11
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Predictive values of D-dimer assay, GRACE scores and TIMI scores for adverse outcome in patients with non-ST-segment elevation myocardial infarction

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Purpose

          To determine the predictive values of D-dimer assay, Global Registry of Acute Coronary Events (GRACE) and Thrombolysis in Myocardial Infarction (TIMI) risk scores for adverse outcome in patients with non-ST-segment elevation myocardial infarction (NSTEMI).

          Patients and methods

          A total of 234 patients (mean age: 57.2±11.7 years, 75.2% were males) hospitalized with NSTEMI were included. Data on D-dimer assay, GRACE and TIMI risk scores were recorded. Logistic regression analysis was conducted to determine the risk factors predicting increased mortality.

          Results

          Median D-dimer levels were 349.5 (48.0–7,210.0) ng/mL, the average TIMI score was 3.2±1.2 and the GRACE score was 90.4±27.6 with high GRACE scores (>118) in 17.5% of patients. The GRACE score was correlated positively with both the D-dimer assay ( r=0.215, P=0.01) and TIMI scores ( r=0.504, P=0.000). Multivariate logistic regression analysis revealed that higher creatinine levels (odds ratio =18.465, 95% confidence interval: 1.059–322.084, P=0.046) constituted the only significant predictor of increased mortality risk with no predictive values for age, D-dimer assay, ejection fraction, glucose, hemoglobin A1c, sodium, albumin or total cholesterol levels for mortality.

          Conclusion

          Serum creatinine levels constituted the sole independent determinant of mortality risk, with no significant values for D-dimer assay, GRACE or TIMI scores for predicting the risk of mortality in NSTEMI patients.

          Related collections

          Most cited references 26

          • Record: found
          • Abstract: found
          • Article: not found

          Predictors of hospital mortality in the global registry of acute coronary events.

          Management of acute coronary syndromes (ACS) should be guided by an estimate of patient risk. To develop a simple model to assess the risk for in-hospital mortality for the entire spectrum of ACS treated in general clinical practice. A multivariable logistic regression model was developed using 11 389 patients (including 509 in-hospital deaths) with ACS with and without ST-segment elevation enrolled in the Global Registry of Acute Coronary Events (GRACE) from April 1, 1999, through March 31, 2001. Validation data sets included a subsequent cohort of 3972 patients enrolled in GRACE and 12 142 in the Global Use of Strategies to Open Occluded Coronary Arteries IIb (GUSTO-IIb) trial. The following 8 independent risk factors accounted for 89.9% of the prognostic information: age (odds ratio [OR], 1.7 per 10 years), Killip class (OR, 2.0 per class), systolic blood pressure (OR, 1.4 per 20-mm Hg decrease), ST-segment deviation (OR, 2.4), cardiac arrest during presentation (OR, 4.3), serum creatinine level (OR, 1.2 per 1-mg/dL [88.4- micro mol/L] increase), positive initial cardiac enzyme findings (OR, 1.6), and heart rate (OR, 1.3 per 30-beat/min increase). The discrimination ability of the simplified model was excellent with c statistics of 0.83 in the derived database, 0.84 in the confirmation GRACE data set, and 0.79 in the GUSTO-IIb database. Across the entire spectrum of ACS and in general clinical practice, this model provides excellent ability to assess the risk for death and can be used as a simple nomogram to estimate risk in individual patients.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Relation between renal dysfunction and cardiovascular outcomes after myocardial infarction.

            The presence of coexisting conditions has a substantial effect on the outcome of acute myocardial infarction. Renal failure is associated with one of the highest risks, but the influence of milder degrees of renal impairment is less well defined. As part of the Valsartan in Acute Myocardial Infarction Trial (VALIANT), we identified 14,527 patients with acute myocardial infarction complicated by clinical or radiologic signs of heart failure, left ventricular dysfunction, or both, and a documented serum creatinine measurement. Patients were randomly assigned to receive captopril, valsartan, or both. The glomerular filtration rate (GFR) was estimated by means of the four-component Modification of Diet in Renal Disease equation, and the patients were grouped according to their estimated GFR. We used a 70-candidate variable model to adjust and compare overall mortality and composite cardiovascular events among four GFR groups. The distribution of estimated GFR was wide and normally shaped, with a mean (+/-SD) value of 70+/-21 ml per minute per 1.73 m2 of body-surface area. The prevalence of coexisting risk factors, prior cardiovascular disease, and a Killip class of more than I was greatest among patients with a reduced estimated GFR (less than 45.0 ml per minute per 1.73 m2), and the use of aspirin, beta-blockers, statins, or coronary-revascularization procedures was lowest in this group. The risk of death or the composite end point of death from cardiovascular causes, reinfarction, congestive heart failure, stroke, or resuscitation after cardiac arrest increased with declining estimated GFRs. Although the rate of renal events increased with declining estimated GFRs, the adverse outcomes were predominantly cardiovascular. Below 81.0 ml per minute per 1.73 m2, each reduction of the estimated GFR by 10 units was associated with a hazard ratio for death and nonfatal cardiovascular outcomes of 1.10 (95 percent confidence interval, 1.08 to 1.12), which was independent of the treatment assignment. Even mild renal disease, as assessed by the estimated GFR, should be considered a major risk factor for cardiovascular complications after a myocardial infarction. Copyright 2004 Massachusetts Medical Society
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              A validated prediction model for all forms of acute coronary syndrome: estimating the risk of 6-month postdischarge death in an international registry.

              Accurate estimation of risk for untoward outcomes after patients have been hospitalized for an acute coronary syndrome (ACS) may help clinicians guide the type and intensity of therapy. To develop a simple decision tool for bedside risk estimation of 6-month mortality in patients surviving admission for an ACS. A multinational registry, involving 94 hospitals in 14 countries, that used data from the Global Registry of Acute Coronary Events (GRACE) to develop and validate a multivariable stepwise regression model for death during 6 months postdischarge. From 17,142 patients presenting with an ACS from April 1, 1999, to March 31, 2002, and discharged alive, 15,007 (87.5%) had complete 6-month follow-up and represented the development cohort for a model that was subsequently tested on a validation cohort of 7638 patients admitted from April 1, 2002, to December 31, 2003. All-cause mortality during 6 months postdischarge after admission for an ACS. The 6-month mortality rates were similar in the development (n = 717; 4.8%) and validation cohorts (n = 331; 4.7%). The risk-prediction tool for all forms of ACS identified 9 variables predictive of 6-month mortality: older age, history of myocardial infarction, history of heart failure, increased pulse rate at presentation, lower systolic blood pressure at presentation, elevated initial serum creatinine level, elevated initial serum cardiac biomarker levels, ST-segment depression on presenting electrocardiogram, and not having a percutaneous coronary intervention performed in hospital. The c statistics for the development and validation cohorts were 0.81 and 0.75, respectively. The GRACE 6-month postdischarge prediction model is a simple, robust tool for predicting mortality in patients with ACS. Clinicians may find it simple to use and applicable to clinical practice.
                Bookmark

                Author and article information

                Journal
                Ther Clin Risk Manag
                Ther Clin Risk Manag
                Therapeutics and Clinical Risk Management
                Therapeutics and Clinical Risk Management
                Dove Medical Press
                1176-6336
                1178-203X
                2017
                29 March 2017
                : 13
                : 393-400
                Affiliations
                [1 ]Department of Cardiology
                [2 ]Department of Biochemistry, Mehmet Akif Ersoy Thoracic and Cardiovascular Surgery Training and Research Hospital, Istanbul
                [3 ]Department of Cardiology, Duzce University Faculty of Medicine, Duzce
                [4 ]Department of Infectious Diseases
                [5 ]Department of Thoracic and Cardiovascular Surgery, Mehmet Akif Ersoy Thoracic and Cardiovascular Surgery Training and Research Hospital, Istanbul, Turkey
                Author notes
                Correspondence: Muhammet Hulusi Satilmisoglu, Department of Cardiology, Mehmet Akif Ersoy Thoracic and Cardiovascular Surgery Training and Research Hospital, Turgut Ozal Bulvari No 11, Kucukcekmece, Istanbul 34303, Turkey, Tel +90 53 2598 2318, Email hulusim@ 123456gmail.com
                Article
                tcrm-13-393
                10.2147/TCRM.S124794
                5384739
                © 2017 Satilmisoglu et al. This work is published and licensed by Dove Medical Press Limited

                The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.

                Categories
                Original Research

                Comments

                Comment on this article