Early identification of patients with chest pain at very low risk of acute myocardial infarction using clinical information and ECG only.
Int J Clin Pract. 2020 May 08;:e13526
Authors: Tscherny K, Kienbacher C, Fuhrmann V, Schreiber W, Herkner H, Roth D
Abstract
BACKGROUND: A considerable proportion of patients with angina-like symptoms in an emergency department have very low pre-test probability for acute myocardial infarction (AMI). Numerous algorithms exist for the exclusion of AMI, usually including laboratory tests. We aimed to investigate whether patients with very low risk can safely be identified by ECG and clinical information without biomarker testing, contributing to saving time and costs.
METHODS: Prospective diagnostic test accuracy study. We included all consecutive patients presenting with angina at the department of emergency medicine of a tertiary care hospital during a one-year period. Using clinical information without biomarker testing and ECG, the "Mini-GRACE score", based on the well-established GRACE-score without using laboratory parameters was calculated. In a cohort design we compared the index test Mini-GRACE to AMI as reference standard in the final diagnosis using standard measures of diagnostic test accuracy.
RESULTS: We included 2,755 patients (44% female, age 44±17 years). Acute myocardial infarction was diagnosed in 103 (4%) patients, among those 44% with STEMI. Overall 2,562 patients (93%) had a negative 'Mini-GRACE', four (0.2%) of these patients had myocardial infarction, and this results in a sensitivity of 96.1% (95% CI 90.4-98.9%), specificity 96.5% (95.7-97.1%), positive predictive value 51.3% (46.3-56.3%) and negative predictive value 99.8% (99.6-99.9%). Model performance according to C statistic (0.90) and Brier score (0.0045) was excellent. In rule-out patients 30-day mortality was 0.3%, and one-year mortality was 0.8%.
CONCLUSIONS: Patients with very low risk of AMI can be identified with high certainty using clinical information without biomarker testing and ECG. Cardiac biomarkers might be avoided in such cases, potentially leading to a significant cost reduction.
PMID: 32383504 [PubMed - as supplied by publisher]