Multiple Biomarkers to Predict Major Adverse Cardiovascular Events in Patients With Coronary Chronic Total Occlusions
Bibliographic record
Abstract
Background: There are limited tools available to predict the long-term prognosis of persons with coronary chronic total occlusions (CTO). Objectives: We evaluated performance of a blood biomarker panel to predict cardiovascular (CV) events in patients with CTO. Methods: From 1251 patients in the CASABLANCA study, 241 participants with a CTO were followed for an average of 4 years for occurrence of major adverse CV events (MACE, CV death, non-fatal myocardial infarction or stroke) and CV death/heart failure (HF) hospitalization. Results of a biomarker panel (kidney injury molecule-1, N-terminal pro-B-type natriuretic peptide, osteopontin, and tissue inhibitor of metalloproteinase-1) from baseline samples were expressed as low-, moderate-, and high-risk. Results: By 4 years, a total of 67 (27.8%) MACE events and 56 (23.2%) CV death/HF hospitalization events occurred. The C-statistic of the panel for MACE through 4 years was 0.79. Considering patients in the low-risk group as a reference, the hazard ratio of MACE by 4 years was 6.65 (95% confidence interval [CI]: 2.98-14.8) and 12.4 (95% CI:5.17-29.6) for the moderate and high-risk groups (both P <0.001). The C-statistic for CVD/HF hospitalization by 4 years was 0.84. Compared to the low-risk score group, the moderate and high-risk groups had hazard ratios of 5.61 (95% CI: 2.33-13.5) and 15.6 (95% CI: 6.18, 39.2; both P value <0.001). Conclusion: A multiple biomarker panel assists in evaluating the risk of adverse outcomes in patients with coronary CTO. These results may have implications for patient care and could have a role for clinical trial enrichment. Clinical Trial: CASABLANCA, ClinicalTrials.gov Identifier: NCT00842868.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".