Stressing the Utility of High-Sensitivity Cardiac Troponin Testing in Patients with Possible Cardiac Ischemia
Bibliographic record
Abstract
Strategies to rule out myocardial infarction (MI)2 in the emergency department include stress test echocardiography, electrocardiography, and assessment of cardiac biomarkers such as troponin I and T (1). The potential for new high-sensitivity cardiac troponin testing to simplify and expedite these rule-out protocols is of great interest. Is all the hype justified? Or are we placing unreasonable expectations on a single laboratory test? There are indeed data indicating that an undetectable or low high-sensitivity cardiac troponin concentration alone at presentation might be useful to rule out MI. Recent data, however, suggest that the addition of other tests may improve the performance and be even more cost-effective compared to high-sensitivity cardiac troponin alone (2, 3). As a …
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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 | 0.005 | 0.001 |
| 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 | 0.001 |
| 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".