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Background: Gastrointestinal bleeding (GIB) is a severe and potentially life-threatening complication in patients with acute myocardial infarction (AMI), significantly affecting prognosis during hospitalization. Early identification of high-risk patients is essential to reduce complications, improve outcomes, and guide clinical decision-making.

Objective: This study aimed to develop and validate a machine learning (ML)-based model for predicting in-hospital GIB in patients with AMI, identify key risk factors, and evaluate the clinical applicability of the model for risk stratification and decision support.

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Cardiovascular and cardiometabolic diseases are leading causes of morbidity and mortality worldwide, driven in part by chronic inflammation. Emerging research suggests that the bone marrow microenvironment, or marrow niche, plays a critical role in both immune system regulation and disease progression. The bone marrow niche is essential for maintaining hematopoietic stem cells (HSCs) and orchestrating hematopoiesis.

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Objectives: The aim of this study was to develop and validate a nomogram model that predicts the risk of bone metastasis (BM) in a prostate cancer (PCa) population.

Methods: We retrospectively collected and analyzed the clinical data of patients with pathologic diagnosis of PCa from January 1, 2013 to December 31, 2022 in two hospitals in Yangzhou, China. Patients from the Affiliated Hospital of Yangzhou University were divided into a training set and patients from the Affiliated Clinical College of Traditional Chinese Medicine of Yangzhou University were divided into a validation set.

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The aim of this study was to determine the prevalence of advanced hepatic fibrosis and to individualize using Bayesian analysis its associated risk factors in patients with metabolic dysfunction-associated steatotic liver disease (MASLD) being cared for in three Alsatian cardio-metabolic health networks in the North East of France. Overall, 712 patients aged ≥18 years with a female predominance were included into a prospective, cross-sectional, and observational study. Advanced fibrosis and severe steatosis were evaluated using transient elastography (FibroScan®).

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Background: Primary hyperparathyroidism (PHPT) due to a parathyroid adenoma stands as one of the most prevalent endocrinological disorders, with focused parathyroidectomy being the established therapeutic strategy.

Aim: This study aims to investigate whether the volume of the pathological gland influences perioperative outcomes and postoperative morbidity.

Methods: A retrospective analysis was conducted on data from 141 patients who underwent focused parathyroidectomy for PHPT at the University Hospital of Basel between 2007 and 2022.

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