Lee, Hyun‐Jung

Abstract Aims Recently, deep learning artificial intelligence (AI) models have been trained to detect cardiovascular conditions, including hypertrophic cardiomyopathy (HCM), from the 12-lead electrocardiogram (ECG). In this external validation study, we sought to assess the performance of an AI-ECG algorithm for detecting HCM in diverse international cohorts. Methods and results A convolutional neural network-based AI-ECG algorithm was developed previously in a single-centre North American HCM cohort (Mayo Clinic). This algorithm was applied to the raw 12-lead ECG data of patients with HCM and non-HCM controls from three external cohorts (Bern, Switzerland; Oxford, UK; and Seoul, South Korea). The algorithm’s ability to distinguish HCM vs. non-HCM status from the ECG alone was examined. A total of 773 patients with HCM and 3867 non-HCM controls were included across three sites in the merged external validation cohort. The HCM study sample comprised 54.6% East Asian, 43.2% White, and 2.2% Black patients. Median AI-ECG probabilities of HCM were 85% for patients with HCM and 0.3% for controls (P < 0.001). Overall, the AI-ECG algorithm had an area under the receiver operating characteristic curve (AUC) of 0.922 [95% confidence interval (CI) 0.910–0.934], with diagnostic accuracy 86.9%, sensitivity 82.8%, and specificity 87.7% for HCM detection. In age- and sex-matched analysis (case–control ratio 1:2), the AUC was 0.921 (95% CI 0.909–0.934) with accuracy 88.5%, sensitivity 82.8%, and specificity 90.4%. Conclusion The AI-ECG algorithm determined HCM status from the 12-lead ECG with high accuracy in diverse international cohorts, providing evidence for external validity. The value of this algorithm in improving HCM detection in clinical practice and screening settings requires prospective evaluation.

Abstract Aims To investigate whether left arterial reservoir strain (LASr) could predict new-onset atrial fibrillation (NOAF) in patients with light-chain-type cardiac amyloidosis (ALCA). Methods and results This study enrolled 427 patients with CA from two tertiary centres between 2005 and 2019. LASr was measured using a vendor-independent analysis programme. The primary outcome was NOAF. A total of 287 patients with ALCA were included [median age 63.0 (56.0–70.0) years, 53.3% male]. The median LASr was 13.9% (10.5–20.8%). During the median follow-up of 0.85 years, AF occurred in 34 patients (11.8%). In the receiver operating characteristics curve analysis, the optimal cut-off of LASr for predicting NOAF was 14.4%. Patients with LASr ≤14.4% had a higher risk of NOAF than those with LASr >14.4% (18.1% vs. 5.1%, P < 0.010). In the multivariate analysis adjusting for confounding factors, including left arterial volume index and left ventricular global longitudinal strain (LV-GLS), higher LASr (%) was independently associated with lower risk for NOAF [adjusted hazard ratio (aHR): 0.936, 95% confidence interval (95% CI): 0.879–0.997, P = 0.039]. Furthermore, LASr ≤14.4% was an independent predictor for NOAF (aHR: 3.370, 95% CI: 1.337–8.492, P = 0.010). This remained true after accounting for all-cause death as a competing risk. Compared with Model 1 (LV-GLS) and Model 2 (LV-GLS plus LAVI), Model 3, including LASr showed a better reclassification ability for predicting NOAF (net reclassification index = 0.735, P < 0.001 compared with Model 1; net reclassification index = 0.514, P = 0.003 compared with Model 2). Conclusion LASr was an independent predictor of NOAF in patients with ALCA.

Background and Purpose— Hypertrophic cardiomyopathy patients with atrial fibrillation are at increased risk of stroke, and anticoagulation is strongly recommended. However, limited data are available regarding the safety and effectiveness of non–vitamin K antagonist oral anticoagulants (NOACs) for primary prevention of stroke. Methods— Using the Korean Health Insurance Review and Assessment Service database, we identified 2397 patients with hypertrophic cardiomyopathy and nonvalvular atrial fibrillation on oral anticoagulation from 2013 to 2016 without history of ischemic stroke, intracranial hemorrhage (ICH), or gastrointestinal bleeding (992 on warfarin and 1405 on NOACs). Inverse probability of treatment weighting with propensity scores was used to balance covariates between treatment groups. Risk for ischemic stroke, ICH, gastrointestinal bleeding, death, and their composite outcome associated with NOAC use was assessed with warfarin use as the reference. Results— During a mean follow-up of 1.6 years, the incidence rates of ischemic stroke, ICH, gastrointestinal bleeding, death, and composite outcome were all significantly lower in the NOAC than in the warfarin group (stroke, 2.8 versus 5.0; ICH, 0.5 versus 1.3; gastrointestinal bleeding, 2.3 versus 3.0; death, 3.0 versus 5.1; composite, 7.5 versus 12.5 events per 100 person-years). NOACs were associated with significantly lower risks of ischemic stroke (hazard ratio [HR], 0.47; 95% CI, 0.32–0.68), ICH (HR, 0.31; 95% CI, 0.14–0.69), gastrointestinal bleeding (HR, 0.62; 95% CI, 0.40–0.96), death (HR, 0.45; 95% CI, 0.31–0.65), and the composite outcome (HR, 0.48; 95% CI, 0.38–0.61) than warfarin. The same trend was observed regardless of the NOAC dose and across various high-risk subgroups. In analysis of individual NOACs, all NOACs were associated with lower risks of ischemic stroke and composite outcome. Conclusions— NOACs showed superior effectiveness and safety versus warfarin in the primary prevention of stroke versus warfarin in real-world Asian hypertrophic cardiomyopathy with atrial fibrillation.