Comprehensive Age and Sex 99th Percentiles for a High-Sensitivity Cardiac Troponin I Assay
Bibliographic record
Abstract
To the Editor: Cardiac troponin I (cTnI)1 is routinely used to aid in the diagnosis of acute myocardial infarction. Few available cardiac troponin assays have adopted 99th percentiles based on patient demographics. However, there is growing evidence of age and sex differences for cTnI and cardiac troponin T (cTnT), especially when using high-sensitivity cardiac troponin assays, with sex-dependent 99th percentiles being recommended for clinical care (1–3). The Single Molecule Counting (SMCTM) cTnI test (Singulex) can measure cTnI in nearly all healthy individuals (4). We sought to establish the 99th percentile for the SMC cTnI test by deriving an objective definition of “healthy” from >100000 patient results. SMC cTnI is a laboratory-developed test (not cleared by the Food and Drug Administration). The test is a quantitative fluorescent 1-step sandwich immunoassay developed to measure human cTnI concentrations in separated EDTA plasma (5). The lower limit of quantification (LLoQ) was 0.40 ng/L (the lowest standard concentration with back-interpolated recovery bias <20% and CV <20%). The LLoQ was the lowest reliable concentration and the lowest result clinically reported. SMC cTnI results were retrospectively mined from the Singulex patient database (n = 132417) containing data from all-comer community-based patients at risk for cardiovascular disease whose physicians ordered this test between 2013 and 2014. The former 99th percentile was 7.1 ng/L and applied to all patients regardless of age or sex. Samples were collected from 21 states within the continental US and shipped overnight at 2 to 8 °C to the CLIA-certified Singulex Clinical Laboratory (SCL) for analysis on the Erenna® system.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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 source (direct Gemma or distilled Codex), 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".