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Abstract Background Despite the positive impact of implantable cardioverter defibrillators (ICDs) and wearable cardioverter defibrillators (WCDs) on prognosis, their implantation is often withheld especially in Japanese heart failure patients with reduced left ventricular ejection fraction (HFrEF) who have not experienced ventricular tachycardia (VT) or ventricular fibrillation (VF) for uncertain reasons. Recent advancements in heart failure (HF) medications have significantly improved the prognosis for HFrEF. Given this context, a critical reassessment of the treatment and prognosis of ICDs and WCDs is essential, as it has the potential to reshape awareness and treatment strategies for these patients. Methods We are initiating a prospective multicenter observational study for HFrEF patients eligible for ICD in primary and secondary prevention, and WCD, regardless of device use, including all consenting patients. Study subjects are to be enrolled from 31 participant hospitals located throughout Japan from April 1, 2023, to December 31, 2024, and each will be followed up for 1 year or more. The planned sample size is 651 cases. The primary endpoint is the rate of cardiac implantable electronic device implementation. Other endpoints include the incidence of VT/VF and sudden death, all‐cause mortality, and HF hospitalization, other events. We will collect clinical background information plus each patient's symptoms, Clinical Frailty Scale score, laboratory test results, echocardiographic and electrocardiographic parameters, and serial changes will also be secondary endpoints. Results Not applicable. Conclusion This study offers invaluable insights into understanding the role of ICD/WCD in Japanese HF patients in the new era of HF medication.

Background: Older candidates for transcatheter aortic valve replacement (TAVR) frequently present with both cardiac and noncardiac comorbidities. There are few risk scores that evaluate a wide range of comorbidities. Methods: Patients who underwent TAVR for severe aortic stenosis were retrospectively evaluated. A new prediction model (Cardiac and nonCardiac Comorbidities risk score: 3C score) was determined based on coefficient in the multivariate Cox regression analysis for two-year all-cause mortality. C-statistics were assessed to compare the predictive abilities of the 3C score, the Charlson Comorbidities Index (CCI) score, the European System for Cardiac Operative Risk Evaluation (EuroSCORE) II, and the Model for End-stage Liver Disease eXcluding International normalized ratio (MELD-XI) score. Results: The present study included 226 patients (age, 86 ± 5 years; males, 38 %). The values of the CCI score, EuroSCORE II, and MELD-XI score were 2 (1–3), 3.36 (2.12–4.58), and 5.35 (3.05–8.55), respectively. Multivariate Cox regression analysis identified two cardiac (left ventricular ejection fraction [LVEF]

Abstract The right ventricular (RV) impairment can predict clinical adverse events in patients following transcatheter aortic valve replacement (TAVR) for severe aortic stenosis (AS). Limited reports have compared impact of the left ventricular (LV) and RV disorders. This retrospective study evaluated two-year major adverse cardiac and cerebrovascular events (MACCE) in patients following TAVR for severe AS. RV sphericity index was calculated as the ratio between RV mid-ventricular and longitudinal diameters during the end-diastolic phase. Of 239 patients, 2-year MACCE were observed in 34 (14%). LV ejection fraction was 58 ± 11%. Tricuspid annular plane systolic excursion (TAPSE) and RV sphericity index were 20 ± 3 mm and 0.36 (0.31–0.39). Although the univariate Cox regression analysis demonstrated that both LV and RV parameters predicted the outcomes, LV parameters no longer predicted them after adjustment. Lower TAPSE (adjusted hazard ratio per 1 mm, 0.84; 95% confidence interval, 0.75–0.93) and higher RV sphericity index (adjusted hazard ratio per 0.1, 1.94; 95% confidence interval, 1.17–3.22) were adverse clinical predictors. In conclusion, the RV structural and functional disorders predict two-year MACCE, whereas the LV parameters do not. Impact of LV impairment can be attenuated after development of RV disorders.

Background: High-intensity plaque (HIP) on magnetic resonance imaging (MRI) has been documented as a powerful predictor of periprocedural myocardial injury (PMI) following percutaneous coronary intervention (PCI). Despite the recent proposal of three-dimensional HIP quantification to enhance the predictive capability, the conventional pulse sequence, which necessitates the separate acquisition of anatomical reference images, hinders accurate three-dimensional segmentation along the coronary vasculature. Coronary atherosclerosis T1-weighted characterization (CATCH) enables the simultaneous acquisition of inherently coregistered dark-blood plaque and bright-blood coronary artery images. We aimed to develop a novel HIP quantification approach using CATCH and to ascertain its superior predictive performance compared to the conventional two-dimensional assessment based on plaque-to-myocardium signal intensity ratio (PMR). Methods: In this prospective study, CATCH MRI was conducted before elective stent implantation in 137 lesions from 125 patients. On CATCH images, dedicated software automatically generated tubular three-dimensional volumes of interest on the dark-blood plaque images along the coronary vasculature, based on the precisely matched bright-blood coronary artery images, and subsequently computed PMR and HIP volume (HIPvol). Specifically, HIPvol was calculated as the volume of voxels with signal intensity exceeding that of the myocardium, weighted by their respective signal intensities. PMI was defined as post-PCI cardiac troponin-T > 5 × the upper reference limit. Results: The entire analysis process was completed within 3 min per lesion. PMI occurred in 44 lesions. Based on the receiver operating characteristic curve analysis, HIPvol outperformed PMR for predicting PMI (C-statistics, 0.870 [95% CI, 0.805–0.936] vs. 0.787 [95% CI, 0.706–0.868]; p = 0.001). This result was primarily driven by the higher sensitivity HIPvol offered: 0.886 (95% CI, 0.754–0.962) vs. 0.750 for PMR (95% CI, 0.597–0.868; p = 0.034). Multivariable analysis identified HIPvol as an independent predictor of PMI (odds ratio, 1.15 per 10-μL increase; 95% CI, 1.01–1.30, p = 0.035). Conclusions: Our semi-automated method of analyzing coronary plaque using CATCH MRI provided rapid HIP quantification. Three-dimensional assessment using this approach had a better ability to predict PMI than conventional two-dimensional assessment.