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This study aimed to evaluate the modification of non-invasive myocardial work (MW) indices related to aortic stenosis (AS) stages of cardiac damage and their prognostic value. The echocardiographic and outcome data of 170 patients, with asymptomatic moderate-to-severe AS and left ventricular ejection fraction (LVEF) ≥ 50%, and 50 age- and sex-comparable healthy controls were analysed. Primary endpoints were the occurrence of all-cause and cardiovascular death. Increased values of the global work index (GWI), global constructive work (GCW), and global wasted work (GWW) were observed in AS patients compared to controls (GWI: 2528 ± 521 vs. 2005 ± 302 mmHg%, GCW: 2948 ± 598 vs. 2360 ± 353 mmHg%, p < 0.001; GWW: 139 ± 90 vs. 90 ± 49 mmHg%, p = 0.005), with no changes in the global work efficiency. When patients were stratified according to the stages of cardiac damage, the GWI showed lower values in Stage 3−4 as compared to Stage 0 and Stage 2 (p = 0.024). During a mean follow-up of 30 months, 27 patients died. In multivariable Cox-regression analysis, adjusted for confounders, GWI (HR: 0.998, CI: 0.997−1.000; p = 0.034) and GCW (HR:0.998, CI: 0.997−0.999; p = 0.003) were significantly associated with excess mortality. When used as categorical variables, a GWI ≤ 1951 mmHg% and a GCW ≤ 2475 mmHg% accurately predicted all-cause and cardiovascular death at 4-year follow-up. In conclusion, in asymptomatic patients with moderate-to-severe AS, reduced values of GWI and GCW are associated with increased mortality. Therefore, the evaluation of MW indices may allow for a better identification of asymptomatic patients with moderate to severe AS and preserved LVEF whom are at increased risk of worse prognosis during follow-up.
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http://dx.doi.org/10.3390/jcm11061555 | DOI Listing |
JACC Heart Fail
September 2025
Université de Lorraine, Inserm, Centre d'Investigations Cliniques Plurithématique 1433, Centre Hospitalier Régional Universitaire de Nancy, Nancy, France.
Clin Res Cardiol
September 2025
Department of Cardiology, University Heart Center, University Hospital Zurich, Center for Translational and Experimental Cardiology (CTEC), University of Zurich, Rämistrasse 100, 8091, Zurich, Switzerland.
Background: Diabetic patients with ST-segment elevation myocardial infarction (STEMI) are at an increased risk of cardiovascular events as compared to non-diabetic patients. This analysis investigated outcomes of diabetic patients presenting with multivessel disease (MVD) and STEMI in a contemporary trial and the relevance of an immediate versus staged multivessel PCI strategy in this high-risk population.
Methods: Patients enrolled in the MULTISTARS AMI trial were stratified according to the presence/absence of diabetes.
Biochem Biophys Rep
December 2025
Henan University of Chinese Medicine, Zhengzhou, 450046, China.
Introduction: 5-Hydroxymethyl furfural (5-HMF) is a furan compound with a molecular formula of CHO. Studies have found that 5-HMF has many pharmacological effects, such as improving hemorheology, anti-inflammatory, antioxidant activity and anti-myocardial ischemia. Identifying the preventive effect of 5-HMF against ischemic stroke and its possible mechanism was the aim of this investigation.
View Article and Find Full Text PDFEClinicalMedicine
October 2025
Department of Cardiology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Background: The benefits of physiology-guided management in acute coronary syndrome (ACS) remain inconclusive due to limited evidence. In our FAVOR III China trial, a quantitative flow ratio (QFR)-based physiology-guided strategy versus standard angiography guidance improved the 1-year primary outcome among participants with coronary artery disease (CAD). We aimed to investigate, in a prespecified analysis, the outcomes of QFR-based physiological guidance in the FAVOR III China participants with low-risk ACS.
View Article and Find Full Text PDFHeart Lung
September 2025
Department of Nursing, College of Medicine, National Cheng Kung University, No. 1, University Road, East District, Tainan City 70101, Taiwan. Electronic address:
Background: In-hospital mortality in patients with acute myocardial infarction (AMI) following primary percutaneous coronary intervention (pPCI) remains a significant concern. Developing a predictive model of in-hospital mortality is crucial for identifying high-risk patients, guiding clinical decisions, and preventing in-hospital mortality. Machine learning (ML) may analyze patterns in large datasets and provide accurate predictions of in-hospital mortality in AMI patients following pPCI.
View Article and Find Full Text PDF