Journal of the American Heart Association
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Multicenter Study Clinical Trial
Atrial Arrhythmias in Clinically Manifest Cardiac Sarcoidosis: Incidence, Burden, Predictors, and Outcomes.
Background Recent data have suggested a substantial incidence of atrial arrhythmias (AAs) in cardiac sarcoidosis (CS). Our study aims were to first assess how often AAs are the presenting feature of previously undiagnosed CS. Second, we used prospective follow-up data from implanted devices to investigate AA incidence, burden, predictors, and response to immunosuppression. ⋯ Second, AAs occurred in a minority of patients at follow-up; the burden was very low in most patients. Only 2 patients had clinically significant AA burden, and both had a reduction after CS was treated. Registration URL: https://www.clinicaltrials.gov; unique identifier NCT01477359.
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Multicenter Study
Phenotyping Heart Failure According to the Longitudinal Ejection Fraction Change: Myocardial Strain, Predictors, and Outcomes.
Background Many patients with heart failure (HF) experience changes in left ventricular ejection fraction (LVEF) during follow-up. We sought to evaluate the predictors and outcomes of different HF phenotypes according to longitudinal changes in EF. Methods and Results A total of 2104 patients with acute HF underwent echocardiography at baseline and follow-up. ⋯ Each HF phenotype according to longitudinal LVEF changes has a distinct prognosis. Global longitudinal strain can be used to predict the HF phenotype. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03513653.
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Multicenter Study Comparative Study Observational Study
Long-Term (10-Year) Outcomes of Stenting or Bypass Surgery for Left Main Coronary Artery Disease in Patients With and Without Diabetes Mellitus.
Background Data are still limited regarding whether there are differential long-term outcomes after percutaneous coronary intervention versus coronary artery bypass grafting (CABG) for left main coronary artery disease with or without diabetes mellitus (DM). Methods and Results Using the 10-year data from the MAIN-COMPARE (Revascularization for Unprotected Left Main Coronary Artery Stenosis: Comparison of Percutaneous Coronary Angioplasty Versus Surgical Revascularization) registry, we sought to examine the effect of DM on comparative outcomes after percutaneous coronary intervention or CABG in patients with unprotected left main coronary artery disease. The outcomes of interest were all-cause mortality; a composite of death, Q-wave myocardial infarction, or stroke; and target-vessel revascularization. ⋯ Conclusions In this cohort of patients with longest follow-up who underwent left main coronary artery revascularization, the clinical impact of DM favoring CABG over percutaneous coronary intervention has diminished over time from the bare-metal stent to the drug-eluting stent era. Registration URL: http://www.clinicaltrials.gov. Unique identifier: NCT02791412.
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Multicenter Study Comparative Study Observational Study
Coronary Angiography and Intervention in Women Resuscitated From Sudden Cardiac Death.
Background Coronary artery disease is the primary etiology for sudden cardiac arrest in adults, but potential differences in the incidence and utility of invasive coronary testing between resuscitated men and women have not been extensively evaluated. Our aim was to characterize angiographic similarities and differences between men and women after cardiac arrest. Methods and Results Data from the International Cardiac Arrest Registry-Cardiology database included patients resuscitated from out-of-hospital cardiac arrest of presumed cardiac origin, admitted to 7 academic cardiology/resuscitation centers during 2006 to 2017. ⋯ Women were also less often re-vascularized (44% versus 52%, P<0.03). Conclusions Among cardiac arrest survivors, women are less likely to undergo angiography or percutaneous coronary intervention than men. Sex disparities for invasive therapies in post-cardiac arrest care need continued attention.
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Multicenter Study
Deep Learning-Based Algorithm for Detecting Aortic Stenosis Using Electrocardiography.
Background Severe, symptomatic aortic stenosis (AS) is associated with poor prognoses. However, early detection of AS is difficult because of the long asymptomatic period experienced by many patients, during which screening tools are ineffective. The aim of this study was to develop and validate a deep learning-based algorithm, combining a multilayer perceptron and convolutional neural network, for detecting significant AS using ECGs. ⋯ During internal and external validation, the areas under the receiver operating characteristic curve of the deep learning-based algorithm using 12-lead ECG for detecting significant AS were 0.884 (95% CI, 0.880-0.887) and 0.861 (95% CI, 0.858-0.863), respectively; those using a single-lead ECG signal were 0.845 (95% CI, 0.841-0.848) and 0.821 (95% CI, 0.816-0.825), respectively. The sensitivity map showed the algorithm focused on the T wave of the precordial lead to determine the presence of significant AS. Conclusions The deep learning-based algorithm demonstrated high accuracy for significant AS detection using both 12-lead and single-lead ECGs.