Results 181 to 190 of about 1,329,751 (405)
Introduction: Pulmonary embolism results from thrombus migration into the pulmonary artery, with the most common cause being deep vein thrombosis. However, pulmonary embolism might not necessarily originate in the lower extremities, which necessitates ...
Antonio Nenna+6 more
doaj +1 more source
When pulmonary embolism is not an obvious diagnosis - pathophysiology, risk factors, diagnosis, treatment and a review of the most unusual cases [PDF]
Introduction: This review paper aims to emphasize how pulmonary embolism is a seriously life-threatening disease entity, point out risk factors, symptoms, diagnostic trails, treatment and prove that a diagnosis, specifically aimed at embolism is often ...
Długozima, Patrycja+9 more
core +1 more source
Acute Pulmonary Embolism [PDF]
Anish Bhatt, Emil P Sfedu, Casey Fauth
openaire +10 more sources
Abstract Aims Although predominant in routine practice, non‐ischaemic cardiogenic shock (NICS) remains underrepresented in past studies, mainly focused on ischaemic cardiogenic shock (CS). This study aims to describe the current NICS picture and define its independent correlates of short‐ and long‐term outcomes.
Miloud Cherbi+20 more
wiley +1 more source
Purpose. To document the incidence of proximal deep vein thrombosis and pulmonary embolism in 58 consecutive Japanese patients undergoing total hip arthroplasty or total knee arthroplasty. Methods.
A Sudo+5 more
doaj +1 more source
Label up: Learning Pulmonary Embolism Segmentation from Image Level Annotation through Model Explainability [PDF]
Pulmonary Embolisms (PE) are a leading cause of cardiovascular death. Computed tomographic pulmonary angiography (CTPA) stands as the gold standard for diagnosing pulmonary embolisms (PE) and there has been a lot of interest in developing AI-based models for assisting in PE diagnosis. Performance of these algorithms has been hindered by the scarcity of
arxiv
Socio‐economic status and the effect of guideline‐directed medical therapy in the STRONG‐HF study
Abstract Aims Acute heart failure (AHF) impacts millions globally, with outcomes varying based on socio‐economic status (SES). Methods SES measured by annual household income, years of education and medical insurance coverage. Each patient's income and education level relative to the median or mean, respectively, in the country was calculated, and ...
Albertino Damasceno+29 more
wiley +1 more source