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Predicting the risk of bleeding during dual antiplatelet therapy after acute coronary syndromes
Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Cardiology in Linköping. Duke Clin Research Institute, NC USA.
Duke Clin Research Institute, NC USA.
Duke Clin Research Institute, NC USA.
Brigham and Womens Hospital, MA 02115 USA; Harvard Medical Sch, MA USA.
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2017 (English)In: Heart, ISSN 1355-6037, E-ISSN 1468-201X, Vol. 103, no 15, 1168-1176 p.Article in journal (Refereed) Published
Abstract [en]

Objectives Dual antiplatelet therapy (DAPT) with aspirin + a P2Y12 inhibitor is recommended for at least 12 months for patients with acute coronary syndrome (ACS), with shorter durations considered for patients with increased bleeding risk. However, there are no decision support tools available to predict an individual patients bleeding risk during DAPT treatment in the post-ACS setting. Methods To develop a longitudinal bleeding risk prediction model, we analysed 9240 patients with unstable angina/non-ST segment elevation myocardial infarction (NSTEMI) from the Targeted Platelet Inhibition to Clarify the Optimal Strategy to Medically Manage Acute Coronary Syndromes (TRILOGY ACS) trial, who were managed without revascularisation and treated with DAPT for a median of 14.8 months. Results We identified 10 significant baseline predictors of non-coronary artery bypass grafting (CABG)-related Global Use of Strategies to Open Occluded Arteries (GUSTO) severe/life-threatening/moderate bleeding: age, sex, weight, NSTEMI (vs unstable angina), angiography performed before randomisation, prior peptic ulcer disease, creatinine, systolic blood pressure, haemoglobin and treatment with beta-blocker. The five significant baseline predictors of Thrombolysis In Myocardial Infarction (TIMI) major or minor bleeding included age, sex, angiography performed before randomisation, creatinine and haemoglobin. The models showed good predictive accuracy with Therneaus C-indices: 0.78 (SE=0.024) for the GUSTO model and 0.67 (SE=0.023) for the TIMI model. Internal validation with bootstrapping gave similar C-indices of 0.77 and 0.65, respectively. External validation demonstrated an attenuated C-index for the GUSTO model (0.69) but not the TIMI model (0.68). Conclusions Longitudinal bleeding risks during treatment with DAPT in patients with ACS can be reliably predicted using selected baseline characteristics. The TRILOGY ACS bleeding models can inform riskbenefit considerations regarding the duration of DAPT following ACS.

Place, publisher, year, edition, pages
BMJ PUBLISHING GROUP , 2017. Vol. 103, no 15, 1168-1176 p.
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Cardiac and Cardiovascular Systems
Identifiers
URN: urn:nbn:se:liu:diva-139535DOI: 10.1136/heartjnl-2016-310090ISI: 000405486600008PubMedID: 28381584OAI: oai:DiVA.org:liu-139535DiVA: diva2:1130167
Note

Funding Agencies|Daiichi Sankyo; Eli Lilly and Company; Merck Co.

Available from: 2017-08-08 Created: 2017-08-08 Last updated: 2017-08-08

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Alfredsson, Joakim
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Division of Cardiovascular MedicineFaculty of Medicine and Health SciencesDepartment of Cardiology in Linköping
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