Validation of Analytical Performance Limits for Accuracy with High-Sensitivity Cardiac Troponin Assays
Bibliographic record
Abstract
Fifteen years ago, a publication on a prototype high-sensitivity cardiac troponin (hs-cTn) I assay determined a CV of 10.9% at a mean concentration of 10.2 ng/L using quality control material (SD = 1.11 ng/L) (1). Acceptable analytical variation used in in this publication to assess early diagnostic utility (i.e., change or the delta for serial concentrations) of the hs-cTn assay was ±3.33 ng/L (1). In recent years, significant attention has been focused on defining what constitutes a clinically significant change or difference in hs-cTn concentrations, while there has been less published data and fewer studies on the analytical limits for the accuracy of hs-cTn assays (2). There has been some interest in biological variation as a quality metric for hs-cTn assays, with a meta-analysis indicating similar reference change values in healthy individuals over the short term with hs-cTnI (−25.6 to 34.4%) and hs-cTnT (−26.2 to 35.6%) (3). However, higher biological variation than these estimates has been reported, with clinical simulation data providing different estimates for acceptable analytical variation in relation to patient classification for myocardial infarction (4). A recent year-long multisite study assessing analytical variation for hs-cTn determined that acceptable analytical variation below 10 ng/L was ±3 ng/L with 30% variation acceptable above and near the 99th-percentile concentrations (5). Thirty-six sites participated in this study with patient material (3 samples: normal, female 99th percentile, male 99th percentile) tested monthly, yielding 2142 results from 6 different hs-cTn assays over the year (5). We aimed to validate these analytical limits for accuracy by reassessing external quality assurance data from 2 large proficiency testing programs that evaluated hs-cTn assays from 2021 to 2024.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".