Literature DB >> 25501977

Risk stratification and prognostic value of GRACE and TIMI risk scores for female patients with non-ST segment elevation acute coronary syndrome.

H Zhu1, H Xue, H Wang, Y Chen, S Zhou, F Tian, S Hu, J Wang, J Yang, T Zhang.   

Abstract

AIM: The aim of this paper was to investigate the value of Global Registry of Acute Coronary Events (GRACE) and thrombolysis in myocardial infarction (TIMI) risk scores for risk stratification and prognosis in female patients with non-ST segment elevation acute coronary syndrome (NSTE-ACS).
METHODS: Non-elderly (<65 years) and elderly (≥65 years) female patients with NSTE-ACS (totally 869 cases) were enrolled in this study. The patients were further divided into low, intermediate and high-risk groups according to their GRACE and TIMI scores. Patients were followed up for 1 year to record the mortality and incidence of major adverse cardiac events (MACE). Differences in mortality and MACE incidence between the two scoring systems were compared by the area under the ROC curve.
RESULTS: The area under ROC curve (AUC) corresponding to the mortality and MACE incidence in any period by the GRACE scoring system was significantly larger than the TIMI scoring system in the elderly patients at 1 year of follow-up (AUC of mortality, 0.79 vs. 0.68; AUC of MACE, 0.78 vs. 0.72; P<0.05). Mortality and MACE incidence increased in parallel with the scores. Risk ratio values of Cox regression analysis based on GRACE and TIMI scores were greater than 1 (P<0.001).
CONCLUSION: Both GRACE and TIMI were adoptable in clinical risk stratification and prognosis of female patients with NSTE-ACS at different age groups. GRACE showed better accuracy than the TIMI scores.

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Year:  2014        PMID: 25501977

Source DB:  PubMed          Journal:  Minerva Cardioangiol        ISSN: 0026-4725            Impact factor:   1.347


  2 in total

1.  Physicians' perceptions of the Thrombolysis in Myocardial Infarction (TIMI) risk score in older adults with acute myocardial infarction.

Authors:  Shelli L Feder; Dena Schulman-Green; Mary Geda; Kathleen Williams; John A Dodson; Michael G Nanna; Heather G Allore; Terrence E Murphy; Mary E Tinetti; Thomas M Gill; Sarwat I Chaudhry
Journal:  Heart Lung       Date:  2015-07-09       Impact factor: 2.210

2.  Treatment of individual predictors with neural network algorithms improves Global Registry of Acute Coronary Events score discrimination.

Authors:  Raul A Borracci; Claudio C Higa; Graciana Ciambrone; Jimena Gambarte
Journal:  Arch Cardiol Mex       Date:  2021
  2 in total

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