Risk prediction of inappropriate implantable cardioverter-defibrillator therapy using machine learning

We aimed to develop machine learning-based predictive models for identifying inappropriate implantable cardioverter-defibrillator (ICD) therapy. Our study included 182 consecutive cases (average age 62.2 ± 4.5 years, 169 men) and employed 14 non-deep learning models for prediction (hold-out method). These models utilized selected electrocardiogram parameters and clinical features collected after ICD implantation. From the feature importance analysis of the best ML model, we established easily calculable scores. Among the patients, 25 (13.7%) experienced inappropriate therapy, and we identified 16 significant predictors. Using recursive feature elimination with cross-validation, we reduced the features to six with high feature importance: history of atrial arrhythmia (Atr-arrhythm), ischemic cardiomyopathy (ICM), absence of diabetes mellitus (DM), lack of cardiac resynchronization therapy (CRT), V3 ST level at J point (V3 STJ), and V5 R-wave amplitudes (V5R amp). The extra-trees classifier yielded the highest area under receiver operating characteristics curve (AUROC; 0.869 on test data). Thus, the Cardi35 score was defined as [+ 5.5*Atr-arrhythm - 1.5*CRT + 1.0*V3STJ + 1.0*V5R - 1.0*ICM - 0.5*DM], which demonstrated a hazard ratio of 1.62 (P < 0.001). A cut-off value of the score + 5.5 showed high AUROC (0.826). The ML approach can yield a robust prediction model, and the Cardi35 score was a convenient predictor for inappropriate therapy.

Efficacy and Limitations of Tachycardia Detection Interval Guided Reprogramming for Reduction of Inappropriate Shock in Implantable Cardioverter-Defibrillator Patients

The avoidance of inappropriate shock therapy is an important clinical issue in implantable cardioverter-defibrillator (ICD) patients. We retrospectively analyzed therapeutic events in ICD patients, and the effect of tachycardia detection interval (TDI) and tachycardia cycle length (TCL) guided reprograming on the reduction of inappropriate ICD therapy. The clinical determinants of after reprogramming were also evaluated.A total of 254 consecutive ICD patients were included in the study, and the incidence of antitachycardia therapy was evaluated during the follow-up period of 27.3 ± 18.7 months. When inappropriate antitachycardia therapy appeared, TDI was reprogrammed not to exceed the detected TCL and the patients continued to be followed-up. Various clinical parameters were compared between patients with and without inappropriate ICD therapy. During the initial follow-up period of 18.6 ± 15.6 months, ICD therapy occurred in 127/254 patients (50%) including inappropriate antitachycardia pacing (ATP) (12.9%) and shock (44.35%). Determinants of initial inappropriate therapy were dilated cardiomyopathy (DCM), history of therapeutic hypothermia, and QRS duration. Of the 61 patients with inappropriate therapy, 24 received TCL guided reprogramming. During the additional observation period of 17.0 ± 16.8 months, inappropriate therapy recurred in 5/24 patients (2 ATP, 3 shocks). The determinant of these inappropriate therapy events after reprogramming was the presence of supraventricular tachycardia.By applying simple TCL and TDI guided reprogramming, inappropriate therapy was reduced by 79%. The determinant of inappropriate therapy after reprogramming was the presence of supraventricular tachycardia.