Why the study?
Do prognostic modalities for bleeding reliably identify high-risk patients among those with coronary artery disease on dual antiplatelet therapy?
Do prognostic modalities for bleeding reliably identify high-risk patients among those with coronary artery disease on dual antiplatelet therapy?
Low on-treatment platelet reactivity, the CYP2C19*17 allele, and specific clinical characteristics (older age, female sex, renal failure) are independent predictors of bleeding in CAD patients on DAPT, which can be combined into a risk stratification algorithm.
Bleeding prevention merits equal priority in post-PCI DAPT decisions; leaves open optimal strategies for prospective validation.
Patients with coronary artery disease are usually treated with dual antiplatelet therapy (DAPT) after percutaneous coronary intervention. Patients on DAPT are at risk of both ischaemic and bleeding events. Although side-lined for a long time, real-life studies have shown that both the incidence and the associated morbidity and mortality of out-of-hospital bleeding are high. This indicates that prevention of (post-interventional) bleeding is as important as prevention of ischaemia. For this purpose it is crucial to reliably identify patients with a high bleeding risk. In order to postulate an algorithm, which could help identifying these patients, we performed a systematic review to determine the value of previously proposed prognostic modalities for bleeding. We searched and appraised the following tools: platelet function tests, genetic tests, bleeding scores and questionnaires and haemostatic tests. Most studies indicated that low on-treatment platelet reactivity (LTPR), as measured by several platelet function tests, and the carriage of CYP2C19*17 allele were independent risk factors for bleeding. A bleeding score also proved to be helpful in identifying patients at risk. No studies on haemostatic tests were retrieved. Several patient characteristics were also identified as independent predictors of bleeding, such as older age, female sex and renal failure. Combining these risk factors we propose an algorithm that would hypothetically facilitate identification of those patients at highest risk, warranting prevention measures for bleeding. This could be a starting point for further research concerning the topic.
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Meijden et al. (2015) studied this question.
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