A covariance-based algorithm: a novel technique for rhythm discrimination in ICDs

Heart Rate Variability Analysis to Predict Onset of Ventricular Tachyarrhythmias in Implantable Cardioverter Defibrillators

Implantable cardioverter defibrillators (ICDs) are commonly used in patients at high risk of sudden cardiac death (SCD) to help prevent and treat life-threatening arrhythmia. Up to 80% of cases of sudden cardiac death are caused by ventricular tachyarrhythmias (VTA) and the accurate prediction of VTA in patients with ICDs can help prevent SCD. Early prediction allows tiered and less invasive therapies to be used to help prevent VTA which are more easily tolerated by the patient and are less battery intensive. In this work, a comparative study of three types of frequency domain features (spectral, bispectrum, and Fourier-Bessel) for VTA prediction is presented based on heart rate variability (HRV) signals between one and five minutes prior to known SCD. Using Fourier-Bessel features and a standard classification approach resulted in the best performance of 87.5% accuracy, 89.3% sensitivity and 85.7% specificity. These results suggest that Fourier-Bessel features are a promising approach for SCD prediction, and that new feature development can help improve both the sensitivity and specificity of SCD prediction in ICDs.

Reduction of the inappropriate ICD therapies by implementing a new fuzzy logic-based diagnostic algorithm

AIMS

The aim of the study was to analyze the value of a completely new fuzzy logic-based detection algorithm (FA) in comparison with arrhythmia classification algorithms used in existing ICDs in order to demonstrate whether the rate of inappropriate therapies can be reduced.

METHODS

On the basis of the RR intervals database containing arrhythmia events and controls recordings from the ICD memory a diagnostic algorithm was developed and tested by a computer program. This algorithm uses the same input signals as existing ICDs: RR interval as the primary input variable and two variables derived from it, onset and stability. However, it uses 15 fuzzy rules instead of fixed thresholds used in existing devices. The algorithm considers 6 diagnostic categories: (1) VF (ventricular fibrillation), (2) VT (ventricular tachycardia), (3) ST (sinus tachycardia), (4) DAI (artifacts and heart rhythm irregularities including extrasystoles and T-wave oversensing-TWOS), (5) ATF (atrial and supraventricular tachycardia or fibrillation), and 96) NT (sinus rhythm). This algorithm was tested on 172 RR recordings from different ICDs in the follow-up of 135 patients.

RESULTS

All diagnostic categories of the algorithm were present in the analyzed recordings: VF (n = 35), VT (n = 48), ST (n = 14), DAI (n = 32), ATF (n = 18), NT (n = 25). Thirty-eight patients (31.4%) in the studied group received inappropriate ICD therapies. In all these cases the final diagnosis of the algorithm was correct (19 cases of artifacts, 11 of atrial fibrillation and 8 of ST) and fuzzy rules algorithm implementation would have withheld unnecessary therapies. Incidence of inappropriate therapies: 3 vs. 38 (the proposed algorithm vs. ICD diagnosis, respectively) differed significantly (p < 0.05). VT/VF were detected correctly in both groups. Sensitivity and specificity were calculated: 100%, 97.8%, and 100%, 72.9% respectively for FA and tested ICDs recordings (p < 0.05).

CONCLUSIONS

Diagnostic performance of the proposed fuzzy logic based algorithm seems to be promising and its implementation could diminish ICDs inappropriate therapies. We found FA usefulness in correct diagnosis of sinus tachycardia, atrial fibrillation and artifacts in comparison with tested ICDs.

Inappropriate shocks in patients with ICDs: single chamber versus dual chamber

BACKGROUND

Despite the technological evolution of the implantable defibrillator, one of the questions that remains is the possible benefit of the dual chamber versus single chamber implantable cardioverter defibrillator (ICD) in reducing inappropriate shocks.

OBJECTIVE

To evaluate which type of device provides fewer inappropriate shocks (dual chamber versus single chamber) in patients with implantable cardioverter defibrillators (ICDs).

METHODS

Meta-analysis of randomized studies published in the literature comparing dual-chamber implantable cardioverter defibrillators to single chamber devices which have been known to cause, as an evaluated endpoint, inappropriate shocks.

RESULTS

The dual-chamber implantable cardioverter showed no benefit in reducing the number of inappropriate shocks. In fact, the opposite was shown. In the analysis of fixed effects, the association tended to favor single-chamber implantable cardioverter defibrillators (OR = 1.53, CI 95%: 0.91-2.57), despite the absence of statistical significance (p = 0.11). We highlight the heterogeneity observed in the results (I² = 53%), which motivated a replication of the analysis using a model of random effects. However, significant differences remained in the occurrence of inappropriate shocks in both groups (OR = 1.1, 95% CI: 0.37-3.31; p = 0.86). To complement the analysis, we proceeded to perform sensitivity analysis, which showed that the exclusion of a study resulted in the lowest heterogeneity observed (I²=24%) and the association with inappropriate shocks significantly favored the single chamber cardiodefibrillator (OR = 1.91; 95% CI: 1.09-3.37; p = 0.27).

CONCLUSIONS

It was determined that there was no clear evidence of superiority of any of the devices evaluated.

A new approach for ICD rhythm classification based on support vector machines

Inappropriate shocks due to misclassification of supraventricular and ventricular arrhythmias remain a major problem in the care of patients with Implantable Cardioverter Defibrillators (ICDs). The purpose of this study was to investigate the ability of a new covariance-based support vector machine classifier, to distinguish ventricular tachycardia from other rhythms such as supraventricular tachycardia. The proposed algorithm is applicable on both single and dual chamber ICDs and has a low computational demand. The results demonstrate that suggested algorithm has considerable promise and merits further investigation.