Literature DB >> 27432444

Validation of the 6-Month GRACE Score in Predicting 1-Year Mortality of Patients With Acute Coronary Syndrome Admitted to the Arabian Gulf Hospitals.

Lukman Thalib1, Luis Furuya-Kanamori2, Khalid F AlHabib3, Hussam F Alfaleh3, Mostafa Q AlShamiri3, Haitham Amin4, Jassim Al Suwaidi5, Kadhim Sulaiman6, Wael Almahmeed7, Alawi A Alsheikh-Ali8,9,10, Ahmed Al-Motarreb11, Suhail A R Doi2,12,13.   

Abstract

Acute coronary syndromes (ACS) are the most common cardiovascular diseases and are associated with a significant risk of mortality and morbidity. The Global Registry of Acute Coronary Events (GRACE) risk score postdischarge is a widely used ACS prediction model for risk of mortality (low, intermediate, and high); however, it has not yet been validated in patients from the Arabian Gulf. This prospective multicenter study (second Gulf Registry of Acute Coronary Events) provides detailed information of the GRACE risk score postdischarge in patients from the Arabian Gulf. Its prognostic utility was validated at 1-year follow-up in over 5000 patients with ACS from 65 hospitals in 6 Arabian Gulf countries (Bahrain, Saudi Arabia, Qatar, Oman, United Arab Emirates, and Yemen). Overall, the goodness of fit (Hosmer and Lemeshow statistic P value = .826), calibration, and discrimination (area under the receiver operating characteristic curve = 0.695; 95% confidence interval: 0.668-0.722) were good. The GRACE risk score postdischarge can be used to stratify 1 year mortality risk in the Arabian Gulf population; it does not require further calibration and has a good discriminatory ability.

Entities:  

Keywords:  GRACE risk score; acute coronary syndrome; mortality; postdischarge; validation

Mesh:

Year:  2016        PMID: 27432444     DOI: 10.1177/0003319716659179

Source DB:  PubMed          Journal:  Angiology        ISSN: 0003-3197            Impact factor:   3.619


  3 in total

1.  Risk stratification based on components of the complete blood count in patients with acute coronary syndrome: A classification and regression tree analysis.

Authors:  Xiaowei Niu; Guoyong Liu; Lichao Huo; Jingjing Zhang; Ming Bai; Yu Peng; Zheng Zhang
Journal:  Sci Rep       Date:  2018-02-12       Impact factor: 4.379

2.  Health informatics publication trends in Saudi Arabia: a bibliometric analysis over the last twenty-four years.

Authors:  Samar Binkheder; Raniah Aldekhyyel; Jwaher Almulhem
Journal:  J Med Libr Assoc       Date:  2021-04-01

3.  Short- and long-term mortality prediction after an acute ST-elevation myocardial infarction (STEMI) in Asians: A machine learning approach.

Authors:  Firdaus Aziz; Sorayya Malek; Khairul Shafiq Ibrahim; Raja Ezman Raja Shariff; Wan Azman Wan Ahmad; Rosli Mohd Ali; Kien Ting Liu; Gunavathy Selvaraj; Sazzli Kasim
Journal:  PLoS One       Date:  2021-08-02       Impact factor: 3.240

  3 in total

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