High-Sensitivity Cardiac Troponin I Measurement for Risk Stratification in a Stable High-Risk Population
Bibliographic record
Abstract
BACKGROUND: Past investigations regarding the utility of high-sensitivity cardiac troponin I (cTnI) assays have been focused primarily on the acute coronary syndrome setting. We assessed whether such assays can predict future ischemic cardiovascular events in a stable high-risk population. METHODS: We quantified serum cTnI using an investigational high-sensitivity assay (hs-cTnI IUO, Beckman Coulter) in 2572 participants from the Heart Outcomes Prevention Evaluation (HOPE) study. The derived ROC curve cutoff and the 99th percentile for the hs-cTnI assay were assessed by Kaplan-Meier and Cox analyses for the primary outcome [composite of myocardial infarction (MI), stroke, and cardiovascular death] at 4.5 years of follow-up. We also assessed individual outcomes (MI, stroke, cardiovascular death) and the combined outcome (MI/cardiovascular death) by regression analyses to determine hazard ratios (HRs) and c statistics in models that included established risk factors, C-reactive protein, and N-terminal pro-B-type natriuretic peptide (NT-proBNP). RESULTS: Participants with hs-cTnI >6 ng/L (ROC cutoff) were at higher risk for the primary outcome (HR 1.38, 95% CI 1.09-1.76; P = 0.008, adjusted models). For the individual outcomes, participants with hs-cTnI above the 99th percentile (≥10 ng/L) had higher risk for cardiovascular death (HR 2.15, 95% CI 1.32-3.52; P = 0.002) and MI (HR 1.49, 95% CI 1.05-2.10; P = 0.025) but not stroke (HR 1.38, 95% CI 0.76-2.47; P = 0.288, adjusted models). Addition of hs-cTnI to an established risk model with NT-proBNP also yielded a higher c statistic for the combined outcome of MI/cardiovascular death. CONCLUSIONS: The investigational Beckman Coulter hs-cTnI assay provides prognostic information for future MI and cardiovascular death in a stable high-risk population.
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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 | 0.004 | 0.004 |
| 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 | 0.000 |
| 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".