Study Status: Recruiting
Recruit Status: Recruiting
Study Type: Observational
Official Title: Point of Care Testing of Platelet Function in Patients With Acute Upper Gastrointestinal Bleeding
Brief Summary: Acute upper gastrointestinal bleeding (AUGIB) is a common medical emergency. In an ageing population, antiplatelet drugs are increasingly being prescribed for treatment and prophylaxis against cardiovascular thrombo-embolic events. In many patients, platelet dysfunction mostly acquired is the principal cause of bleeding. To clinicians, the management of patients on antiplatelet drugs or anticoagulants is a challenge. One has to carefully balance the bleeding against thrombo-embolic risks. Therefore measuring platelet function should be integral in the management plan. A quantitative measurement allows titration of platelet function in accordance with bleeding or thromboembolic risk. Platelet function has not been studied in a large cohort of patients with acute upper gastrointestinal bleeding. As a first step, the study will determine if platelet dysfunction is associated with clinical outcome. In this prospective, observational single centre cohort study of consecutive patients with overt signs of acute upper gastrointestinal bleeding, their platelet function by point of care tests (light transmittance aggregometry, verify now p2y12,the platelet function analysis system (PFA-100) upon their admissions. Patients will be followed up for 30 days after trial enrollment. The primary endpoint is defined as significant bleeding that requires interventions (endoscopic, radiologic or surgery). Secondary end points include cardio- and cerebrovascular thrombo-embolic events and all cause deaths. A receiver operating characteristic (ROC) curve analysis is calculated for each point-of-care test to evaluate if individual test can distinguish between patients with and without primary end point. This study aims to evaluate the capability of platelet function tests to predict clinical outcome in patients with AUGIB. Logistic regression models will then be built in search for independent correlates to the primary and secondary endpoints and to adjust for confounding variables.