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Vlad C Vasile, Amy K Saenger, Jean M Kroning, George G Klee, Allan S Jaffe, Biologic Variation of a Novel Cardiac Troponin I Assay, Clinical Chemistry, Volume 57, Issue 7, 1 July 2011, Pages 1080–1081, https://doi.org/10.1373/clinchem.2011.162545
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To the Editor:
Cardiac troponin is the marker of choice for evaluating myocardial injury (1). High-sensitivity assays improve analytical detection limits, thereby allowing concentrations to be measured in the majority of healthy individuals. This capability allows an assessment of biologic variation (BV)1 to determine what constitutes a clinically important change in the cardiac troponin concentration, a critical metric for identifying acute events. Such an event is often a myocardial infarction, but any acute cardiac injury can cause increasing and/or decreasing values (1). Accordingly, we evaluated BV for a recently developed high-sensitivity cardiac troponin I (hs-cTnI) assay (2) from Beckman Coulter. We performed this study with the same cohort used to define BV for the high-sensitivity cardiac troponin T (hs-cTnT) assay (3) and according to a protocol approved by our institutional review board.
For assessment of short-term BV, we collected blood into serum separator tubes (Becton Dickinson) at 0, 1, 2, 3, and 4 h, centrifuged the tubes, and stored the serum samples immediately at −70 °C. Samples are stable under these conditions (2). For the long-term study, samples were obtained biweekly for 8 weeks and processed similarly. After thawing the samples, we analyzed the samples without recentrifugation in duplicate on the Access analyzer (Beckman Coulter). The limit of blank for this assay is 1.03 ng/L, the limit of detection is 2.06 ng/L, the lowest concentration with an imprecision (CV) <10% is 8.66 ng/L, and the 99th percentile value for serum is 8.00 ng/L, as previously reported (2). Reference change values (RCVs) were calculated as previously described (4) according to the method of Fokkema et al. ANOVA (generalized linear model procedure in statistical analysis software; SAS Institute) was used to calculate the sums of squares for the analytical and biological components. Total (SDT2), analytical (SDA2), intraindividual (SDI2), and interindividual (SDG2) variances were determined by the maximum-likelihood approach. Values were averaged across participants; variances were homogeneously distributed. The Cochran test was used to identify outliers; no values were removed. The index of individuality was computed as (CVA2 + CVI2)1/2/CVG, where CVA is the analytical CV, CVI is the intraindividual CV, and CVG is the interindividual CV. Because the data were skewed, RCVs were calculated after lognormal transformation. A 95% CI was used for short- and long-term RCVs.
