High-Sensitivity Cardiac Troponin Assays—Change Is Important
Bibliographic record
Abstract
To the Editor: The recent publication by Aldous and colleagues in Clinical Chemistry (1) starts an important discussion concerning the optimal change criteria that should be used with high-sensitivity (hs)1 cardiac troponin assays. This report suggests that an optimal relative change (i.e., percent δ) in hs cardiac troponin T (hs-cTnT) for predicting a major adverse cardiovascular event over a 1-year period is 3%. This relative difference was not significant, however, with respect to risk stratification (hazard ratio, 1.6; P = 0.052) and would not be considered an analytically robust change, because 3% is within the imprecision of the assay at concentrations measured with the low- and high-quality control materials provided by Roche Diagnostics for this assay. From the data presented, it appears that the percent δ values for hs-cTnT concentrations over 2 h were not important for long-term risk stratification; however, relative changes (e.g., 10% as determined by ROC curve analysis) did improve the detection of the index diagnosis of myocardial infarction (MI) in patients presenting …
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; both teacher heads agree on what is shown here.
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".