Why the study?
The study was conducted to establish the 99th-percentile cutoff for a sensitive cardiac troponin-I assay in an Egyptian population.
Does the exclusion of cardiovascular risk factors affect the 99th-percentile cutoff for sensitive cardiac troponin-I assays in the Egyptian population?
Does the exclusion of cardiovascular risk factors affect the 99th-percentile cutoff for sensitive cardiac troponin-I assays in the Egyptian population?
Establishing cTnI 99th-percentile cutoffs in a strictly healthy population without cardiovascular risk factors yields lower thresholds, increasing sensitivity but reducing specificity for MI diagnosis.
Answers are grounded in this paper and cite their sources.
Local cTnI cutoffs may aid MI diagnosis in Egyptians; leaves open outcome-based validation before practice change.
Background To establish the 99th-percentile cutoff for sensitive cardiac troponin-I (cTnI) assay in Egyptian population. Patients and methods A sample size of 400 volunteers were divided into two groups [group A, including 200 participants without cardiovascular risk factors (CVRF), and group B, including 200 participants with more than 1 CVRF]. These two groups were used to create cardiac troponin-I (cTnI) 99th-percentile cutoffs, which were implied later on a third group of 100 patients suspected as myocardial infarction (MI) to illustrate the effect of the calculated values and to assess their precision in the diagnosis of MI. Results After calculation of the 99th percentile of each group, the present data revealed that the exclusion of CVRFs resulted in lowering of the calculated cutoffs from 0.05 to 0.038 ng/ml for group B and group A, respectively. Additionally, it has been clear that sex and age are important factors influencing the cTn concentrations. These lower values have predicted more patients at risk of having acute MI. There were correlations of troponin I with age, sex, and traditional risk factors. Conclusion Troponin-I concentrations in apparently healthy individuals rely on cardiac risk factors, sex, and age. Using the lower cutoff values after exclusion of risk factors led to prediction of more patients at risk compared with higher thresholds at the expense of specificity.
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Nassar et al. (2020) studied this question.
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