Risk score to predict serious bleeding in stable outpatients with or at risk of atherothrombosis

INSERM U-698 'Recherche Clinique en Athérothrombose', Department of Cardiology, Centre Hospitalier Universitaire Bichat-Claude Bernard, 46 rue Henri Huchard, Paris Cedex, France.
European Heart Journal (Impact Factor: 15.2). 02/2010; 31(10):1257-65. DOI: 10.1093/eurheartj/ehq021
Source: PubMed


To develop a risk score to quantify bleeding risk in outpatients with or at risk of atherothrombosis.
We studied patients in the REACH Registry, a cohort of 68 236 patients with/at risk of atherothrombosis. The outcome of interest was serious bleeding (non-fatal haemorrhagic stroke or bleeding leading to hospitalization and transfusion) over 2 years. Risk factors for bleeding were assessed using modified regression analysis. Multiple potential scoring systems based on the least complex models were constructed. Competing scores were compared on their discriminative ability via logistic regression. The score was validated externally using the CHARISMA population. From a final cohort of 56 616 patients, 804 (1.42%, 95% confidence interval 1.32-1.52) experienced serious bleeding between baseline and 2 years. A nine-item bleeding risk score (0-23 points) was constructed (age, peripheral arterial disease, congestive heart failure, diabetes, hypertension, smoking, antiplatelets, oral anticoagulants, hypercholesterolaemia). Observed incidence of bleeding at 2 years was: 0.46% (score < or = 6); 0.95% (7-8); 1.25% (9-10); 2.76% (> or = 11). The score's discriminative performance was consistent in CHARISMA and REACH (c-statistics 0.64 and 0.68, respectively); calibration in the CHARISMA population was very good (modified Hosmer-Lemeshow c(2) = 4.74; P = 0.69).
Bleeding risk increased substantially with a score >10. This score can assist clinicians in predicting the risk of serious bleeding and making decisions on antithrombotic therapy in outpatients.

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    • "At the time this study was designed, the AFib risk-specific HAS-BLED (Hypertension, Abnormal renal/liver function, Stroke, Bleeding history or predisposition, Labile international normalized ratio, Elderly [>65 years], Drugs/alcohol concomitantly) [20] and atherothrombotic risk-specific REACH (REduction of Atherothrombosis for Continued Health) [21] bleeding algorithms had not yet been published. Bleeding risk factors were identified from the Atrial Fibrillation Follow-up Investigation of Rhythm Management (AFFIRM) study [22] and from other studies [23, 24]. "
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