Publications by authors named "H Helfer"

Purpose Of Review: The life expectancy of patients suffering from thrombosis associated with cancer has improved significantly, making them a chronic disease. Patients with thrombosis and cancer are fragile. Treated with anticoagulants, they remain at risk of complications.

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Background: Venous thromboembolism (VTE), including pulmonary embolism (PE) and deep vein thrombosis (DVT), is a potentially fatal disease with a multifactorial nature, impacting different medical and surgical specialties. Recently, new guidelines and direct oral anticoagulants facilitated early discharge for most DVT patients and non-severe PE patients.

Objective: The aim of this study is to illustrate the distribution of VTE patients throughout the hospital and map their care pathway from Emergency Department (ED) to hospital discharge.

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Article Synopsis
  • A study evaluated the eligibility of patients with cancer-associated thrombosis (CAT) for randomized clinical trials assessing direct oral anticoagulants (DOACs) against low molecular weight heparin.
  • Out of 302 patients analyzed, nearly 46% for the HOKUSAI-VTE trial and 53% for the CARAVAGGIO trial had non-inclusion criteria, such as unusual site thrombosis and severe health conditions.
  • The 6-month follow-up showed no significant difference in event-free survival between those eligible and ineligible for the trials, highlighting the need for more research on DOACs' safety and effectiveness for ineligible CAT patients.
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Introduction: Anticoagulant is the cornerstone of the management of VTE at the cost of a non-negligible risk of bleeding. Reliable and validated clinical tools to predict thromboembolic and hemorrhagic events are crucial for individualized decision-making for the type and duration of anticoagulant treatment. We evaluate the available risk models in real life cancer patients with VTE.

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Venous thromboembolic disease (VTE) is a common complication in cancer patients. The currently recommended VTE diagnostic approach involves a step-by-step algorithm, which is based on the assessment of clinical probability, D-dimer measurement, and/or diagnostic imaging. While this diagnostic strategy is well validated and efficient in the noncancer population, its use in cancer patients is less satisfactory.

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