Diagnosis and Management of Pulmonary Hypertension and Right Ventricular Failure in the Cardiovascular Intensive Care Unit.

Pulmonary hypertension (PH) encompasses a broad range of conditions, including pulmonary artery hypertension, left-sided heart disease, and pulmonary and thromboembolic disorders. Successful diagnosis and management rely on an integrated clinical assessment of the patient's physiology and right heart function. Right ventricular (RV) heart failure is often a result of PH, but may result from varying abnormalities in preload, afterload, and intrinsic myocardial dysfunction, which require distinct management strategies.

Pulmonary artery diameter correlates with echocardiographic parameters of right ventricular dysfunction in patients with acute pulmonary embolism.

Introduction: Right ventricular dysfunction (RVD) is a key component in the process of risk stratification in patients with acute pulmonary embolism (PE). Echocardiography remains the gold standard for RVD assessment, however, measures of RVD may be seen on CTPA imaging, including increased pulmonary artery diameter (PAD). The aim of our study was to evaluate the association between PAD and echocardiographic parameters of RVD in patients with acute PE.

Clinical outcomes and factors associated with pulmonary infarction following acute pulmonary embolism: a retrospective observational study at a US academic centre.

Objective: Pulmonary infarction is a common clinical and radiographic finding in acute pulmonary embolism (PE), yet the clinical relevance and prognostic significance of pulmonary infarction remain unclear. The study aims to investigate the clinical features, radiographic characteristics, impact of reperfusion therapy and outcomes of patients with pulmonary infarction.

Design, Setting And Participants: A retrospective cohort study of 496 adult patients (≥18 years of age) diagnosed with PE who were evaluated by the PE response team at a tertiary academic referral centre in the USA.

Machine Learning Consensus Clustering Approach for Patients with Lactic Acidosis in Intensive Care Units.

Background: Lactic acidosis is a heterogeneous condition with multiple underlying causes and associated outcomes. The use of multi-dimensional patient data to subtype lactic acidosis can personalize patient care. Machine learning consensus clustering may identify lactic acidosis subgroups with unique clinical profiles and outcomes.