BACKGROUND: It is important that cardiac troponin be measured accurately with a robust method to limit false results with potentially adverse clinical outcomes. In this study, we characterized the robustness of 4 analytical platforms by measuring the outlier rate between duplicate results. METHODS: We measured cardiac troponin concurrently in duplicate with 4 analyzers on 2391 samples. The outliers were detected from the difference between duplicate results and by calculating a z value: z = (result 1 - result 2) ÷ √(SD1(est)² + SD2(est)²), with z > 3.48 identifying outliers with a probability of 0.0005. RESULTS: The outlier rates were as follows: Abbott Architect i2000SR STAT Troponin-I, 0.10% (0.01%-0.19%); Beckman Coulter Access2 Enhanced AccuTnI, 0.44% (0.25%-0.63%); Roche Cobas e601 TroponinT hs, 0.06% (0.00%-0.13%); and Siemens ADVIA Centaur XP TnI-Ultra, 0.10% (0.01%-0.19%). The occurrence of outliers was higher than statistically expected on all platforms except the Cobas e601 (χ² = 2.7; P = 0.10). A conservative approach with a constant 10% CV and z > 5.0 identified outliers with clear clinical impact and resulted in outlier rates of 0.11% (0.02%-0.20%) with the Architect i2000SR STAT Troponin-I, 0.36% (0.19%-0.53%) with the Access2 Enhanced AccuTnI, 0.02% (0.00%-0.06%) with the Cobas e601 TroponinT hs, and 0.06% (0.00%-0.13%) with the ADVIA Centaur XP TnI-Ultra. CONCLUSIONS: Outliers occurred on all analytical platforms, at different rates. Clinicians should be made aware by their laboratory colleagues of the existence of outliers and the rate at which they occur.
BACKGROUND: It is important that cardiac troponin be measured accurately with a robust method to limit false results with potentially adverse clinical outcomes. In this study, we characterized the robustness of 4 analytical platforms by measuring the outlier rate between duplicate results. METHODS: We measured cardiac troponin concurrently in duplicate with 4 analyzers on 2391 samples. The outliers were detected from the difference between duplicate results and by calculating a z value: z = (result 1 - result 2) ÷ √(SD1(est)² + SD2(est)²), with z > 3.48 identifying outliers with a probability of 0.0005. RESULTS: The outlier rates were as follows: Abbott Architect i2000SR STAT Troponin-I, 0.10% (0.01%-0.19%); Beckman Coulter Access2 Enhanced AccuTnI, 0.44% (0.25%-0.63%); Roche Cobas e601 TroponinT hs, 0.06% (0.00%-0.13%); and Siemens ADVIA Centaur XP TnI-Ultra, 0.10% (0.01%-0.19%). The occurrence of outliers was higher than statistically expected on all platforms except the Cobas e601 (χ² = 2.7; P = 0.10). A conservative approach with a constant 10% CV and z > 5.0 identified outliers with clear clinical impact and resulted in outlier rates of 0.11% (0.02%-0.20%) with the Architect i2000SR STAT Troponin-I, 0.36% (0.19%-0.53%) with the Access2 Enhanced AccuTnI, 0.02% (0.00%-0.06%) with the Cobas e601 TroponinT hs, and 0.06% (0.00%-0.13%) with the ADVIA Centaur XP TnI-Ultra. CONCLUSIONS: Outliers occurred on all analytical platforms, at different rates. Clinicians should be made aware by their laboratory colleagues of the existence of outliers and the rate at which they occur.
Authors: Stefanie Neubig; Anne Grotevendt; Anders Kallner; Matthias Nauck; Astrid Petersmann Journal: Biochem Med (Zagreb) Date: 2017-02-15 Impact factor: 2.313
Authors: Graham R Lee; Tara Ca Browne; Berna Guest; Imran Khan; Eamon Murphy; Catherine McGorrian; Niall G Mahon; Maria C Fitzgibbon Journal: Pract Lab Med Date: 2016-01-13