Dataset Information

Absolute beat-to-beat variability and instability parameters of ECG intervals: biomarkers for predicting ischaemia-induced ventricular fibrillation.

ABSTRACT:

Background and purpose

Predicting lethal arrhythmia liability from beat-to-beat variability and instability (BVI) of the ECG intervals is a useful technique in drug assessment. Most investigators use only arrhythmia-free ECGs for this. Recently, it was shown that drug-induced torsades de pointes (TdP) liability can be predicted more accurately from BVI measured irrespective of rhythm, even during arrhythmias (absolute?BVI). The present study tested the broader applicability of this assessment by examining whether absolute?BVI parameters predict another potential lethal arrhythmia, ischaemia-induced ventricular fibrillation (VF).

Experimental approach

Langendorff-perfused rat hearts were subjected to regional ischaemia for 15 min. Absolute BVI parameters were derived from ECG intervals measured in 40 consecutive ventricular complexes (irrespective of rhythm) immediately preceding VF onset and compared with time-matched values in hearts not expressing VF.

Key results

Increased frequency of non-sinus beats and 'R on T' arrhythmic beats, shortened mean RR and electrical diastolic intervals, and increased BVI of cycle length and repolarization predicted VF occurrence. Absolute?BVI parameters that quantify variability of repolarization (e.g. 'short-term variability' of QT interval) had the best predictive power with high sensitivity and specificity. In contrast, VF was not predicted by any BVI parameter derived from the last arrhythmia-free interlude before VF.

Conclusions and implications

The novel absolute?BVI parameters that predicted TdP in rabbit also predict ischaemia-induced VF in rat, indicating a diagnostic and mechanistic congruence. Repolarization inhomogeneity represents a pivotal biomarker of ischaemia-induced VF. The newly validated biomarkers could serve as surrogates for VF in pre-clinical drug investigations.

SUBMITTER: Sarusi A

PROVIDER: S-EPMC3966755 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

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Publications

Absolute beat-to-beat variability and instability parameters of ECG intervals: biomarkers for predicting ischaemia-induced ventricular fibrillation.

Sarusi Annamária A Rárosi Ferenc F Szűcs Mónika M Csík Norbert N Farkas Attila S AS Papp Julius Gy JG Varró András A Forster Tamás T Curtis Michael J MJ Farkas András A

British journal of pharmacology 20140401 7

<h4>Background and purpose</h4>Predicting lethal arrhythmia liability from beat-to-beat variability and instability (BVI) of the ECG intervals is a useful technique in drug assessment. Most investigators use only arrhythmia-free ECGs for this. Recently, it was shown that drug-induced torsades de pointes (TdP) liability can be predicted more accurately from BVI measured irrespective of rhythm, even during arrhythmias (absolute BVI). The present study tested the broader applicability of this asses ...[more]

PMID: 24417376

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Project description:BackgroundMeasures of the ventricular fibrillation (VF) waveform may enable better allocation of cardiac arrest treatment by discriminating which patients should receive immediate defibrillation versus alternate therapies such as CPR. We derive a new measure based on the 'roughness' of the VF waveform, the Logarithm of the Absolute Correlations (LAC), and assess and contrast how well the LAC and the previously published scaling exponent (ScE) predict the duration of VF and the likelihood of return of spontaneous circulation (ROSC) under both optimal experimental and commercial-defibrillator sampling conditions.Methods and resultsWe derived the LAC and ScE from two different populations--an animal study of 44 swine and a retrospective human sample of 158 out-of-hospital VF arrests treated with a commercial defibrillator. In the animal study, the LAC and ScE were calculated on 5s epochs of VF recorded at 1000 samples/s and then down sampled to 125 samples/s. In the human study, the LAC and ScE were calculated using 6s epochs recorded at 200 samples/s that occurred immediately prior to the initial shock. We compared the LAC and ScE measures using the Spearman correlation coefficients (CC) and areas under the receiver operating characteristic curve (AUC).ResultsIn the animal study, the LAC and ScE were highly correlated at 1000 sample/s (CC=0.93) but not at 125 samples/s (CC=-0.06). These correlations were reflected in how well the measures discriminated VF of < or =5 versus >5 min: AUC at 1000 samples/s was similar for LAC compared to ScE (0.71 versus 0.76). However AUC at 125 samples was greater for LAC compared to ScE (0.75 versus 0.62). In the human study, the LAC measure was a better predictor of ROSC following initial defibrillation as reflected by an AUC of 0.77 for LAC compared to 0.57 for ScE.ConclusionsThe LAC is an improvement over the ScE because the LAC retains its prognostic characteristics at lower ECG sampling rates typical of current clinical defibrillators. Hence, the LAC may have a role in better allocating treatment in resuscitation of VF cardiac arrest.

Project description:Beat-to-beat variability of repolarization duration (BVR) is an intrinsic characteristic of cardiac function and a better marker of proarrhythmia than repolarization prolongation alone. The ionic mechanisms underlying baseline BVR in physiological conditions, its rate dependence, and the factors contributing to increased BVR in pathologies remain incompletely understood. Here, we employed computer modeling to provide novel insights into the subcellular mechanisms of BVR under physiological conditions and during simulated drug-induced repolarization prolongation, mimicking long-QT syndromes type 1, 2, and 3. We developed stochastic implementations of 13 major ionic currents and fluxes in a model of canine ventricular-myocyte electrophysiology. Combined stochastic gating of these components resulted in short- and long-term variability, consistent with experimental data from isolated canine ventricular myocytes. The model indicated that the magnitude of stochastic fluctuations is rate dependent due to the rate dependence of action-potential (AP) duration (APD). This process (the "active" component) and the intrinsic nonlinear relationship between membrane current and APD ("intrinsic component") contribute to the rate dependence of BVR. We identified a major role in physiological BVR for stochastic gating of the persistent Na(+) current (INa) and rapidly activating delayed-rectifier K(+) current (IKr). Inhibition of IKr or augmentation of INa significantly increased BVR, whereas subsequent β-adrenergic receptor stimulation reduced it, similar to experimental findings in isolated myocytes. In contrast, β-adrenergic stimulation increased BVR in simulated long-QT syndrome type 1. In addition to stochastic channel gating, AP morphology, APD, and beat-to-beat variations in Ca(2+) were found to modulate single-cell BVR. Cell-to-cell coupling decreased BVR and this was more pronounced when a model cell with increased BVR was coupled to a model cell with normal BVR. In conclusion, our results provide new insights into the ionic mechanisms underlying BVR and suggest that BVR reflects multiple potentially proarrhythmic parameters, including increased ion-channel stochasticity, prolonged APD, and abnormal Ca(2+) handling.

Project description:Background and Objectives: Enhanced beat-to-beat variability of ventricular repolarization (BVR) has been linked to arrhythmias and sudden cardiac death. Recent experimental studies on human left ventricular epicardial electrograms have shown that BVR closely interacts with low-frequency (LF) oscillations of activation recovery interval during sympathetic provocation. In this work human ventricular computational cell models are developed to reproduce the experimentally observed interactions between BVR and its LF oscillations, to assess underlying mechanisms and to establish a relationship with arrhythmic risk. Materials and Methods: A set of human ventricular action potential (AP) models covering a range of experimental electrophysiological characteristics was constructed. These models incorporated stochasticity in major ionic currents as well as descriptions of β-adrenergic stimulation and mechanical effects to investigate the AP response to enhanced sympathetic activity. Statistical methods based on Automatic Relevance Determination and Canonical Correlation Analysis were developed to unravel individual and common factors contributing to BVR and LF patterning of APD in response to sympathetic provocation. Results: Simulated results reproduced experimental evidences on the interactions between BVR and LF oscillations of AP duration (APD), with replication of the high inter-individual variability observed in both phenomena. ICaL, IKr and IK1 currents were identified as common ionic modulators of the inter-individual differences in BVR and LF oscillatory behavior and were shown to be crucial in determining susceptibility to arrhythmogenic events. Conclusions: The calibrated family of human ventricular cell models proposed in this study allows reproducing experimentally reported interactions between BVR and LF oscillations of APD. Ionic factors involving ICaL, IKr and IK1 currents are found to underlie correlated increments in both phenomena in response to sympathetic provocation. A link to arrhythmogenesis is established for concomitantly elevated levels of BVR and its LF oscillations.

Project description:BackgroundAtrial electrical and structural remodelling in older individuals with cardiovascular risk factors has been associated with changes in surface electrocardiographic (ECG) parameters (e.g., prolongation of the PR interval) and higher risks of atrial fibrillation (AF). However, it has been difficult to establish whether altered ECG parameters are the cause or a consequence of the myocardial substrate leading to AF. This study aimed to examine the potential causal relevance of ECG parameters on risk of AF using mendelian randomisation (MR).Methods and findingsWeighted genetic scores explaining lifelong differences in P-wave duration, PR interval, and QT interval were constructed, and associations between these ECG scores and risk of AF were estimated among 278,792 UK Biobank participants (mean age: 57 years at recruitment; 19,132 AF cases). The independent genetic variants contributing to each of the separate ECG scores, and their corresponding weights, were based on published genome-wide association studies. In UK Biobank, genetic scores representing a 5 ms longer P-wave duration or PR interval were significantly associated with lower risks of AF (odds ratio [OR] 0.91; 95% confidence interval [CI]: 0.87-0.96, P = 2 × 10-4 and OR 0.94; 95% CI: 0.93-0.96, P = 2 × 10-19, respectively), while longer QT interval was not significantly associated with AF. These effects were independently replicated among a further 17,931 AF cases from the AFGen Consortium. Investigation of potential mechanistic pathways showed that differences in ECG parameters associated with specific ion channel genes had effects on risk of AF consistent with the overall scores, while the overall scores were not associated with changes in left atrial size. Limitations of the study included the inherent assumptions of MR, restriction to individuals of European ancestry, and possible restriction of results to the normal ECG ranges represented in UK Biobank.ConclusionsIn UK Biobank, we observed evidence suggesting a causal relationship between lifelong differences in ECG parameters (particularly PR interval) that reflect longer atrial conduction times and a lower risk of AF. These findings, which appear to be independent of atrial size and concomitant cardiovascular comorbidity, support the relevance of varying mechanisms underpinning AF and indicate that more individualised treatment strategies warrant consideration.

Dataset Information

Absolute beat-to-beat variability and instability parameters of ECG intervals: biomarkers for predicting ischaemia-induced ventricular fibrillation.

Background and purpose

Experimental approach

Key results

Conclusions and implications

Publications

Absolute beat-to-beat variability and instability parameters of ECG intervals: biomarkers for predicting ischaemia-induced ventricular fibrillation.

Similar Datasets

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