Rong Bing1, Shaun G Goodman2, Andrew T Yan2, Keith Fox3, Chris P Gale4, Karice Hyun1, Mario D'Souza1, Pratap Shetty5, John Atherton6, Chris Hammett6, Derek Chew7, David Brieger1. 1. Department of Cardiology, Concord Hospital, 1A Hospital Road, Concord, Sydney, NSW, Australia. 2. Terrence Donnelly Heart Centre, St Michael's Hospital, University of Toronto, 30 Bond St, Toronto, Ontario, Canada. 3. Centre for Cardiovascular Science, University of Edinburgh, 47 Little France Crescent, Edinburgh, UK. 4. Medical Research Council Bioinformatics Centre, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Level 11 Worsley Building, Clarendon Way, Leeds, UK. 5. Wollongong Hospital, 252 Loftus Street, Wollongong, NSW, Australia. 6. Royal Brisbane Hospital, Bowen Bridge Road and Butterfield Street, Herston, QLD, Australia. 7. Flinders Medical Centre, Flinders University, Flinders Drive, Bedford Park, SA, Australia.
Abstract
Aims: There is little information on clinical risk stratification (CRS) compared to objective risk tools in patients with non-ST elevation acute coronary syndromes (NSTEACS). We quantified CRS use, its agreement with Global Registry of Acute Coronary Events (GRACE) risk scores (GRS), and association with outcomes. Methods and results: Data were extracted from the Australian Cooperative National Registry of Acute Coronary Care, Guideline Adherence and Clinical Events (CONCORDANCE), a multi-centre NSTEACS registry. From February 2009 to December 2015, 4512 patients from 41 sites were included. Predictors of CRS use and association with treatment were identified, CRS-GRS agreement determined and prediction of in-hospital and 6-month mortality compared. Clinical risk stratification was documented in 21% of patients. Family history of coronary disease was the only independent predictor of CRS use [odds ratio (OR) 1.23, 95% confidence interval (95% CI) 1.04-1.45]; electrocardiogram changes (OR 0.8, 95% CI 0.68-0.96), elevated biomarkers (OR 0.59, 95% CI 0.48-0.73), dementia (OR 0.56, 95% CI 0.36-0.84), and an urban hospital setting (OR 0.41, 95% CI 0.19-0.89) were independent negative predictors. A treatment-risk paradox was observed: high CRS risk patients received less anticoagulation (79% vs. 88%, P = 0.001) and angiography (83% vs. 71%, P < 0.001). CRS-GRS agreement was poor (kappa coefficient = 0.034) and CRS less predictive for in-hospital (c-statistic 0.54 vs. 0.87, P < 0.001) and 6-month (c-statistic 0.55 vs. 0.74, P < 0.01) mortality. Conclusion: In Australia, CRS does not guide treatment, correlate with GRS or predict outcomes. This study suggests the need for greater awareness and integration of validated tools such as the GRACE score to optimally direct treatment and potentially improve outcomes.
Aims: There is little information on clinical risk stratification (CRS) compared to objective risk tools in patients with non-ST elevation acute coronary syndromes (NSTEACS). We quantified CRS use, its agreement with Global Registry of Acute Coronary Events (GRACE) risk scores (GRS), and association with outcomes. Methods and results: Data were extracted from the Australian Cooperative National Registry of Acute Coronary Care, Guideline Adherence and Clinical Events (CONCORDANCE), a multi-centre NSTEACS registry. From February 2009 to December 2015, 4512 patients from 41 sites were included. Predictors of CRS use and association with treatment were identified, CRS-GRS agreement determined and prediction of in-hospital and 6-month mortality compared. Clinical risk stratification was documented in 21% of patients. Family history of coronary disease was the only independent predictor of CRS use [odds ratio (OR) 1.23, 95% confidence interval (95% CI) 1.04-1.45]; electrocardiogram changes (OR 0.8, 95% CI 0.68-0.96), elevated biomarkers (OR 0.59, 95% CI 0.48-0.73), dementia (OR 0.56, 95% CI 0.36-0.84), and an urban hospital setting (OR 0.41, 95% CI 0.19-0.89) were independent negative predictors. A treatment-risk paradox was observed: high CRS risk patients received less anticoagulation (79% vs. 88%, P = 0.001) and angiography (83% vs. 71%, P < 0.001). CRS-GRS agreement was poor (kappa coefficient = 0.034) and CRS less predictive for in-hospital (c-statistic 0.54 vs. 0.87, P < 0.001) and 6-month (c-statistic 0.55 vs. 0.74, P < 0.01) mortality. Conclusion: In Australia, CRS does not guide treatment, correlate with GRS or predict outcomes. This study suggests the need for greater awareness and integration of validated tools such as the GRACE score to optimally direct treatment and potentially improve outcomes.
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Authors: Colin C Everett; Keith Aa Fox; Catherine Reynolds; Catherine Fernandez; Linda Sharples; Deborah D Stocken; Kathryn Carruthers; Harry Hemingway; Andrew T Yan; Shaun G Goodman; David Brieger; Derek P Chew; Chris P Gale Journal: BMJ Open Date: 2019-09-05 Impact factor: 2.692