For a rapid diagnosis of acute myocardial infarction, a sensitive troponin assay is needed in the near-patient testing setting
Bibliographic record
Abstract
Evaluation of: Collinson P, Goodacre S, Gaze D et al. Very early diagnosis of chest pain by point-of-care testing: comparison of the diagnostic efficiency of a panel of cardiac biomarkers compared with troponin measurement alone in the RATPAC trial. Heart 98(4), 312–318 (2012).An early diagnosis of myocardial infarction in the emergency setting would be advantageous for both patients and the physicians treating these patients. Guidelines currently recommend serial samples that are drawn at presentation and 6–9 h later to be measured for cardiac troponin to aid in this diagnosis. However, much effort has been directed to decrease the time to make a diagnosis in this setting, and there has been renewed interest in shortening the time between serial measurements as well as the turnaround time for reporting the results. By eliminating the blood sample transit time to the central laboratory, point-of-care testing or near-patient testing can reduce the turnaround time for reporting the results, however this is possibly at the cost of decreased diagnostic performance. In this article, we discuss the recent results from the RATPAC study, which evaluated whether the combination of myoglobin, the MB isoenzyme of creatine kinase (CKMB) and a sensitive troponin assay would be superior to troponin alone.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".