factors.

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.

T-wave axis deviation is associated with biomarkers of low-grade inflammation. Findings from the MOLI-SANI study.

T-wave axis deviation (TDev) may help identifying subjects at risk for major cardiac events and mortality, but the pathogenesis of TDev is not well established; in particular, the possible association between TDev and inflammation is unexplored and unknown. We aimed at investigating the association between low-grade inflammation and TDev abnormalities by conducting a cross-sectional analysis on 17,507 subjects apparently free from coronary heart and haematological diseases enrolled in the MOLI-SANI study. TDev was measured from a standard 12-lead resting electrocardiogram. High sensitivity (Hs) C-reactive protein (CRP), leukocyte (WBC) and platelet counts, neutrophil or granulocyte to lymphocyte ratios were used as markers of inflammation. In multivariable model subjects reporting high CRP levels had higher odds of having borderline and abnormal TDev (OR=1.70; 95 %CI: 1.53-1.90 and OR=1.72; 95 %CI: 1.23-2.41, respectively); the association was still significant, although reduced, after controlling for body mass index (OR=1.17; 95 %CI: 1.05-1.32, for borderline and OR=1.46; 95 %CI: 1.03-2.08, for abnormal). Similarly, higher neutrophil or granulocyte to lymphocyte ratios were associated with increased odds of having abnormal TDev. Neither platelet nor leukocyte counts were associated with abnormal TDev. The relationship between CRP with TDev abnormalities was significantly stronger in men, in non- obese or normotensive individuals, and in those without metabolic syndrome. In conclusion, C-reactive protein and some cellular biomarkers of inflammation such as granulocyte or neutrophil to lymphocyte ratios were independently associated with abnormal TDev, especially in subjects at low CVD risk. These results suggest that a low-grade inflammation likely contributes to the pathogenesis of T- wave axis deviation.

A fundamental relationship between intraventricular conduction and heart rate

BACKGROUND Existence of a relationship between the electrocardiographic QRS interval duration and the diurnally varying heart rate, of consistent sign and magnitude, is controversial and the relationship has not been fully characterized in normal populations. METHODS AND RESULTS We analyzed the QRS-RR interval relationship in 884 Holter recordings in 410 normal subjects participating in 5 clinical trials. The slope of the linear regression of QRS on RR was positive in 93% of subjects with an average slope of 0.0125, which indicates an increase in QRS duration of 1.25msec for an increase in RR interval of 100msec. The increase was 15% larger in women than in men. Age had no significant effect on the slope. CONCLUSIONS In two populations of normal subjects we observed a robust, direct relationship between the spontaneously changing RR interval and intraventricular conduction time represented by the duration of the QRS interval. As heart rate increases, QRS duration decreases. The change is larger in women. These observations have important physiological and clinical implications.