Colleen Shortt1, Jinhui Ma2, Natasha Clayton3, Jonathan Sherbino4, Richard Whitlock5, Guillaume Pare1, Stephen A Hill1, Matthew McQueen1, Shamir R Mehta6, P J Devereaux6, Andrew Worster4, Peter A Kavsak7. 1. Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada. 2. School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, ON, Canada; and the Children's Hospital of Eastern Ontario Research Institute, ON, Canada. 3. Department of Medicine, McMaster University, Hamilton, ON, Canada. 4. Division of Emergency Medicine, McMaster University, Hamilton, ON, Canada. 5. Division of Cardiac Surgery, and Population Health Research Institute, McMaster University, Hamilton, ON, Canada. 6. Division of Cardiology, and Population Health Research Institute, McMaster University, Hamilton, ON, Canada. 7. Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada; kavsakp@mcmaster.ca.
Abstract
BACKGROUND: Early rule-in/rule-out of myocardial infarction (MI) in patients presenting to the emergency department (ED) is important for patient care and resource allocation. Given that dysglycemia is a strong risk factor for MI, we sought to explore and compare different combinations of cardiac troponin (cTn) cutoffs with glycemic markers for the early rule-in/rule-out of MI. METHODS: We included ED patients (n = 1137) with symptoms suggestive of acute coronary syndrome (ACS) who had cTnI, high-sensitivity cTnI (hs-cTnI), hs-cTnT, glucose, and hemoglobin A1c (Hb A1c) measurements. We derived rule-in/rule-out algorithms using different combinations of ROC-derived and literature cutoffs for rule-in and rule-out of MI within 7 days after presentation. These algorithms were then tested for MI/cardiovascular death and ACS/cardiovascular death at 7 days. ROC curves, sensitivity, specificity, likelihood ratios, positive and negative predictive values (PPV and NPV), and CIs were determined for various biomarker combinations. RESULTS: MI was diagnosed in 133 patients (11.7%; 95% CI, 9.8-13.8). The algorithms that included cTn and glucose produced the greatest number of patients ruled out/ruled in for MI and yielded sensitivity ≥99%, NPV ≥99.5%, specificity ≥99%, and PPV ≥80%. This diagnostic performance was maintained for MI/cardiovascular death but not for ACS/cardiovascular death. The addition of hemoglobin A1c (Hb A1c) (≥6.5%) to these algorithms did not change these estimates; however, 50 patients with previously unknown diabetes may have been identified if Hb A1c was measured. CONCLUSIONS: Algorithms incorporating glucose with cTn may lead to an earlier MI diagnosis and rule-out for MI/cardiovascular death. Addition of Hb A1c into these algorithms allows for identification of diabetes. Future studies extending these findings are needed for ACS/cardiovascular death. ClinicalTrials.gov identifier: NCT01994577.
BACKGROUND: Early rule-in/rule-out of myocardial infarction (MI) in patients presenting to the emergency department (ED) is important for patient care and resource allocation. Given that dysglycemia is a strong risk factor for MI, we sought to explore and compare different combinations of cardiac troponin (cTn) cutoffs with glycemic markers for the early rule-in/rule-out of MI. METHODS: We included ED patients (n = 1137) with symptoms suggestive of acute coronary syndrome (ACS) who had cTnI, high-sensitivity cTnI (hs-cTnI), hs-cTnT, glucose, and hemoglobin A1c (Hb A1c) measurements. We derived rule-in/rule-out algorithms using different combinations of ROC-derived and literature cutoffs for rule-in and rule-out of MI within 7 days after presentation. These algorithms were then tested for MI/cardiovascular death and ACS/cardiovascular death at 7 days. ROC curves, sensitivity, specificity, likelihood ratios, positive and negative predictive values (PPV and NPV), and CIs were determined for various biomarker combinations. RESULTS: MI was diagnosed in 133 patients (11.7%; 95% CI, 9.8-13.8). The algorithms that included cTn and glucose produced the greatest number of patients ruled out/ruled in for MI and yielded sensitivity ≥99%, NPV ≥99.5%, specificity ≥99%, and PPV ≥80%. This diagnostic performance was maintained for MI/cardiovascular death but not for ACS/cardiovascular death. The addition of hemoglobin A1c (Hb A1c) (≥6.5%) to these algorithms did not change these estimates; however, 50 patients with previously unknown diabetes may have been identified if Hb A1c was measured. CONCLUSIONS: Algorithms incorporating glucose with cTn may lead to an earlier MI diagnosis and rule-out for MI/cardiovascular death. Addition of Hb A1c into these algorithms allows for identification of diabetes. Future studies extending these findings are needed for ACS/cardiovascular death. ClinicalTrials.gov identifier: NCT01994577.
Authors: Peter A Kavsak; Joshua O Cerasuolo; Dennis T Ko; Jinhui Ma; Jonathan Sherbino; Shawn E Mondoux; Natasha Clayton; Stephen A Hill; Matthew McQueen; Lauren E Griffith; Shamir R Mehta; Richard Perez; Hsien Seow; P J Devereaux; Andrew Worster Journal: CMAJ Open Date: 2020-11-02
Authors: Peter A Kavsak; Johannes T Neumann; Louise Cullen; Martin Than; Colleen Shortt; Jaimi H Greenslade; John W Pickering; Francisco Ojeda; Jinhui Ma; Natasha Clayton; Jonathan Sherbino; Stephen A Hill; Matthew McQueen; Dirk Westermann; Nils A Sörensen; William A Parsonage; Lauren Griffith; Shamir R Mehta; P J Devereaux; Mark Richards; Richard Troughton; Chris Pemberton; Sally Aldous; Stefan Blankenberg; Andrew Worster Journal: CMAJ Date: 2018-08-20 Impact factor: 8.262
Authors: Andrew R Chapman; Kuan Ken Lee; David A McAllister; Louise Cullen; Jaimi H Greenslade; William Parsonage; Andrew Worster; Peter A Kavsak; Stefan Blankenberg; Johannes Neumann; Nils A Sörensen; Dirk Westermann; Madelon M Buijs; Gerard J E Verdel; John W Pickering; Martin P Than; Raphael Twerenbold; Patrick Badertscher; Zaid Sabti; Christian Mueller; Atul Anand; Philip Adamson; Fiona E Strachan; Amy Ferry; Dennis Sandeman; Alasdair Gray; Richard Body; Brian Keevil; Edward Carlton; Kim Greaves; Frederick K Korley; Thomas S Metkus; Yader Sandoval; Fred S Apple; David E Newby; Anoop S V Shah; Nicholas L Mills Journal: JAMA Date: 2017-11-21 Impact factor: 56.272
Authors: Ingar Ziad Restan; Ana Yufera Sanchez; Ole-Thomas Steiro; Pedro Lopez-Ayala; Hilde L Tjora; Jørund Langørgen; Torbjørn Omland; Jasper Boeddinghaus; Thomas Nestelberger; Luca Koechlin; Paul Collinson; Rune Bjørneklett; Kjell Vikenes; Heidi Strand; Øyvind Skadberg; Øistein R Mjelva; Alf Inge Larsen; Vernon V S Bonarjee; Christian Mueller; Kristin M Aakre Journal: Eur Heart J Acute Cardiovasc Care Date: 2022-03-16