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Objective: To determine gender-specific reference limits of high-sensitivity (hs) cardiac troponins (cTn) and validity of hs assay designation for both genders., Methods: After screening with a questionnaire, 827 presumably healthy individuals were further selected based on clinical criteria (n = 740), clinical criteria plus cardiac imaging including stress magnetic resonance imaging or stress echocardiography (n = 726), and extended cardio-pulmonary parameters (n = 626). Blood samples were measured with hs-cTnT (Roche Diagnostics) on a cobas e602 analyzer as well as hs-cTnI (Abbott Diagnostics) on an ARCHITECT i 2000 SR . The impact of health definition, statistical methods, instrument selection and limit of detection (LoD) on overall and gender-specific 99th percentiles was assessed., Results: Median age was 56 years (50.9% female) for the total study cohort. 99th percentiles for females and males ranged between 13.1 and 13.3 ng/L and 16.8-19.9 ng/L for hs-cTnT as well as 10.3-12.5 ng/L and 27.4-29.7 ng/L for hs-cTnI depending on health definition. Utilization of stricter health definition criteria reduced the difference of the gender-specific 99th percentiles between males and females for hs-cTnT to 3.7 ng/L (males 16.8 ng/L, females 13.1 ng/L), whereas the difference rather increased for hs-cTnI to 19.4 ng/L (males 29.7 ng/L, females 10.3 ng/L). Values > LoD could be measured in the majority of males and females using hs-TnT (81.4-83.3% and 96.5-96.9%, respectively). In contrast, values > LoD could not be observed in the majority of females using hs-cTnI (38.4-41.1%)., Conclusions: In a well-phenotyped healthy cohort, reference values for hs-cTnT were slightly higher, whereas hs-cTnI cut-offs were considerably lower than previously observed. Gender differences were more pronounced in hs-cTnI than in hs-cTnT and were further reduced for hs-cTnT by application of stricter health definition criteria. Contrary to hs-cTnI, hs-cTnT fulfilled criteria for hs designation for both genders., Competing Interests: Declaration of Competing Interest E.G., honoraria for lecturers from Roche Diagnostics, BRAHMS Thermo Scientific, Bayer Vital GmbH and Mitsubishi Chemical Europe, institutional research grant from Roche Diagnostics and Daiichi Sankyo, consultant for Roche Diagnostics and BRAHMS Thermo Scientific, outside the submitted work; M.M.-H., research support by the Medical Faculty of Heidelberg University, during conduct of the study, research support from Roche Diagnostics and BRAHMS Thermo Scientific, speaker honoraria from Roche Diagnostics, non-financial support by BRAHMS Thermo Scientific, Bayer Vital GmbH, Daiichi-Sankyo, Metanomics Health GmbH and Philips Electronics, outside the submitted work; M.B., research support from AstraZeneca and travel support from BRAHMS Thermo Scientific, outside the submitted work; M.V., financial support from Bayer Vital GmbH and Daiichi Sankyo, reimbursement for travel expenses and fees associated with attending seminars and conferences by Bayer Vital GmbH, Lilly Germany, GlaxoSmithKline, Roche Diagnostics and Brahms, outside the submitted work; K.M.S., research supported by Bayer Vital GmbH, outside the submitted work; S.B., non-financial support from Abbott Diagnostics, grants and personal fees from Abbott Diagnostics, Siemens, Thermo Fisher and Roche Diagnostics, outside the submitted work; H.K., honoraria from AstraZeneca, Eli Lilly, GlaxoSmithKline, Roche Diagnostics, and Bayer, holds a Troponin T Test Invention patent jointly with Roche and receives royalties for this patent, outside the submitted work. All other authors have nothing to disclose., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Cardiac troponin (cTn) is the biomarker of choice for assessment of patients with acute coronary syndromes. Guidelines recommend the cTn 99th percentile derived from a cardiovascular healthy reference population as decision threshold. The importance of standardized criteria for the composition of such a reference population is well acknowledged. In this analysis, we investigated to which extent different statistical methods might have bearing on the calculated cTnI 99th percentile., Methods: cTnI (Abbott) 99th percentiles were determined in 521 cardiovascular healthy community-dwelling subjects using the nonparametric method, the Harrell-Davis bootstrap method and the robust method together with different tests to identify potential outliers (Dixon, Tukey, Reed) and different statistical softwares., Results: The cTnI 99th percentiles (nonparametric method) were 37ng/L (total population), 42ng/L (men) and 25ng/L (women). These estimates differed by -7.4% to +5.7% using the Harrell-Davis bootstrap method and were up to 64.1% lower using the robust method. For the robust method, cTnI 99th percentiles varied by 44.2% depending on the applied software. The method of Tukey classified nine subjects as outliers while no outlier was detected using the other methods. Excluding these nine subjects resulted in up to 60.2% lower cTnI 99th percentiles., Conclusions: Our results emphasize the need of a standardized statistical approach to calculate cTnI 99th percentiles. Our findings support the use of the nonparametric method and a conservative approach to detect outliers. This requires that the assessed population is sufficiently large and well selected on the basis of stringently applied clinical criteria., (Copyright © 2016 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.)