Background: Brugada syndrome is a potential cause of sudden cardiac death (SCD) and is characterized by a distinct ECG, but not all patients with A Brugada ECG develop SCD. In this study we sought to examine if an artificial intelligence (AI) model can predict a previous or future ventricular fibrillation (VF) episode from a Brugada ECG.

Methods and Results: We developed an AI-enabled algorithm using a convolutional neural network. From 157 patients with suspected Brugada syndrome, 2,053 ECGs were obtained, and the dataset was divided into 5 datasets for cross-validation. In the ECG-based evaluation, the precision, recall, and F₁score were 0.79±0.09, 0.73±0.09, and 0.75±0.09, respectively. The average area under the receiver-operating characteristic curve (AUROC) was 0.81±0.09. On per-patient evaluation, the AUROC was 0.80±0.07. This model predicted the presence of VF with a precision of 0.93±0.02, recall of 0.77±0.14, and F₁score of 0.81±0.11. The negative predictive value was 0.94±0.11 while its positive predictive value was 0.44±0.29.

Conclusions: This proof-of-concept study showed that an AI-enabled algorithm can predict the presence of VF with a substantial performance. It implies that the AI model may detect a subtle ECG change that is undetectable by humans.

Background: Recently, the function of high-density lipoprotein (HDL), rather than the HDL cholesterol (HDL-C) level, has been attracting more attention in risk prediction for coronary artery disease (CAD).

Methods and Results: Patients with clinically diagnosed familial hypercholesterolemia (FH; n=108; male/female, 51/57) were assessed cross-sectionally. Serum cholesterol uptake capacity (CUC) levels were determined using our original cell-free assay. Linear regression was used to determine associations between CUC and clinical variables, including low-density lipoprotein cholesterol and the carotid plaque score. Multivariable logistic regression analysis was used to test factors associated with the presence of CAD. Among the 108 FH patients, 30 had CAD. CUC levels were significantly lower among patients with than without CAD (median [interquartile range] 119 [92–139] vs. 142 [121–165] arbitrary units [AU]; P=0.0004). In addition, CUC was significantly lower in patients with Achilles tendon thickness ≥9.0 mm than in those without Achilles tendon thickening (133 [110–157] vs. 142 [123–174] AU; P=0.047). Serum CUC levels were negatively correlated with the carotid plaque score (Spearman’s r=0.37; P=0.00018). Serum CUC levels were significantly associated with CAD, after adjusting for other clinical variables (odds ratio=0.86, 95% CI=0.76–0.96, P=0.033), whereas HDL-C was not.

Conclusions: HDL function, assessed by serum CUC level, rather than HDL-C level, adds risk stratification information among FH patients.

Background: Acute aortic dissection (AAD) is a life-threatening cardiovascular disease, with a reported incidence rate ranging from 2.5 to 7.2 per 100,000 person-years in several population-based registries in Western countries, but epidemiological data are lacking in Japan.

Methods and Results: The Shiga Stroke and Heart Attack Registry is an ongoing multicenter population-based registry of cerebro-cardiovascular diseases. We enrolled patients who developed AAD, defined by any imaging examination method from 2014 to 2015 in Shiga Prefecture. Death certificates were used to identify cases that were not registered at acute care hospitals. The incidence rates of AAD were calculated by age categories and adjusted using standard populations for comparison. We evaluated differences in patient characteristics between Stanford type A-AAD and type B-AAD subtypes. A total of 402 incident cases with AAD were analyzed. The age-adjusted incidence rates using the 2015 Japanese population and the 2013 European Standard Population were 15.8 and 12.2 per 100,000 person-years, respectively. Compared with cases of type B-AAD, those with type A-AAD were older (75.0 vs. 69.9 years, P=0.001) and more likely to be women (62.3% vs. 28.6%, P<0.001).

Conclusions: Population-based incidence rates of AAD in Japan appear to be higher than in previous reports from Western countries. Incident cases with type A-AAD were older and female predominance.

Background: To predict mortality in patients with acute heart failure (AHF), we created and validated an internal clinical risk score, the KICKOFF score, which takes physical and social aspects, in addition to clinical aspects, into account. In this study, we validated the prediction model externally in a different geographic area.

Methods and Results: There were 2 prospective multicenter cohorts (1,117 patients in Osaka Prefecture [KICKOFF registry]; 737 patients in Kochi Prefecture [Kochi YOSACOI study]) that had complete datasets for calculation of the KICKOFF score, which was developed by machine learning incorporating physical and social factors. The outcome measure was all-cause death over a 2-year period. Patients were separated into 3 groups: low risk (scores 0–6), moderate risk (scores 7–11), and high risk (scores 12–19). Kaplan-Meier curves clearly showed the score’s propensity to predict all-cause death, which rose independently in higher-risk groups (P<0.001) in both cohorts. After 2 years, the cumulative incidence of all-cause death was similar in the KICKOFF registry and Kochi YOSACOI study for the low-risk (4.4% vs. 5.3%, respectively), moderate-risk (25.3% vs. 22.3%, respectively), and high-risk (68.1% vs. 58.5%, respectively) groups.

Conclusions: The unique prediction score may be used in different geographic areas in Japan. The score may help doctors estimate the risk of AHF mortality, and provide information for decisions regarding heart failure treatment.

Background: Idiopathic bradyarrhythmia is considered to be due to pathological degeneration of the cardiac conduction system (CCS) during aging. There appears to have been no comprehensive genetic investigations in patients with idiopathic bradyarrhythmia.

Methods and Results: Ten autopsy cases with advanced bradyarrhythmia (6 men and 4 women; age: 70–94 years, 81.5±6.9 years; 5 cases each of sinus node dysfunction [SND] and complete atrioventricular block [CAVB]) were genetically investigated by using whole-exome sequencing. Morphometric analysis of the CCS was performed with sex-, age- and comorbidity-matched control cases. As a result, severe loss of nodal cells and distal atrioventricular conduction system were found in SND and CAVB, respectively. However, the conduction tissue loss was not significant in either the atrioventricular node or the proximal bundle of His in CAVB cases. A total of 13 heterozygous potential variants were found in 3 CAVB and 2 SND cases. Of these 13 variants, 4 were missense in the known progressive cardiac conduction disease-related genes: GATA4 and RYR2. In the remaining 9 variants, 5 were loss-of-function mutation with highly possible pathogenicity.

Conclusions: In addition to degenerative changes of selectively vulnerable areas in the heart during advancing age, the vulnerability of the CCS, which may be associated with “rare variants of small effect,” may also be a contributing factor to the degeneration of CCS, leading to “idiopathic” bradyarrhythmia.