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The article focuses on stratifying patients with acute pulmonary embolism (PE) to determine those who are at low risk of adverse outcomes and can be safely treated outside the hospital. Lisa K. Moores, MD, emphasizes the shift from a generalized to an individualized approach in treating venous thromboembolism (VTE). While traditional guidelines are clear for high-risk patients, there is a need to further differentiate hemodynamically stable PE patients. Some may require intensive care due to factors like higher clot burden or right ventricular strain, whereas others could be managed as outpatients, potentially lowering costs and avoiding hospital-acquired conditions.<br /><br />Recent advancements in oral anticoagulants have made outpatient treatment more feasible. Research introduces various risk stratification tools and biomarkers to identify low-risk patients, such as cardiac biomarkers like highly sensitive cardiac troponin I (hs-cTnI), which has shown a high negative predictive value for adverse outcomes. Additionally, other indicators like right ventricular dysfunction on imaging, elevated serum troponin and BNP levels, serum sodium, and heart-type fatty acid binding protein levels contribute to risk assessment.<br /><br />Moores remarks on a study by Dr. Hakemi and colleagues that supports the use of hs-cTnI levels in conjunction with clinical scores and imaging studies to accurately identify low-risk PE patients. However, caution is advised as certain limitations exist, such as underrepresentation of patients with active malignancy. Despite these limitations, the study's findings hold promise for enhancing clinical practices and allowing safe outpatient management for a substantial subset of patients with acute PE. Future studies are encouraged to explore a combination of biomarkers to refine risk stratification further.
Keywords
acute pulmonary embolism
risk stratification
venous thromboembolism
outpatient treatment
oral anticoagulants
cardiac biomarkers
right ventricular dysfunction
hs-cTnI
clinical scores
biomarkers
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