Chang, Sung‐A

Abstract Aims To assess the performance of an artificial intelligence-enabled electrocardiogram (AI-ECG) algorithm in identifying patients with moderate to severe aortic stenosis (AS) in an Asian cohort from a tertiary care centre. Methods and results We identified a randomly selected patients ≥60 years old who underwent echocardiography and ECG within in 31 days between 2012 and 2021 at the Samsung Medical Center in Korea. Patients with previous cardiac surgery, prosthetic valves, or pacemakers were excluded. The AI-ECG model, originally developed and validated by Mayo Clinic in the USA, was applied without fine-tuning. Performance metrics, including the area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy, were calculated to compare AI-ECG predictions with TTE-confirmed AS status. Among 5425 patients, 1095 had moderate to severe AS, and 4330 age- and sex-matched patients without AS were included as controls. The AI-ECG model achieved an AUC of 0.85 (95% CI: 0.84–0.87) in detecting moderate to severe AS. Sensitivity, specificity, PPV, NPV, and accuracy were 0.83, 0.65, 0.37, 0.94, and 68.29%, respectively. The model's performance was consistent across various age and sex subgroups, with sensitivity increasing in older patients. Conclusion The AI-ECG model developed in the USA demonstrated comparable performance in detecting moderate to severe AS in an Asian cohort compared with its original validation population. These findings highlight the potential utility of AI-ECG as a non-invasive screening tool for AS across diverse patient populations.

Background: Conventional transthoracic echocardiography (TTE) is currently not recommended as an initial test to diagnose coronary artery disease (CAD) due to its insensitivity. Left ventricular (LV) strain was reported to be more sensitive than regional wall motion abnormality (RWMA). The aim of this study was to evaluate the usefulness of TTE including LV strain analysis in initial assessment of acute chest pain in emergency department (ED). Methods: Patients visiting ED with acute chest pain were included. Patients with ST elevation myocardial infarct (MI), hemodynamic instability, known CAD or cardiomyopathy, high probability of non-cardiac chest pain, and poor echocardiographic window were excluded. All the patients were initially assessed by an ED physician for pretest probability of CAD. TTE was performed including LV strain image and global and regional LV longitudinal stain (S GL and S RL ) was analyzed online. S RL abnormality was defined as decreased S RL in at least 2 adjacent segments. Diagnosis of CAD (based on coronary angiography or CT angiography) and cardiac events (cardiac death, revascularization, MI, or recurrent ED visit due to chest pain) were reviewed at 1 month after ED visit. Results: Overall 104 patients were analyzed. CAD was diagnosed in 24% (n=25) and cardiac event was detected in 25% (n=26) of patients.Diagnostic accuracy for CAD was higher when using S RL with cut-off value of -13% (sensitivity of 89%, specificity of 77%, NPV = 92%, PPV = 70%) than when using RWMA (sensitivity of 62%, specificity of 88%, NPV = 80%, PPV = 76%). S RL showed better diagnostic performance for CAD than S GL , and pretest probability (Figure). Predictive value of S RL for cardiac events was also highest in those of S GL , RWMA, and pretest probability (Figure). Conclusion: LV strain echocardiography can diagnose the CAD and predict future events with high accuracy. TTE including strain analysis can be used as an initial diagnostic tool in evaluation of acute chest pain in ED.

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.

Objectives We investigated haemodynamics and clinical outcomes according to type of pulmonary hypertension (PH) in patients with constrictive pericarditis (CP). Background As the prevalence of CP with concomitant myocardial disease (mixed CP) grows, PH is more commonly seen in patients with CP. However, haemodynamic and outcome data according to the presence or absence of PH are limited. Methods 150 patients with surgically confirmed CP who underwent echocardiography and cardiac catheterisation within 7 days at two tertiary centres were divided into three groups: no-PH, isolated postcapillary PH (Ipc-PH) and combined postcapillary and precapillary PH (Cpc-PH). Primary outcome was all-cause mortality during follow-up. Result In this retrospective cohort study, 110 (73.3%) had PH (mean pulmonary artery pressure ≥25 mm Hg). Cpc-PH, using defined cut-offs for pulmonary vascular resistance (>3 Wood units) or diastolic pulmonary gradient (≥7 mm Hg), was seen in 18 patients (12%). The Cpc-PH group had a higher prevalence of comorbidities (diabetes and atrial fibrillation) and concomitant myocardial disease as an aetiology of CP than other groups. Pulmonary vascular resistance had a significant direct correlation with medial E/e′ by Doppler echocardiography (r=0.404, p<0.001). Survival rate was significantly lower in the Cpc-PH than the no-PH (p=0.002) and Ipc-PH (p=0.024) groups. On multivariable analysis, age, New York Heart Association functional class IV, medial e′ velocity, Cpc-PH and Ipc-PH were independently associated with long-term mortality. Conclusion Combined postcapillary and precapillary PH develops in a subset of patients with CP and is associated with long-term mortality after pericardiectomy.