Unstable QT interval dynamics precedes ventricular tachycardia onset in patients with acute myocardial infarction: a novel approach to detect instability in QT interval dynamics from clinical ECG.
ABSTRACT: Instability in ventricular repolarization in the presence of premature activations (PA) plays an important role in arrhythmogenesis. However, such instability cannot be detected clinically. This study developed a methodology for detecting QT interval (QTI) dynamics instability from the ECG and explored the contribution of PA and QTI instability to ventricular tachycardia (VT) onset.To examine the contribution of PAs and QTI instability to VT onset, ECGs of 24 patients with acute myocardial infarction, 12 of whom had sustained VT (VT) and 12 nonsustained VT (NSVT), were used. From each patient ECG, 2 10-minute-long ECG recordings were extracted, 1 right before VT onset (onset epoch) and 1 at least 1 hour before it (control epoch). To ascertain how PA affects QTI dynamics stability, pseudo-ECGs were calculated from an MRI-based human ventricular model. Clinical and pseudo-ECGs were subdivided into 1-minute recordings (minECGs). QTI dynamics stability of each minECG was assessed with a novel approach. Frequency of PAs (f(PA)) and the number of minECGs with unstable QTI dynamics (N(us)) were determined for each patient. In the VT group, f(PA) and N(us) of the onset epoch were larger than in control. Positive regression relationships between f(PA) and N(us) were identified in both groups. The simulations showed that both f(PA) and the PA degree of prematurity contribute to QTI dynamics instability.Increased PA frequency and QTI dynamics instability precede VT onset in patients with acute myocardial infarction, as determined by novel methodology for detecting instability in QTI dynamics from clinical ECGs.
Project description:BACKGROUND:Experimental studies have demonstrated that unstable repolarization dynamics is a risk factor of arrhythmia. We have recently developed an algorithm to detect QT interval (QTI) instability from the clinical electrocardiogram (ECG). OBJECTIVE:To develop a clinical arrhythmia risk stratification index based on the detection of QTI instability. METHODS:Intracardiac ECGs were recorded at rest in 114 patients with implanted implantable cardioverter-defibrillators (ICDs). Patients were followed up until appropriate implantable cardioverter-defibrillator therapy or death occurred, whichever came first. Each ECG recording was divided into 1-minute episodes (minECGs); the instability in QTI dynamics, if any, of each minECG was detected with our algorithm. An arrhythmia risk index termed QTI instability index (QTII) was defined as the number of minECGs with unstable QTI dynamics normalized by the number of minECGs with premature activations. The performance of QTII in arrhythmia risk stratification was examined with survival analysis and was compared with other risk indices, such as the mean RR interval (RRI), the standard deviation of the RRI and the QTI, and the frequency of premature activation. We hypothesized that the index QTII, which accounts for multiple risk factors and their interdependence, performs better than indices quantifying individual arrhythmia risk factors in the stratification of arrhythmia risk. RESULTS:The results of survival analysis show that QTII outperformed all other studied indices in arrhythmia risk stratification and was the only independent indicator of arrhythmia propensity in a multivariate survival model. CONCLUSION:QTII is a promising arrhythmia risk stratification index.
Project description:BACKGROUND:A spontaneous coved-type ST segment elevation in the electrocardiogram (ECG) has long been recognized as a risk stratification tool in patients with Brugada syndrome (BrS). This Type-I ST segment elevation is known to exhibit high dynamicity, fluctuating between coved-type and non-coved ST segment elevation. Our objectives in this study were to: 1) Compare ECG parameters in patients with spontaneous coved-type (Type-I) vs. non-coved-type ST segment ECGs; 2) Determine the variability of these ECG parameters with repeated measurements; and 3) Assess the predictive value of ECG parameters in these two groups during follow-up. METHODS:Forty-two consecutive patients with BrS and implanted ICD were studied between 2000 and 2017. Serial ECGs and clinical characteristics were obtained over a period of 199?months. RESULTS:QT-interval, QTc-interval, QRS duration, Tp-e interval and Tp-e dispersion were all significantly longer in spontaneous Type I vs. non-Type 1 ECGs and all ECG parameters displayed significant variability during serial recording obtained throughout the follow-up period. Patients with a spontaneous Type I ECG during the 114?±?56?months follow-up period were at a much higher risk for VT/VF than those without a Type I ECG (p?=?0.016). Moreover, the risk for development of life-threatening ventricular arrhythmias was directly related to the fraction of ECGs displaying a spontaneous Type I pattern during follow-up. CONCLUSION:Our study illustrates the need for multiple ECGs to aid with both the diagnosis and prognosis of BrS. Serial ECGs can assist with risk stratification based on the fraction of ECGs that display a spontaneous Type-I BrS ECG.
Project description:Automatic measurement becomes a preference, and indeed a necessity, when analyzing 1000 s of ECGs in the setting of either drug-inducing QT prolongation screening or genome-wide association studies of QT interval. The problem is that individual manufacturers apply different computerized algorithms to measure QT interval. We conducted a comparative study to assess the outcomes with different automated measurements of QT interval between ECG machine manufacturers and validated the related heart rate correction methods.Herein, we directly compared these different commercial systems using 10,529 Fukuda Denshi ECGs and 72,754 Nihon Kohden ECGs taken in healthy Japanese volunteers. Log-transformed data revealed an equal optimal heart rate correction formula of QT interval for Fukuda Denshi and Nihon Kohden, in the form of QTc?=?QT/RR(-0.347). However, with the raw data, the optimal heart rate correction formula of QT interval was in the form of QTc?=?QT+0.156×(1-RR) for Fukuda Denshi and QTc?=?QT+0.152×(1-RR) for Nihon Kohden. After optimization of heart rate correction of QT interval by the linear regression model using either log-transformed data or raw data, QTc interval was ?10 ms longer in Nihon Kohden ECGs than in those recorded on Fukuda Denshi machines. Indeed, regression analysis revealed that differences in the ECG machine used had up to a two-fold larger impact on QT variation than gender difference. Such an impact is likely to be of considerable importance when ECGs for a given individual are recorded on different machines in the setting of multi-institutional joint research.We recommend that ECG machines of the same manufacturer should be used to measure QT and RR intervals in the setting of multi-institutional joint research. It is desirable to unify the computer algorithm for automatic QT and RR measurements from an ECG.
Project description:Introduction Patients with Brugada electrocardiographic (ECG) patterns have differing levels of arrhythmic risk. We hypothesized that temporal variations in certain ECG markers may provide additional value for risk stratification. The present study evaluated the relationship between temporal variability of ECG markers and arrhythmic outcomes in patients with a Brugada pattern ECG. Comparisons were made between low-risk asymptomatic subjects versus high-risk symptomatic patients with a history of syncope, ventricular tachycardia (VT) or ventricular fibrillation (VF). Methods A total of 81 patients presenting with Brugada patterns were recruited. Serial ECGs and electronic health records from January 2004 to April 2019 were analyzed. Temporal variability of QRS interval, J point-Tpeak interval (JTp), Tpeak-Tend interval (Tp-e), and ST elevation (STe) in precordial leads V1-3, in addition to RR-interval from lead II, was assessed using standard deviation and difference between maximum and minimum values over the serial ECGs. Results Patients presenting with type 1 Brugada ECG pattern initially had significantly higher variability in JTp from lead V2 (SD: 33.5 ± 13.8 vs. 25.2 ± 11.5 ms, P = 0.009; max-min: 98.6 ± 46.2 vs. 78.3 ± 47.6 ms, P = 0.047) and ST elevation in lead V1 (0.117 ± 0.122 vs. 0.053 ± 0.030 mV; P = 0.004). Significantly higher variability in Tp-e interval measured from lead V3 was observed in the VT/VF group compared to the syncope and asymptomatic groups (SD: 20.5 ± 8.5 vs. 16.6 ± 7.3 and 14.7 ± 9.8 ms; P = 0.044; max-min: 70.2 ± 28.9 vs. 56.3 ± 29.0 and 43.5 ± 28.5 ms; P = 0.011). Conclusion Temporal variability in ECG indices may provide additional value for risk stratification in patients with Brugada pattern.
Project description:The SEARCH-RIO study prospectively investigated electrocardiogram (ECG)-derived variables in chronic Chagas disease (CCD) as predictors of cardiac death and new onset ventricular tachycardia (VT). Cardiac arrhythmia is a major cause of death in CCD, and electrical markers may play a significant role in risk stratification. One hundred clinically stable outpatients with CCD were enrolled in this study. They initially underwent a 12-lead resting ECG, signal-averaged ECG, and 24-h ambulatory ECG. Abnormal Q-waves, filtered QRS duration, intraventricular electrical transients (IVET), 24-h standard deviation of normal RR intervals (SDNN), and VT were assessed. Echocardiograms assessed left ventricular ejection fraction. Predictors of cardiac death and new onset VT were identified in a Cox proportional hazard model. During a mean follow-up of 95.3 months, 36 patients had adverse events: 22 new onset VT (mean±SD, 18.4±4/year) and 20 deaths (26.4±1.8/year). In multivariate analysis, only Q-wave (hazard ratio, HR=6.7; P<0.001), VT (HR=5.3; P<0.001), SDNN<100 ms (HR=4.0; P=0.006), and IVET+ (HR=3.0; P=0.04) were independent predictors of the composite endpoint of cardiac death and new onset VT. A prognostic score was developed by weighting points proportional to beta coefficients and summing-up: Q-wave=2; VT=2; SDNN<100 ms=1; IVET+ =1. Receiver operating characteristic curve analysis optimized the cutoff value at >1. In 10,000 bootstraps, the C-statistic of this novel score was non-inferior to a previously validated (Rassi) score (0.89±0.03 and 0.80±0.05, respectively; test for non-inferiority: P<0.001). In CCD, surface ECG-derived variables are predictors of cardiac death and new onset VT.
Project description:BACKGROUND:Contemporary electrocardiographic (ECG) markers including ventricular ectopy and arrhythmias have not proved reliable in risk assessment for life-threatening arrhythmias. METHODS:We developed the "Multilead ECG Template-Derived Residua" approach to remove intrinsic morphologic differences and allow calculation of pathologic ECG heterogeneities among spatially separated leads. Prediction by R-wave and T-wave heterogeneity (RWH, TWH) analysis was tested in simulated and clinical ECGs. RESULTS:An enabling description of the Residua algorithm is provided. Simulated ECGs with but not without Residua produced a linear relationship (correlation coefficient r(2) = 0.999) between input and output RWH and TWH values. In heart failure patients, Residua disclosed a marked crescendo in RWH from 164.1 ± 33.1 at baseline to 299.8 ± 54.5 ?V and TWH from 134.5 ± 20.6 at baseline to 239.2 ± 37.0 ?V at 30-45 minutes before the arrhythmia (both, P < 0.05), which remained elevated until arrhythmia onset. Without Residua, mean RWH and TWH were elevated at 1061.0 ± 222.9 and 882.5 ± 375.2 ?V, respectively, throughout the recording and were not different prior to ventricular tachycardia onset. CONCLUSIONS:Calculation of ECG-template derived Residua provides a highly accurate means for assessing arrhythmia risk from standard ECGs. Potential widespread applications include resting diagnostic 12-lead, ambulatory, and exercise ECGs, electrophysiologic study laboratory recordings, and implantable devices.
Project description:Aims: Risk stratification of patients with Brugada syndrome (BrS) is vital for accurate prognosis and therapeutic decisions. Spontaneous Type 1 ST segment elevation is generally considered to be an independent risk factor for arrhythmic events. Other risk factors include gender, syncope, sudden cardiac arrest (SCA), and positive electrophysiological study (EPS). However, the further risk stratification of spontaneous type 1 combined with the other risk factors remains unclear. The present study pooled data from 4 large trials aiming to systematically evaluate the risk of spontaneous Type-1 ECG when combined with one or more of these other recognized risk factors. Methods: We searched for related studies published from November 2, 2002 to February 10, 2018 in PubMed, EMBASE, Cochrane Library, MEDLINE, Chinese National Knowledge Infrastructure (CNKI), and Wanfang Databases. The pooled data were evaluated combining each risk factor with the presence of a spontaneous Type-1 ECG. All analyses were performed using Review Manager, version 5.0.12. Results: Four eligible studies involving 1,338 patients (85% males, mean age: 48.1 ± 18.1 years) were enrolled. Spontaneous Type-1 ECG was associated with higher risk for ventricular tachycardia/fibrillation (VT/VF) than cases with non-Type 1 ECG in males (odds ratio: 95% CI: 1.84-5.17; P < 0.0001), but not in females (P = 0.29). Among spontaneous Type-1 cases with syncope or with positive EPS, the difference was not statistically significant (P = 0.06 and 0.07, respectively). Patients with Type-1 ECGs and positive EPS were at higher risk than those with negative EPS (95% CI: 1.10-5.04; P = 0.03). Pooled analysis showed an association of Spontaneous Type-1 ECG, Type-1 ECGs combined with male, and Type-1 ECGs combined with positive EPS between increased risk of arrhythmic events. Conclusion: Our results indicate that in BrS patients, a spontaneous Type-1 ECG is an independent risk factor for SCD in males, but not in females. A spontaneous Type-1 BrS is associated with a worse prognosis when combined with positive EPS.
Project description:<h4>Introduction</h4>Multiple algorithms based on 12-lead ECG measurements have been proposed to identify the right ventricular outflow tract (RVOT) and left ventricular outflow tract (LVOT) locations from which ventricular tachycardia (VT) and frequent premature ventricular complex (PVC) originate. However, a clinical-grade machine learning algorithm that automatically analyzes characteristics of 12-lead ECGs and predicts RVOT or LVOT origins of VT and PVC is not currently available. The effective ablation sites of RVOT and LVOT, confirmed by a successful ablation procedure, provide evidence to create RVOT and LVOT labels for the machine learning model.<h4>Methods</h4>We randomly sampled training, validation, and testing data sets from 420 patients who underwent successful catheter ablation (CA) to treat VT or PVC, containing 340 (81%), 38 (9%), and 42 (10%) patients, respectively. We iteratively trained a machine learning algorithm supplied with 1,600,800 features extracted <i>via</i> our proprietary algorithm from 12-lead ECGs of the patients in the training cohort. The area under the curve (AUC) of the receiver operating characteristic curve was calculated from the internal validation data set to choose an optimal discretization cutoff threshold.<h4>Results</h4>The proposed approach attained the following performance: accuracy (ACC) of 97.62 (87.44-99.99), weighted F1-score of 98.46 (90-100), AUC of 98.99 (96.89-100), sensitivity (SE) of 96.97 (82.54-99.89), and specificity (SP) of 100 (62.97-100).<h4>Conclusions</h4>The proposed multistage diagnostic scheme attained clinical-grade precision of prediction for LVOT and RVOT locations of VT origin with fewer applicability restrictions than prior studies.
Project description:Drug-induced long QT syndrome (diLQTS), characterized by a prolongation of the QT-interval on the electrocardiogram (ECG), is a serious adverse drug reaction that can cause the life-threatening arrhythmia Torsade de Points (TdP). Self-monitoring for diLQTS could therefore save lives, but detecting it on the ECG is difficult, particularly at high and low heart rates. In this paper, we evaluate whether using a pseudo-colouring visualisation technique and changing the coordinate system (Cartesian vs. Polar) can support lay people in identifying QT-prolongation at varying heart rates. Four visualisation techniques were evaluated using a counterbalanced repeated measures design including Cartesian no-colouring, Cartesian pseudo-colouring, Polar no-colouring and Polar pseudo-colouring. We used a multi-reader, multi-case (MRMC) receiver operating characteristic (ROC) study design within a psychophysical paradigm, along with eye-tracking technology. Forty-three lay participants read forty ECGs (TdP risk n = 20, no risk n = 20), classifying each QT-interval as normal/abnormal, and rating their confidence on a 6-point scale. The results show that introducing pseudo-colouring to the ECG significantly increased accurate detection of QT-interval prolongation regardless of heart rate, T-wave morphology and coordinate system. Pseudo-colour also helped to reduce reaction times and increased satisfaction when reading the ECGs. Eye movement analysis indicated that pseudo-colour helped to focus visual attention on the areas of the ECG crucial to detecting QT-prolongation. The study indicates that pseudo-colouring enables lay people to visually identify drug-induced QT-prolongation regardless of heart rate, with implications for the more rapid identification and management of diLQTS.
Project description:Aims: QT variability is a promising electrocardiographic marker. It has been studied as a screening tool for coronary artery disease and left ventricular hypertrophy, and increased QT variability is a known risk factor for sudden cardiac death. Considering that comprehensive normal values for QT variability were lacking, we set out to establish these in standard 10-s electrocardiograms (ECGs) covering both sexes and all ages. Methods: Ten-second, 12-lead ECGs were provided by five Dutch population studies (Pediatric Normal ECG Study, Leiden University Einthoven Science Project, Prevention of Renal and Vascular End-stage Disease Study, Utrecht Health Project, Rotterdam Study). ECGs were recorded digitally and processed by well-validated analysis software. We selected cardiologically healthy participants, 46% being women. Ages ranged from 11 days to 91 years. After quality control, 13,828 ECGs were available. We assessed three markers: standard deviation of QT intervals (SDqt), short-term QT variability (STVqt), and QT variability index (QTVI). Results: For SDqt and STVqt, the median and the lower limit of normal remained stable with age. The upper limit of normal declined until around age 45, and increased strongly in the elderly, notably so in women. This implies that a subset of the population, small enough not to have appreciable effect on the median, shows a high degree of QT variability with a possible risk of arrhythmias or worse, especially in women. Otherwise, sex differences were negligible in all three measurements. For QTVI, median, and normal limits decreased until age 20, and steadily went up afterwards except for the lower limit of normal, which flattens off after age 65. Conclusion: We report the first set of normal values for QT variability based on 10-s ECGs, for all ages and both sexes.