T-wave Peak-to-End Changes Quantified by Time-Warping Predicts Ventricular Fibrillation in a Porcine Myocardial Infarction Model.

BACKGROUND: The T-peak-to-T-end ( Tpe) interval has shown potential in predicting ventricular arrhythmic risk. It is an appealing index to be measured during ischemia since it is less influenced by ST-segment changes than the early part of the T wave. A time-warping-based index, derived from a spatially transformed PCA lead, [Formula: see text], quantifying changes in the Tpe morphology, has previously demonstrated utility in tracking repolarization changes induced by a 5-minute ischemia model in humans. The value of [Formula: see text] as a predictor of ventricular fibrillation (VF) episodes is assessed in a porcine model of myocardial ischemia with ischemia maintained for 40 minutes. METHODS: From 32 pigs undergoing a coronary occlusion, pre-occlusion and occlusion ECG recordings from 10 pigs suffering a VF episode after 10 min of occlusion (Delayed VF) and 16 that did not had any episode during the recording were analyzed. The [Formula: see text] series was measured by comparing Tpe morphologies at different stages of the occlusion relative to the peak-to-end morphology of a baseline T-wave. RESULTS: During baseline, [Formula: see text] remained stationary with an intra-recording median [IQR] value of 1.60 [1.33] ms. During artery occlusion, [Formula: see text] followed a well-marked gradual increasing trend as ischemia progressed, reaching a median of 14.58 [17.72] ms. [Formula: see text] averages were significantly higher ( ) in the VF group than in the Non-VF group at time intervals 0-5, 5-10, 10-15, 15-20, 20-25 min after occlusion onset and at 10-15, 5-10 and 5-0 minutes prior to VF episode, with median values of 12.5, 18.8, 26.8, 24.0, 31.0, 18.6, 25.0 and 28.8 vs 6.3, 7.6, 8.0, 7.8, 7.8, 8.5, 7.2 and 6.0 ms, respectively. The [Formula: see text] interval was also significantly higher in the VF group at all analyzed time periods, but with a lower significance level. Pigs with maximum [Formula: see text] ≥ 20.0 ms and [Formula: see text] ≥ 85.4 ms had significantly higher risk for VF occurring in the early 5-10 minutes interval, with 90.0%/75.0% and 80.0%/69.0% sensitivity/specificity, respectively. Univariate Cox analysis yielded hazard ratios of 12.5 for [Formula: see text] vs 5.5 for [Formula: see text]. CONCLUSIONS AND SIGNIFICANCE: The time-warping-based index, [Formula: see text], is a stronger VF predictor than [Formula: see text] during ischemia in a porcine model, advising for further clinical exploration studies in humans.

Characterization of Atrial Fibrillation Episode Patterns: A Comparative Study.

OBJECTIVE: The episode patterns of paroxysmal atrial fibrillation (AF) may carry important information on disease progression and complication risk. However, existing studies offer very little insight into to what extent a quantitative characterization of AF patterns can be trusted given the errors in AF detection and various types of shutdown, i.e., poor signal quality and non-wear. This study explores the performance of AF pattern characterizing parameters in the presence of such errors. METHODS: To evaluate the performance of the parameters AF aggregation and AF density, both previously proposed to characterize AF patterns, the two measures mean normalized difference and the intraclass correlation coefficient are used to describe agreement and reliability, respectively. The parameters are studied on two PhysioNet databases with annotated AF episodes, also accounting for shutdowns due to poor signal quality. RESULTS: The agreement is similar for both parameters when computed for detector-based and annotated patterns, which is 0.80 for AF aggregation and 0.85 for AF density. On the other hand, the reliability differs substantially, with 0.96 for AF aggregation but only 0.29 for AF density. This finding suggests that AF aggregation is considerably less sensitive to detection errors. The results from comparing three strategies to handle shutdowns vary considerably, with the strategy that disregards the shutdown from the annotated pattern showing the best agreement and reliability. CONCLUSIONS: Due to its better robustness to detection errors, AF aggregation should be preferred. To further improve performance, future research should put more emphasis on AF pattern characterization.

ECG Modeling for Simulation of Arrhythmias in Time-Varying Conditions.

The present article proposes an ECG simulator that advances modeling of arrhythmias and noise by introducing time-varying signal characteristics. The simulator is built around a discrete-time Markov chain model for simulating atrial and ventricular arrhythmias of particular relevance when analyzing atrial fibrillation (AF). Each state is associated with statistical information on episode duration and heartbeat characteristics. Statistical, time-varying modeling of muscle noise, motion artifacts, and the influence of respiration is introduced to increase the complexity of simulated ECGs, making the simulator well suited for data augmentation in machine learning. Modeling of how the PQ and QT intervals depend on heart rate is also introduced. The realism of simulated ECGs is assessed by three experienced doctors, showing that simulated ECGs are difficult to distinguish from real ECGs. Simulator usefulness is illustrated in terms of AF detection performance when either simulated or real ECGs are used to train a neural network for signal quality control. The results show that both types of training lead to similar performance.

Atrial fibrillation episode patterns as predictor of clinical outcome of catheter ablation.

Methods for characterization of atrial fibrillation (AF) episode patterns have been introduced without establishing clinical significance. This study investigates, for the first time, whether post-ablation recurrence of AF can be predicted by evaluating episode patterns. The dataset comprises of 54 patients (age 56 ± 11 years; 67% men), with an implantable cardiac monitor, before undergoing the first AF catheter ablation. Two parameters of the alternating bivariate Hawkes model were used to characterize the pattern: AF dominance during the monitoring period (log(mu)) and temporal aggregation of episodes (beta1). Moreover, AF burden and AF density, a parameter characterizing aggregation of AF burden, were studied. The four parameters were computed from an average of 29 AF episodes before ablation. The risk of AF recurrence after catheter ablation using the Hawkes parameters log(mu) and beta1, AF burden, and AF density was evaluated. While the combination of AF burden and AF density is related to a non-significant hazard ratio, the combination of log(mu) and beta1 is related to a hazard ratio of 1.95 (1.03-3.70; p < 0.05). The Hawkes parameters showed increased risk of AF recurrence within 1 year after the procedure for patients with high AF dominance and high episode aggregation and may be used for pre-ablation risk assessment.

QT Interval Adaptation to Heart Rate Changes in Atrial Fibrillation as a Predictor of Sudden Cardiac Death.

OBJECTIVE: The clinical significance of QT interval adaptation to heart rate changes has been poorly investigated in atrial fibrillation (AF), since QT delineation in the presence of f-waves is challenging. The objective of the present study is to investigate new techniques for QT adaptation estimation in permanent AF. METHODS: A multilead strategy based on periodic component analysis, to emphasize T-wave periodicity, is proposed for QT delineation. QT adaptation is modeled by a linear, time-invariant filter, which describes the dependence between the current QT interval and the preceding RR intervals, followed by a memoryless, nonlinear, function. The QT adaptation time lag is determined from the estimated impulse response. RESULTS: Using simulated ECGs in permanent AF, the transformed lead was found to offer more accurate QT delineation and time lag estimation than did the original ECG leads for a wide range of f-wave amplitudes. In a population with chronic heart failure and permanent AF, the time lag estimated from the transformed lead was found to have the strongest, statistically significant association with sudden cardiac death (SCD) (hazard ratio = 3.49). CONCLUSIONS: Periodic component analysis provides more accurate QT delineation and improves time lag estimation in AF. A prolonged QT adaptation time lag is associated with a high risk for SCD. SIGNIFICANCE: SCD risk markers originally developed for sinus rhythm can also be used in AF, provided that T-wave periodicity is emphasized. The time lag is a potentially useful biomarker for identifying patients at risk for SCD, guiding clinicians in adopting effective therapeutic decisions.

Nonlinear T-Wave Time Warping-Based Sensing Model for Non-Invasive Personalised Blood Potassium Monitoring in Hemodialysis Patients: A Pilot Study.

BACKGROUND: End-stage renal disease patients undergoing hemodialysis (ESRD-HD) therapy are highly susceptible to malignant ventricular arrhythmias caused by undetected potassium concentration ([K+]) variations (Δ[K+]) out of normal ranges. Therefore, a reliable method for continuous, noninvasive monitoring of [K+] is crucial. The morphology of the T-wave in the electrocardiogram (ECG) reflects Δ[K+] and two time-warping-based T-wave morphological parameters, dw and its heart-rate corrected version dw,c, have been shown to reliably track Δ[K+] from the ECG. The aim of this study is to derive polynomial models relating dw and dw,c with Δ[K+], and to test their ability to reliably sense and quantify Δ[K+] values. METHODS: 48-hour Holter ECGs and [K+] values from six blood samples were collected from 29 ESRD-HD patients. For every patient, dw and dw,c were computed, and linear, quadratic, and cubic fitting models were derived from them. Then, Spearman's (ρ) and Pearson's (r) correlation coefficients, and the estimation error (ed) between Δ[K+] and the corresponding model-estimated values (Δ^[K+]) were calculated. RESULTS AND DISCUSSIONS: Nonlinear models were the most suitable for Δ[K+] estimation, rendering higher Pearson's correlation (median 0.77 ≤r≤ 0.92) and smaller estimation error (median 0.20 ≤ed≤ 0.43) than the linear model (median 0.76 ≤r≤ 0.86 and 0.30 ≤ed≤ 0.40), even if similar Spearman's ρ were found across models (median 0.77 ≤ρ≤ 0.83). CONCLUSION: Results support the use of nonlinear T-wave-based models as Δ[K+] sensors in ESRD-HD patients.

Considerations on Performance Evaluation of Atrial Fibrillation Detectors.

OBJECTIVE: A large number of atrial fibrillation (AF) detectors have been published in recent years, signifying that the comparison of detector performance plays a central role, though not always consistent. The aim of this study is to shed needed light on aspects crucial to the evaluation of detection performance. METHODS: Three types of AF detector, using either information on rhythm, rhythm and morphology, or segments of ECG samples, are implemented and studied on both real and simulated ECG signals. The properties of different performance measures are investigated, for example, in relation to dataset imbalance. RESULTS: The results show that performance can differ considerably depending on the way detector output is compared to database annotations, i.e., beat-to-beat, segment-to-segment, or episode-to-episode comparison. Moreover, depending on the type of detector, the results substantiate that physiological and technical factors, e.g., changes in ECG morphology, rate of atrial premature beats, and noise level, can have a considerable influence on performance. CONCLUSION: The present study demonstrates overall strengths and weaknesses of different types of detector, highlights challenges in AF detection, and proposes five recommendations on how to handle data and characterize performance.

Monitoring blood potassium concentration in hemodialysis patients by quantifying T-wave morphology dynamics.

We investigated the ability of time-warping-based ECG-derived markers of T-wave morphology changes in time ([Formula: see text]) and amplitude ([Formula: see text]), as well as their non-linear components ([Formula: see text] and [Formula: see text]), and the heart rate corrected counterpart ([Formula: see text]), to monitor potassium concentration ([Formula: see text]) changes ([Formula: see text]) in end-stage renal disease (ESRD) patients undergoing hemodialysis (HD). We compared the performance of the proposed time-warping markers, together with other previously proposed [Formula: see text] markers, such as T-wave width ([Formula: see text]) and T-wave slope-to-amplitude ratio ([Formula: see text]), when computed from standard ECG leads as well as from principal component analysis (PCA)-based leads. 48-hour ECG recordings and a set of hourly-collected blood samples from 29 ESRD-HD patients were acquired. Values of [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text] were calculated by comparing the morphology of the mean warped T-waves (MWTWs) derived at each hour along the HD with that from a reference MWTW, measured at the end of the HD. From the same MWTWs [Formula: see text] and [Formula: see text] were also extracted. Similarly, [Formula: see text] was calculated as the difference between the [Formula: see text] values at each hour and the [Formula: see text] reference level at the end of the HD session. We found that [Formula: see text] and [Formula: see text] showed higher correlation coefficients with [Formula: see text] than [Formula: see text]-Spearman's ([Formula: see text]) and Pearson's (r)-and [Formula: see text]-Spearman's ([Formula: see text])-in both SL and PCA approaches being the intra-patient median [Formula: see text] and [Formula: see text] in SL and [Formula: see text] and [Formula: see text] in PCA respectively. Our findings would point at [Formula: see text] and [Formula: see text] as the most suitable surrogate of [Formula: see text], suggesting that they could be potentially useful for non-invasive monitoring of ESRD-HD patients in hospital, as well as in ambulatory settings. Therefore, the tracking of T-wave morphology variations by means of time-warping analysis could improve continuous and remote [Formula: see text] monitoring of ESRD-HD patients and flagging risk of [Formula: see text]-related cardiovascular events.

Modeling and Estimation of Temporal Episode Patterns in Paroxysmal Atrial Fibrillation.

OBJECTIVE: The present study proposes a model-based, statistical approach to characterizing episode patterns in paroxysmal atrial fibrillation (AF). Thanks to the rapid advancement of noninvasive monitoring technology, the proposed approach should become increasingly relevant in clinical practice. METHODS: History-dependent point process modeling is employed to characterize AF episode patterns, using a novel alternating, bivariate Hawkes self-exciting model. In addition, a modified version of a recently proposed statistical model to simulate AF progression throughout a lifetime is considered, involving non-Markovian rhythm switching and survival functions. For each model, the maximum likelihood estimator is derived and used to find the model parameters from observed data. RESULTS: Using three databases with a total of 59 long-term ECG recordings, the goodness-of-fit analysis demonstrates that the proposed alternating, bivariate Hawkes model fits SR-to-AF transitions in 40 recordings and AF-to-SR transitions in 51; the corresponding numbers for the AF model with non-Markovian rhythm switching are 40 and 11, respectively. Moreover, the results indicate that the model parameters related to AF episode clustering, i.e., aggregation of temporal AF episodes, provide information complementary to the well-known clinical parameter AF burden. CONCLUSION: Point process modeling provides a detailed characterization of the occurrence pattern of AF episodes that may improve the understanding of arrhythmia progression.

Evaluation of Cardiac Circadian Rhythm Deconditioning Induced by 5-to-60 Days of Head-Down Bed Rest.

Head-down tilt (HDT) bed rest elicits changes in cardiac circadian rhythms, generating possible adverse health outcomes such as increased arrhythmic risk. Our aim was to study the impact of HDT duration on the circadian rhythms of heart beat (RR) and ventricular repolarization (QTend) duration intervals from 24-h Holter ECG recordings acquired in 63 subjects during six different HDT bed rest campaigns of different duration (two 5-day, two 21-day, and two 60-day). Circadian rhythms of RR and QTend intervals series were evaluated by Cosinor analysis, resulting in a value of midline (MESOR), oscillation amplitude (OA) and acrophase (φ). In addition, the QTc (with Bazett correction) was computed, and day-time, night-time, maximum and minimum RR, QTend and QTc intervals were calculated. Statistical analysis was conducted, comparing: (1) the effects at 5 (HDT5), 21 (HDT21) and 58 (HDT58) days of HDT with baseline (PRE); (2) trends in recovery period at post-HDT epochs (R) in 5-day, 21-day, and 60-day HDT separately vs. PRE; (3) differences at R + 0 due to bed rest duration; (4) changes between the last HDT acquisition and the respective R + 0 in 5-day, 21-day, and 60-day HDT. During HDT, major changes were observed at HDT5, with increased RR and QTend intervals' MESOR, mostly related to day-time lengthening and increased minima, while the QTc shortened. Afterward, a progressive trend toward baseline values was observed with HDT progression. Additionally, the φ anticipated, and the OA was reduced during HDT, decreasing system's ability to react to incoming stimuli. Consequently, the restoration of the orthostatic position elicited the shortening of RR and QTend intervals together with QTc prolongation, notwithstanding the period spent in HDT. However, the magnitude of post-HDT changes, as well as the difference between the last HDT day and R + 0, showed a trend to increase with increasing HDT duration, and 5/7 days were not sufficient for recovering after 60-day HDT. Additionally, the φ postponed and the OA significantly increased at R + 0 compared to PRE after 5-day and 60-day HDT, possibly increasing the arrhythmic risk. These results provide evidence that continuous monitoring of astronauts' circadian rhythms, and further investigations on possible measures for counteracting the observed modifications, will be key for future missions including long periods of weightlessness and gravity transitions, for preserving astronauts' health and mission success.

Assessment of ventricular repolarization instability in terms of T-wave alternans induced by head-down bed-rest immobilization.

OBJECTIVE: To assess the effects of different durations of simulated microgravity exposure on ventricular repolarization (VR) in terms of T-wave alternans (TWA) as well as to test whether an increase in VR heterogeneity could be detected once normal gravity was restored. APPROACH: A total of 63 healthy volunteers were recruited in several head-down bed-rest (HDBR) experiments in the context of the European Space Agency bed-rest strategy. TWA is evaluated during the night period using ambulatory ECG recordings, before, during and after long- (60 d), mid- (21 d) and short- (5 d) duration HDBR by the long-term averaging technique. MAIN RESULTS: 5-21 d of exposure to simulated microgravity by means of the HDBR model do not lead to a significant increase of cardiac electrical instability in healthy myocardial substrates up to the point of eliciting TWA on the surface ECG. However, TWA indices increased after long-term HDBR exposure, once normal gravity was re-established, indicative of incipient electrical instability on VR at the conclusion of 60 d of HDBR. SIGNIFICANCE: The results of this work underline the importance of focusing future research on immediate effects after long-term microgravity exposure, both simulated by HDBR or from space mission scenarios, once partial gravity conditions are re-established. A deeper insight in the understanding of human body reactions in these scenarios results crucial in the design of future long-duration spaceflight missions, to mitigate any potential risk that can limit astronaut's performance.

Assessment of Ultra-Short Heart Variability Indices Derived by Smartphone Accelerometers for Stress Detection.

Body acceleration due to heartbeat-induced reaction forces can be measured as mobile phone accelerometer (m-ACC) signals. Our aim was to test the feasibility of using m-ACC to detect changes induced by stress by ultra-short heart rate variability (USV) indices (standard deviation of normal-to-normal interval-SDNN and root mean square of successive differences-RMSSD). Sixteen healthy volunteers were recruited; m-ACC was recorded while in supine position, during spontaneous breathing at rest conditions (REST) and during one minute of mental stress (MS) induced by arithmetic serial subtraction task, simultaneous with conventional electrocardiogram (ECG). Beat occurrences were extracted from both ECG and m-ACC and used to compute USV indices using 60, 30 and 10s durations, both for REST and MS. A feasibility of 93.8% in the beat-to-beat m-ACC heart rate series extraction was reached. In both ECG and m-ACC series, compared to REST, in MS the mean beat duration was reduced by 15% and RMSSD decreased by 38%. These results show that short term recordings (up to 10 s) of cardiac activity using smartphone's accelerometers are able to capture the decrease in parasympathetic tone, in agreement with the induced stimulus.

Automatic diagnosis of strict left bundle branch block using a wavelet-based approach.

Patients with left bundle branch block (LBBB) are known to have a good clinical response to cardiac resynchronization therapy. However, the high number of false positive diagnosis obtained with the conventional LBBB criteria limits the effectiveness of this therapy, which has yielded to the definition of new stricter criteria. They require prolonged QRS duration, a QS or rS pattern in the QRS complexes at leads V1 and V2 and the presence of mid-QRS notch/slurs in 2 leads within V1, V2, V5, V6, I and aVL. The aim of this work was to develop and assess a fully-automatic algorithm for strict LBBB diagnosis based on the wavelet transform. Twelve-lead, high-resolution, 10-second ECGs from 602 patients enrolled in the MADIT-CRT trial were available. Data were labelled for strict LBBB by 2 independent experts and divided into training (n = 300) and validation sets (n = 302) for assessing algorithm performance. After QRS detection, a wavelet-based delineator was used to detect individual QRS waves (Q, R, S), QRS onsets and ends, and to identify the morphological QRS pattern on each standard lead. Then, multilead QRS boundaries were defined in order to compute the global QRS duration. Finally, an automatic algorithm for notch/slur detection within the QRS complex was applied based on the same wavelet approach used for delineation. In the validation set, LBBB was diagnosed with a sensitivity and specificity of Se = 92.9% and Sp = 65.1% (Acc = 79.5%, PPV = 74% and NPV = 89.6%). The results confirmed that diagnosis of strict LBBB can be done based on a fully automatic extraction of temporal and morphological QRS features. However, it became evident that consensus in the definition of QRS duration as well as notch and slurs definitions is necessary in order to guarantee accurate and repeatable diagnosis of complete LBBB.

Quantification of Ventricular Repolarization Variation for Sudden Cardiac Death Risk Stratification in Atrial Fibrillation.

OBJECTIVE: Atrial fibrillation (AF) rhythm gives rise to an irregular response in ventricular activity, preventing the use of standard ECG-derived risk markers based on ventricular repolarization heterogeneity under this particular condition. In this study, we proposed new indices to quantify repolarization variations in AF patients, assessing their stratification performance in a chronic heart failure population with AF. METHODS: We developed a method based on a selective bin averaging technique. Consecutive beats preceded by a similar RR interval were selected, from which the average variation within the ST-T complex for each RR range was computed. We proposed two sets of indices: 1) the 2-beat index of ventricular repolarization variation, ( IV2), computed from pairs of stable consecutive beats; and 2) the 3-beat indices of ventricular repolarization variation, computed in triplets of stable consecutive beats ( IV3). RESULTS: These indices showed a significant association with sudden cardiac death (SCD) outcome in the study population. In addition, risk assessment based on the combination of the proposed indices improved stratification performance compared to their individual potential. CONCLUSION: Patients with enhanced ventricular repolarization variation computed in terms of the proposed indices were successfully associated to a higher SCD incidence in our study population, evidencing their prognostic value. SIGNIFICANCE: using a simple ambulatory ECG recording, it is possible to stratify AF patients at risk of SCD, which may help cardiologists in adopting most effective therapeutic strategies, with a positive impact in both the patient and healthcare systems.

Post-Ventricular Premature Contraction Phase Correction Improves the Predictive Value of Average T-Wave Alternans in Ambulatory ECG Recordings.

OBJECTIVE: We proposed and evaluated a method for correcting possible phase shifts provoked by the presence of ventricular premature contractions (VPCs) for a better assessment of T-wave alternans (TWA).  Methods: First, we synthesized ECG signals with artificial TWA in the presence of different noise sources. Then, we assessed the prognostic value for sudden cardiac death (SCD) of the long-term average of TWA amplitude (the index of average alternans, ) in ambulatory ECG signals from congestive heart failure (CHF) and evaluated whether it is sensitive to the presence of VPCs. RESULTS: The inclusion of the phase correction after VPC in the processing always improved estimation accuracy of the under different noisy conditions and regardless of the number of the VPCs included in the sequence. It also presented a positive impact on the prognostic value of with increased hazard ratios (from 17% to 29%, depending of the scenario) in comparison to the noninclusion of this step. CONCLUSION: The proposed methodology for estimation, which corrects for the possible phase reversal on TWA after the presence of VPCs, represents a robust TWA estimation approach with a significant impact on the prognostic value of for SCD stratification in CHF patients. SIGNIFICANCE: An accurate TWA estimation has a potential direct clinical impact on noninvasive SCD stratification, allowing better identification of patients at higher risk and helping clinicians in adopting the most appropriate therapeutic strategy.

QRS broadening due to terminal distortion is associated with the size of myocardial injury in experimental myocardial infarction.

INTRODUCTION: Not only repolarization, but also depolarization ECG indexes reflect the progression of ischemic injury. The aim was to assess the QRS duration and morphology dynamics during the prolonged coronary occlusion and their association with the myocardial area at risk (MaR) and final infarct size (IS). METHODS: In pigs, myocardial infarction was induced by inflation of an angioplasty balloon in the left descending artery (LAD), and ECG was continuously recorded. QRS duration was calculated on a beat-to-beat basis during the occlusion period. Single photon emission computed tomography (SPECT) was performed for the assessment of MaR, and IS was assessed by magnetic resonance imaging (MRI). RESULTS: All animals developed an anteroseptal infarction with MaR 40±9% and IS 23±7%. Two peaks of QRS widening were found in all animals: the early peak immediately after LAD occlusion and the late one 17.7±4.1min later. No association was found between MaR and IS and either QRS width or the degree of QRS widening at the early peak. QRS duration on the late peak correlated with both MaR (r=0.61; p=0.007) and IS (r=0.55; p=0.018). CONCLUSION: The QRS widening at the late peak, but not at the early peak, is associated with the size of myocardial injury, suggesting different underlying mechanisms.

Transient and rapid QRS-widening associated with a J-wave pattern predicts impending ventricular fibrillation in experimental myocardial infarction.

BACKGROUND: Certain types of the early repolarization phenomenon, previously considered to be benign, have been reported to be associated with ventricular fibrillation (VF), both in population-based studies and in the myocardial infarction (MI) settings. OBJECTIVE: To analyze whether QRS widening and appearance of a J-wave pattern in experimental MI settings is predictive of VF. METHODS: MI was induced in 32 pigs by 40-minute inflation of an angioplasty balloon in the left descending artery, and electrocardiogram was continuously recorded. Multilead QRS boundaries were computed, and QRS duration was calculated on a beat-to-beat basis during the occlusion period for each pig. An association between QRS widening and subsequent VF was studied using receiver operating characteristic curve analysis. Electrocardiograms at maximum QRS duration were reviewed for the presence of a J-wave pattern. RESULTS: Sixteen animals had VF episodes during the occlusion period. Two peaks of QRS widening were found in all animals: the first peak immediately on left descending artery occlusion and the second peak 19.1 ± 4.0 minutes later. The magnitude of changes in the QRS width over time had significant interindividual differences. A QRS widening of ≥28 ms during a 3-minute time window was observed in 14 animals and predicted impending VF (selectivity 80%, specificity 73%, positive predictive value 57%, and negative predictive value 89%; P = .008). In 10 of 14 (71%) pigs, a J-wave pattern appeared at maximal QRS duration. The appearance of a J-wave pattern predicted VF with selectivity 80%, specificity 68%, positive predictive value 53%, and negative predictive value 88% (P = .02). CONCLUSION: Transient QRS widening, commonly associated with a J-wave pattern, appears to predict impending VF in acute ischemia settings and motivates further clinical studies for monitoring immediate risk of VF in MI.

T wave alternans in experimental myocardial infarction: time course and predictive value for the assessment of myocardial damage.

BACKGROUND: T-wave alternans (TWA) is associated with prognosis after myocardial infarction (MI), however its link to the extent of ischemic injury has not been clarified. We analyzed the course of TWA and its relation to myocardial damage in experimental myocardial infarction. METHODS: In 21 pigs, infarction was induced by 40-minute long balloon inflation in LAD under continuous 12-lead ECG monitoring. TWA was assessed in a 32-beat sliding window, using periodic component analysis and the Laplacian Likelihood Ratio method. Myocardium at risk (MaR) and infarct size (IS) were evaluated by SPECT and magnetic resonance imaging respectively. RESULTS: TWA appeared at 7.2±4.5minutes of occlusion, reached its maximum at 12.7±6.3 and lasted until 26.5±9.2minutes. The maximal level of TWA was associated with both MaR (r=0.499, p=0.035) and IS (r=0.65, p=0.004). CONCLUSION: TWA magnitude is associated with both MaR and IS in experiment, which encourages further studies in clinical settings.