Validation of presentation and 3 h high-sensitivity troponin to rule-in and rule-out acute myocardial infarction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: International guidelines to rule-in acute myocardial infarction (AMI) in patients presenting with chest pain to the emergency department (ED) recommend an algorithm using high-sensitivity cardiac troponin (hs-cTn) sampling on presentation and 3 h following presentation. We tested the diagnostic accuracy of this algorithm by pooling data from five distinct cohorts from three countries of prospectively recruited patients with independently adjudicated outcomes. METHOD: We measured high-sensitivity cardiac troponin I (hs-cTnI) and high-sensitivity cardiac troponin T (hs-cTnT) on presentation (0 h) and 3 h post-presentation samples in adult patients attending an ED with possible AMI to validate the European Society of Cardiology (ESC) Working Group on Acute Cardiac Care rule-in algorithm (ESC-rule-in). Specifically, (i) in patients with a 0 h hs-cTn concentration ≤99th percentile and a 3 h hs-cTn >99th percentile, positive patients are those with an absolute change in troponin ≥50% of the 99th percentile, and (ii) in patients with a 0 and 3 h hs-cTn >99th percentile, positive patients are those with a relative change in troponin of ≥20%. We concurrently assessed the efficacy of the 0 and 3 h hs-cTn <99th percentile to rule-out AMI. RESULTS: 1061 patients with hs-cTnI and 985 with hs-cTnT were included. The ESC-rule-in positive predictive value (PPV) was 83.5% (95% CI 74.9% to 90.1%) for hs-cTnI and 72.0% (95% CI 62.1% to 80.5%) for hs-cTnT. Forty-six AMIs (34.9%) were not ruled in using hs-cTnI and 62 (46.2%) using hs-cTnT. The sensitivity of the 99th percentile to rule-out AMI was 93.2% (95% CI 87.5% to 96.8%) for hs-cTnI and 94.8% (95% CI 89.5% to 97.9%) for hs-cTnT. CONCLUSIONS: The ESC-rule-in algorithm has good PPV with hs-cTnI and reasonable with hs-cTnT and can rule-in over 50% of AMIs. However, the sensitivity of the 99th percentile to rule-out AMI is too low for clinical use.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 it