Artificial intelligence (AI)-based electrocardiogram (ECG) analysis has emerged as a promising adjunct to human ECG interpretation in suspected ST-segment elevation myocardial infarction (STEMI). To expand knowledge in this evolving field, the authors retrospectively analyzed the performance of a novel AI-ECG model in patients with cardiac catheterization laboratory activation for suspected STEMI. Consecutive patients were gathered from a multicenter U.S. STEMI registry (2018-2022) and categorized into 3 clinical cohorts based on the presence or absence of angiographic culprit and troponin elevation: acute myocardial infarction (AMI) with culprit, AMI without culprit, and no-AMI. Cardiac catheterization laboratory-activating ECGs were analyzed using an AI-ECG model trained to identify acute coronary occlusion and classified as occlusion myocardial infarction, OMI(+) or not, OMI(-). The study included 2,523 patients, 68.3% male, with a median age of 63 years. AMI with culprit was present in 2076 (82.3%), AMI without culprit in 314 (12.4%), and no-AMI in 133 (5.3%). Among AMI with culprit patients, the model correctly identified 93.8% as OMI(+). Sensitivity for TIMI flow 0/1, 2, and 3 was 96.3%, 93.1%, and 86.9% respectively; P < 0.001. The model correctly identified 79.7% of no-AMI patients as OMI(-). The AUCROC was 0.952 (95% CI: 0.924-0.966). The AMI without culprit cohort included takotsubo syndrome OMI(+) = 78%, MI with nonobstructive coronary arteries OMI(+) = 61%, and myopericarditis OMI(+) = 67%. In suspected STEMI, this AI-ECG model correctly identified nearly all patients with acute coronary obstruction and most of those without AMI. If prospectively validated, this approach could improve management of patients with suspected AMI.

Cardiac anxiety, characterized by cardiac-related fear and avoidance, is common after myocardial infarction (MI) and is associated with reduced quality of life and adverse prognosis. Despite its clinical relevance, cardiac anxiety remains underaddressed in routine post-MI care. The objective of the study was to evaluate the efficacy of a therapist-guided, digitally delivered exposure-based cognitive behavioral therapy intervention for cardiac anxiety (CA-CBT) in patients after MI. In this randomized clinical trial, patients with a history of type 1 MI (≥6 months prior) and clinically significant cardiac anxiety were randomly assigned to 8 weeks of digital CA-CBT or usual care. The primary outcome was disease-specific health status assessed at 3-month follow-up using the Seattle Angina Questionnaire; cardiac anxiety was also assessed. Compared with usual care, CA-CBT was associated with greater improvements in disease-specific health status, particularly quality of life and physical limitation, as well as greater reductions in cardiac anxiety. Treatment effects were sustained at 12 months. A therapist-guided, digitally delivered CBT intervention targeting cardiac anxiety improved disease-specific health status and reduced cardiac anxiety after MI, with durable effects. These findings support the clinical relevance of integrating psychological interventions into multidisciplinary secondary prevention after MI. (Online Cognitive Behavioral Therapy Targeting Cardiac Anxiety [MI-CBT]; NCT05580718).

The role of transcatheter aortic valve replacement (TAVR) in nonagenarians remains uncertain, especially regarding long-term outcomes and prognostic factors. This study aimed to evaluate long-term outcomes of TAVR in nonagenarians, focusing on cause-specific mortality and the prognostic influence of frailty and malnutrition. We analyzed 4,623 patients who underwent transfemoral TAVR in a multicenter Japanese registry, including 700 aged ≥90 years. Outcomes were followed for 5 years. We analyzed all-cause mortality, cause-specific mortality, and the prognostic impact of the Clinical Frailty Scale and Geriatric Nutritional Risk Index. At 5 years, all-cause mortality was higher in patients aged ≥90 years than in those <90 years (53.2% vs37.0%, P < 0.001), primarily due to noncardiovascular deaths such as senility and infections (32.5% vs 19.9%; P < 0.001). Cardiovascular mortality was similar (20.3% vs 17.0%; P = 0.198). Multivariable analysis showed that age ≥90 years was not an independent predictor; frailty and malnutrition were the strongest prognostic factors. A Clinical Frailty Scale-Geriatric Nutritional Risk Index heatmap revealed marked heterogeneity, identifying subgroups of nonagenarians with preserved nutrition and low frailty who achieved favorable long-term survival. In this large multicenter registry, excess mortality in nonagenarians after TAVR was driven mainly by noncardiovascular causes. Frailty and malnutrition, rather than chronological age, were central determinants of long-term outcomes. These findings emphasize that TAVR candidacy in nonagenarians should be guided on geriatric assessment of frailty and nutrition to identify patients most likely to achieve meaningful survival while avoiding futile interventions.