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High-sensitivity-cardiac troponin for accelerated diagnosis of acute myocardial infarction: A systematic review and meta-analysis
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High-sensitivity-cardiac troponin for accelerated diagnosis of acute myocardial infarction: A systematic review and meta-analysis
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High-sensitivity-cardiac troponin for accelerated diagnosis of acute myocardial infarction: A systematic review and meta-analysis
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Journal Article
High-sensitivity-cardiac troponin for accelerated diagnosis of acute myocardial infarction: A systematic review and meta-analysis
2020
Overview
Cardiovascular disease is the leading cause of mortality and morbidity. Serial troponin tests have been endorsed as essential diagnostic steps to rule out/−in acute myocardial infarction (AMI), and hs-cTn assays have shown promise in enhancing the accuracy and efficiency of AMI diagnosis in the emergency department (ED).
A systematic review and meta-analysis of diagnostic test accuracy studies were conducted to compare the diagnostic performance of various accelerated diagnostic algorithms of hs-cTn assays for patients with symptoms of AMI. Random-effects bivariate meta-analysis was conducted to estimate the summary sensitivity, specificity, likelihood ratios, and area under receiver operating characteristic curve.
In the systematic review consisting of 56 studies and 67,945 patients, both hs-cTnT and hs-cTnI-based 0-, 1-, 2- and 0–1 h algorithms showed a pooled sensitivity >90%. The hs-cTnI-based algorithm showed a pooled specificity >80%. The hs-cTnT-based algorithms had a specificity of 68% for the 0-h algorithm and of around 80% for the 1-, 2-, and 0–1 h algorithms. The heterogeneities of all diagnostic algorithms were mild (I2 < 50%).
Both hs-cTnI- and hs-cTnT-based accelerated diagnostic algorithms have high sensitivities but moderate specificities for early diagnosis of AMI. Overall, hs-cTnI-based algorithms have slightly higher specificities in early diagnosis of AMI. For patients presenting ED with typical symptoms, the use of hs-cTnT or hs-cTnI assays at the 99th percentile may help identify patients with low risk for AMI and promote early discharge from the ED.
