Christopher B Van Hise1, Jaimi H Greenslade2, William Parsonage3, Martin Than4, Joanna Young5, Louise Cullen6. 1. Faculty of Medicine, The University of Queensland, Brisbane, Australia; Department of Emergency Medicine, Royal Brisbane and Women's Hospital, Brisbane, Australia. Electronic address: christopher.vanhise@uqconnect.edu.au. 2. Faculty of Medicine, The University of Queensland, Brisbane, Australia; Department of Emergency Medicine, Royal Brisbane and Women's Hospital, Brisbane, Australia. Electronic address: jaimi.greenslade@health.qld.gov.au. 3. Faculty of Medicine, The University of Queensland, Brisbane, Australia; Faculty of Health, Queensland University of Technology, Australia; Department of Cardiology, Royal Brisbane and Women's Hospital, Brisbane, Australia. Electronic address: William.parsonage@health.qld.gov.au. 4. Emergency Department, Christchurch Hospital, Christchurch, New Zealand. Electronic address: martin@thanstedman.onmicrosoft.com. 5. Emergency Department, Christchurch Hospital, Christchurch, New Zealand. Electronic address: joanna.young@cdhb.health.nz. 6. Faculty of Medicine, The University of Queensland, Brisbane, Australia; Department of Emergency Medicine, Royal Brisbane and Women's Hospital, Brisbane, Australia; Faculty of Health, Queensland University of Technology, Australia. Electronic address: louise.cullen@health.qld.gov.au.
Abstract
OBJECTIVE: To externally validate a clinical decision rule incorporating heart fatty acid binding protein (h-FABP), high-sensitivity troponin (hs-cTn) and electrocardiogram (ECG) for the detection of acute myocardial infarction (AMI) on presentation to the Emergency Department. We also investigated whether this clinical decision rule improved identification of AMI over algorithms incorporating hs-cTn and ECG only. DESIGN AND METHODS: This study included data from 789 patients from the Brisbane ADAPT cohort and 441 patients from the Christchurch TIMI RCT cohort. The primary outcome was index AMI. Sensitivity, specificity, positive predictive value and negative predictive value were used to assess the diagnostic accuracy of the algorithms. RESULTS: 1230 patients were recruited, including 112 (9.1%) with AMI. The algorithm including h-FABP and hs-cTnT had 100% sensitivity and 32.4% specificity. The algorithm utilising h-FABP and hs-cTnI had similar sensitivity (99.1%) and higher specificity (43.4%). The hs-cTnI and hs-cTnT algorithms without h-FABP both had a sensitivity of 98.2%; a result that was not significantly different from either algorithm incorporating h-FABP. Specificity was higher for the hs-cTnI algorithm (68.1%) compared to the hs-cTnT algorithm (33.0%). The specificity of the algorithm incorporating hs-cTnI alone was also significantly higher than both of the algorithms incorporating h-FABP (p<0.01). CONCLUSION: For patients presenting to the Emergency Department with chest pain, an algorithm incorporating h-FABP, hs-cTn and ECG has high accuracy and can rule out up to 40% of patients. An algorithm incorporating only hs-cTn and ECG has similar sensitivity and may rule out a higher proportion of patients. Each of the algorithms can be used to safely identify patients as low risk for AMI on presentation to the Emergency Department.
OBJECTIVE: To externally validate a clinical decision rule incorporating heart fatty acid binding protein (h-FABP), high-sensitivity troponin (hs-cTn) and electrocardiogram (ECG) for the detection of acute myocardial infarction (AMI) on presentation to the Emergency Department. We also investigated whether this clinical decision rule improved identification of AMI over algorithms incorporating hs-cTn and ECG only. DESIGN AND METHODS: This study included data from 789 patients from the Brisbane ADAPT cohort and 441 patients from the Christchurch TIMI RCT cohort. The primary outcome was index AMI. Sensitivity, specificity, positive predictive value and negative predictive value were used to assess the diagnostic accuracy of the algorithms. RESULTS: 1230 patients were recruited, including 112 (9.1%) with AMI. The algorithm including h-FABP and hs-cTnT had 100% sensitivity and 32.4% specificity. The algorithm utilising h-FABP and hs-cTnI had similar sensitivity (99.1%) and higher specificity (43.4%). The hs-cTnI and hs-cTnT algorithms without h-FABP both had a sensitivity of 98.2%; a result that was not significantly different from either algorithm incorporating h-FABP. Specificity was higher for the hs-cTnI algorithm (68.1%) compared to the hs-cTnT algorithm (33.0%). The specificity of the algorithm incorporating hs-cTnI alone was also significantly higher than both of the algorithms incorporating h-FABP (p<0.01). CONCLUSION: For patients presenting to the Emergency Department with chest pain, an algorithm incorporating h-FABP, hs-cTn and ECG has high accuracy and can rule out up to 40% of patients. An algorithm incorporating only hs-cTn and ECG has similar sensitivity and may rule out a higher proportion of patients. Each of the algorithms can be used to safely identify patients as low risk for AMI on presentation to the Emergency Department.
Authors: Harsh Goel; Joshua Melot; Matthew D Krinock; Ashish Kumar; Sunil K Nadar; Gregory Y H Lip Journal: Ann Med Date: 2020-08-04 Impact factor: 4.709
Authors: S S Anroedh; I Kardys; K M Akkerhuis; M Biekart; B van der Hulst; G J Deddens; P Smits; M Gardien; E Dubois; F Zijlstra; E Boersma Journal: Neth Heart J Date: 2018-11 Impact factor: 2.380