Literature DB >> 22608950

Risk-prediction model for ischemic stroke in patients hospitalized with an acute coronary syndrome (from the global registry of acute coronary events [GRACE]).

Kay Lee Park1, Andrzej Budaj, Robert J Goldberg, Frederick A Anderson, Giancarlo Agnelli, Brian M Kennelly, Enrique P Gurfinkel, Gordon Fitzgerald, Joel M Gore.   

Abstract

The risk of stroke in patients hospitalized with an acute coronary syndrome (ACS) ranges from <1% to ≥ 2.5%. The aim of this study was to develop a simple predictive tool for bedside risk estimation of in-hospital ischemic stroke in patients with ACS to help guide clinicians in the acute management of these high-risk patients. Data were obtained from 63,118 patients enrolled from April 1999 to December 2007 in the Global Registry of Acute Coronary Events (GRACE), a multinational registry involving 126 hospitals in 14 countries. A regression model was developed to predict the occurrence of in-hospital ischemic stroke in patients hospitalized with an ACS. The main study outcome was the development of ischemic stroke during the index hospitalization for an ACS. Eight risk factors for stroke were identified: older age, atrial fibrillation on index electrocardiogram, positive initial cardiac biomarkers, presenting systolic blood pressure ≥ 160 mm Hg, ST-segment change on index electrocardiogram, no history of smoking, higher Killip class, and lower body weight (c-statistic 0.7). The addition of coronary artery bypass graft surgery and percutaneous coronary intervention into the model increased the prediction of stroke risk. In conclusion, the GRACE stroke risk score is a simple tool for predicting in-hospital ischemic stroke risk in patients admitted for the entire spectrum of ACS, which is widely applicable to patients in various hospital settings and will assist in the management of high-risk patients with ACS.
Copyright © 2012 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22608950     DOI: 10.1016/j.amjcard.2012.04.040

Source DB:  PubMed          Journal:  Am J Cardiol        ISSN: 0002-9149            Impact factor:   2.778


  6 in total

1.  Presence and extent of coronary calcified plaque evaluated by coronary computed tomographic angiography are independent predictors of ischemic stroke in patients with suspected coronary artery disease.

Authors:  Heesun Lee; Yeonyee E Yoon; Yong-Jin Kim; Hack-Lyoung Kim; Seung-Pyo Lee; Hyung-Kwan Kim; Goo-Yeong Cho; Joo-Hee Zo; Dae-Won Sohn
Journal:  Int J Cardiovasc Imaging       Date:  2015-07-16       Impact factor: 2.357

2.  Risk stratification and prognostic value of grace and timi risk scores for female patients with non-st segment elevation acute coronary syndrome.

Authors:  Hang Zhu; Hao Xue; Haotian Wang; Yundai Chen; Shanshan Zhou; Feng Tian; Shunying Hu; Jing Wang; Junjie Yang; Tao Zhang
Journal:  Int J Clin Exp Med       Date:  2015-03-15

3.  Prognosis of primary percutaneous coronary intervention in elderly patients with ST-elevation myocardial infarction.

Authors:  Abdullah Alkhushail; Sanjay Kohli; Andrew Mitchel; Robert Smith; Charles Ilsely
Journal:  J Saudi Heart Assoc       Date:  2014-12-18

4.  Is 6-month GRACE risk score a useful tool to predict stroke after an acute coronary syndrome?

Authors:  Belén Álvarez-Álvarez; Sergio Raposeiras-Roubín; Emad Abu-Assi; Cristina Cambeiro-González; Santiago Gestal-Romaní; Andrea López-López; Noelia Bouzas-Cruz; María Castiñeira-Busto; Ozoda Saidhodjayeva; Alfredo Redondo-Diéguez; Eva Pereira López; José María García-Acuña; José Ramón González-Juanatey
Journal:  Open Heart       Date:  2014-12-22

5.  Risk evaluation of new-onset atrial fibrillation complicating ST-segment elevation myocardial infarction: a comparison between GRACE and CHA2DS2-VASc scores.

Authors:  Jiachen Luo; Liming Dai; Jianming Li; Jinlong Zhao; Zhiqiang Li; Xiaoming Qin; Hongqiang Li; Baoxin Liu; Yidong Wei
Journal:  Clin Interv Aging       Date:  2018-06-06       Impact factor: 4.458

Review 6.  Untapped potential of multicenter studies: a review of cardiovascular risk prediction models revealed inappropriate analyses and wide variation in reporting.

Authors:  L Wynants; D M Kent; D Timmerman; C M Lundquist; B Van Calster
Journal:  Diagn Progn Res       Date:  2019-02-22
  6 in total

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