The coin toss: implications for risk stratification for sudden cardiac death

Predicting Electrical Storm Using Episodes' Parameters from ICD Recorded Data

Electrical storm (ES) is a life-threatening heart condition for patients with implantable cardioverter defibrillators (ICDs). ICD patients experienced episodes are at higher risk for ES. However, predicting ES using previous episodes' parameters recorded by ICDs have never been developed. This study aims to predict ES using machine learning models based on ICD remote monitoring-summaries during episodes in the anonymized large number of patients. Episode ICD-summaries from 16,022 patients were used to construct and evaluate two models, logistic regression and random forest, for predicting the short-term risk of ES. Episode parameters in this study included the total number of sustained episodes, shocks delivered and the cycle length parameters. The models evaluated on the data sections not used for model development. Random forest performed significantly better than logistic regression (P <; 0.01), achieving a test accuracy of 0.99 and an Area Under an ROC Curve (AUC) of 0.93 (vs. an accuracy of 0.98 and an AUC of 0.90). The total number of previous sustained episodes was the most relevant variables in the both models.

Personalizing Risk Stratification for Sudden Death in Dilated Cardiomyopathy: The Past, Present, and Future

Results from the DANISH Study (Danish Study to Assess the Efficacy of ICDs in Patients With Non-Ischemic Systolic Heat Failure on Mortality) suggest that for many patients with dilated cardiomyopathy (DCM), implantable cardioverter-defibrillators do not increase longevity. Accurate identification of patients who are more likely to die of an arrhythmia and less likely to die of other causes is required to ensure improvement in outcomes and wise use of resources. Until now, left ventricular ejection fraction has been used as a key criterion for selecting patients with DCM for an implantable cardioverter-defibrillator for primary prevention purposes. However, registry data suggest that many patients with DCM and an out-of-hospital cardiac arrest do not have a markedly reduced left ventricular ejection fraction. In addition, many patients with reduced left ventricular ejection fraction die of nonsudden causes of death. Methods to predict a higher or lower risk of sudden death include the detection of myocardial fibrosis (a substrate for ventricular arrhythmia), microvolt T-wave alternans (a marker of electrophysiological vulnerability), and genetic testing. Midwall fibrosis is identified by late gadolinium enhancement cardiovascular magnetic resonance imaging in ≈30% of patients and provides incremental value in addition to left ventricular ejection fraction for the prediction of sudden cardiac death events. Microvolt T-wave alternans represents another promising predictor, supported by large meta-analyses that have highlighted the negative predictive value of this test. However, neither of these strategies have been routinely adopted for risk stratification in clinical practice. More convincing data from randomized trials are required to inform the management of patients with these features. Understanding of the genetics of DCM and how specific mutations affect arrhythmic risk is also rapidly increasing. The finding of a mutation in lamin A/C, the cause of ≈6% of idiopathic DCM, commonly underpins more aggressive management because of the malignant nature of the associated phenotype. With the expansion of genetic sequencing, the identification of further high-risk mutations appears likely, leading to better-informed clinical decision making and providing insight into disease mechanisms. Over the next 5 to 10 years, we expect these techniques to be integrated into the existing algorithm to form a more sensitive, specific, and cost-effective approach to the selection of patients with DCM for implantable cardioverter-defibrillator implantation.

Asymptomatic Wolff-Parkinson-White Syndrome: Who Should Be Treated?

This article discusses the merits of electrophysiology study (EPS) and/or ablation for asymptomatic preexcitation Wolff-Parkinson-White (WPW) ECG pattern. Sudden deaths in asymptomatic patients are too few to merit broad screening and aggressive intervention. It also discusses the risks of ablation and the low predictive accuracy of EPS. When WPW is an incidental finding, the decision to proceed with investigation and ablation can be made considering patients' situations and preferences. An invasive strategy is targeted at patients concerned about the low risk of life-threatening arrhythmia as a first presentation after a discussion of the risks and benefits.

Intracardiac QT integral on far-field ICD electrogram predicts sustained ventricular tachyarrhythmias in ICD patients

BACKGROUND

Prediction of sustained ventricular tachycardia (VT)/ventricular fibrillation (VF) could help to guide preventive interventions in at-risk patients. The QRST integral (∫QT) reflects intrinsic repolarization properties.

OBJECTIVE

The objective of this study was to determine whether intracardiac ∫QT predicts VT/VF in the next few months in patients with implantable cardioverter defibrillators (ICDs).

METHODS

Far-field (FF) and near-field (NF) right ventricular intracardiac electrograms (EGMs) were recorded via telemetry in 46 patients with structural heart disease and ICDs implanted for secondary prevention of sudden cardiac death. Epochs of 4.9 ± 0.4 minutes during sinus rhythm (mean heart rate 70.9 ± 15.2 beats/min) and ventricular pacing at 105 beats/min were analyzed. Mean ∫QT was calculated on FF and NF EGMs as the algebraic sum of areas under the QRST curve and adjusted by mean heart rate. Patients were followed up for at least 3 months. True VT/VF events treated by the ICD served as the end point.

RESULTS

During a mean follow-up of 4.6 months, 22 patients (48%) were treated for VT/VF. Unadjusted and adjusted by heart rate, FF EGM ∫QT in sinus rhythm was a significant predictor of VT/VF (unadjusted ∫QT hazard ratio 1.007; 95% confidence interval 1.002 to 1.0013; P = .007; adjusted ∫QT hazard ratio 1.68; 95% confidence interval 1.19 to 2.36; P = .002). The highest quartile of intracardiac ∫QT predicted VT/VF (log-rank test P = .042) and identified patients at risk with a specificity of 86% and positive predictive value of 73%.

CONCLUSION

Increased intracardiac FF EGM ∫QT predicts VT/VF in patients with structural heart disease and secondary prevention ICDs.