In-hospital bioimpedance-derived total body water predicts short-term cardiovascular mortality and re-hospitalizations in acute decompensated heart failure patients.

Background: Hospital re-admissions in heart failure (HF) patients are mostly caused by an acute exacerbation of their chronic congestion. Bioimpedance analysis (BIA) has emerged as a promising non-invasive method to assess the volume status in HF. However, its correlation with clinically assessed volume status and its prognostic value in the acute intra-hospital setting remains uncertain.

BPA Exposure Affects Mouse Gastruloids Axial Elongation by Perturbing the Wnt/β-Catenin Pathway.

Mammalian embryos are very vulnerable to environmental toxicants (ETs) exposure. Bisphenol A (BPA), one of the most diffused ETs, exerts endocrine-disrupting effects through estro-gen-mimicking and hormone-like properties, with detrimental health effects, including on reproduction. However, its impact during the peri-implantation stages is still unclear.

Prediction of Left Ventricle Pressure Indices Via a Machine Learning Approach Combining ECG, Pulse Oximetry, and Cardiac Sounds: a Preclinical Feasibility Study.

Heart failure (HF) is defined as the inability of the heart to meet body oxygen demand requiring an elevation in left ventricular filling pressures (LVP) to compensate. LVP increase can be assessed in the cardiac catheterization laboratory, but this procedure is invasive and time-consuming to the extent that physicians rather rely on non-invasive diagnostic tools. In this work, we assess the feasibility to develop a novel machine-learning (ML) approach to predict clinically relevant LVP indices.