BACKGROUND: Management decisions for thromboprophylaxis in atrial fibrillation need to balance the risk of stroke against serious hemorrhage. The objective of the present analysis is to compare the Hypertension, Abnormal renal/liver function, Stroke, Bleeding history or predisposition, Labile international normalized ratio, Elderly (>65 years), Drugs/alcohol concomitantly (HAS-BLED) score against other older bleeding risk scores and the new Anticoagulation and Risk Factors in Atrial Fibrillation score in an atrial fibrillation cohort. METHODS AND RESULTS: Patients diagnosed with nonvalvular atrial fibrillation in a 4-hospital institution between 2000 and 2010 were identified. Independent risk factors of bleeding were investigated using Cox regression. The predictive value of several bleeding risk schema was assessed using the c-statistic and net reclassification improvement. Oral anticoagulation use was highest in moderate-risk patients (59.8%) but only slightly more than high-risk (50.1%) and low-risk (46.4%) patients. Those at higher bleeding risk (HAS-BLED ≥ 3) were also at highest risk of stroke/thromboembolism or stroke/thromboembolism/death, as well as bleeding and all-cause mortality. On multivariable analysis, independent predictors of bleeding were age ≥ 75 years and age ≥ 65 years, alcohol excess, anemia, and heart failure. All risk scores had only modest predictive ability for bleeding, whether on vitamin K antagonist or not (c-statistic ≈0.6). When the HAS-BLED score was compared with other bleeding risk scores, the net reclassification improvement was significantly improved against all other scores tested. CONCLUSIONS: Current oral anticoagulation prescribing patterns would suggest that bleeding risk estimation by clinicians is poor and that oral anticoagulation prescribing does not reflect bleeding risk per se. The HAS-BLED score performs well in relation to predicting bleeding events compared with older bleeding scores and the Anticoagulation and Risk Factors in Atrial Fibrillation score, with significantly improved reclassification using HAS-BLED compared with all other bleeding risk scores tested.
BACKGROUND: Management decisions for thromboprophylaxis in atrial fibrillation need to balance the risk of stroke against serious hemorrhage. The objective of the present analysis is to compare the Hypertension, Abnormal renal/liver function, Stroke, Bleeding history or predisposition, Labile international normalized ratio, Elderly (>65 years), Drugs/alcohol concomitantly (HAS-BLED) score against other older bleeding risk scores and the new Anticoagulation and Risk Factors in Atrial Fibrillation score in an atrial fibrillation cohort. METHODS AND RESULTS:Patients diagnosed with nonvalvular atrial fibrillation in a 4-hospital institution between 2000 and 2010 were identified. Independent risk factors of bleeding were investigated using Cox regression. The predictive value of several bleeding risk schema was assessed using the c-statistic and net reclassification improvement. Oral anticoagulation use was highest in moderate-risk patients (59.8%) but only slightly more than high-risk (50.1%) and low-risk (46.4%) patients. Those at higher bleeding risk (HAS-BLED ≥ 3) were also at highest risk of stroke/thromboembolism or stroke/thromboembolism/death, as well as bleeding and all-cause mortality. On multivariable analysis, independent predictors of bleeding were age ≥ 75 years and age ≥ 65 years, alcohol excess, anemia, and heart failure. All risk scores had only modest predictive ability for bleeding, whether on vitamin K antagonist or not (c-statistic ≈0.6). When the HAS-BLED score was compared with other bleeding risk scores, the net reclassification improvement was significantly improved against all other scores tested. CONCLUSIONS: Current oral anticoagulation prescribing patterns would suggest that bleeding risk estimation by clinicians is poor and that oral anticoagulation prescribing does not reflect bleeding risk per se. The HAS-BLED score performs well in relation to predicting bleeding events compared with older bleeding scores and the Anticoagulation and Risk Factors in Atrial Fibrillation score, with significantly improved reclassification using HAS-BLED compared with all other bleeding risk scores tested.
Authors: Benjamin A Steinberg; Melissa A Greiner; Bradley G Hammill; Lesley H Curtis; Emelia J Benjamin; Susan R Heckbert; Jonathan P Piccini Journal: Cardiovasc Ther Date: 2015-08 Impact factor: 3.023
Authors: Joshua A Roth; Katharine Bradley; Kenneth E Thummel; David L Veenstra; Denise Boudreau Journal: Pharmacoepidemiol Drug Saf Date: 2015-04-08 Impact factor: 2.890
Authors: Nina A Hilkens; Ale Algra; Hans-Christoph Diener; Johannes B Reitsma; Philip M Bath; Laszlo Csiba; Werner Hacke; L Jaap Kappelle; Peter J Koudstaal; Didier Leys; Jean-Louis Mas; Ralph L Sacco; Pierre Amarenco; Leila Sissani; Jacoba P Greving Journal: Neurology Date: 2017-08-02 Impact factor: 9.910
Authors: Ethan D Borre; Adam Goode; Giselle Raitz; Bimal Shah; Angela Lowenstern; Ranee Chatterjee; Lauren Sharan; Nancy M Allen LaPointe; Roshini Yapa; J Kelly Davis; Kathryn Lallinger; Robyn Schmidt; Andrzej Kosinski; Sana M Al-Khatib; Gillian D Sanders Journal: Thromb Haemost Date: 2018-10-30 Impact factor: 6.681