Medically Treated Nonischemic Thin-Cap Fibroatheroma Lesions Versus Fractional Flow Reserve-Guided Complete Revascularization in Diabetic Patients
Bibliographic record
Abstract
Background Fractional flow reserve (FFR) is an established method to guide decisions on revascularization; however, in patients with diabetes mellitus (DM), FFR-negative lesions carrying an optical coherence tomography-detected thin-cap fibroatheroma (TCFA) remain at high risk for adverse cardiac events. Methods In this prespecified subanalysis of the COMBINE OCT-FFR trial, DM patients with ≥1 FFR-negative, TCFA-positive medically treated target lesions referred to as vulnerable plaque (VP group), were compared to patients with exclusively FFR-positive target lesions who underwent complete revascularization (CR group). The primary endpoint was first and recurrent event analysis for target lesion failure and the secondary endpoint was a composite of cardiac death, target vessel myocardial infarction, target lesion revascularization, or hospitalization due to unstable angina. Results Among 550 patients enrolled, 98 belonged to the VP group while 93 to the CR group and were followed up to 5 years. The VP group had a higher occurrence of the primary endpoint (20.4% vs 8.6%; HR, 2.22; 95% CI, 0.98-5.04; P = .06). Recurrent event analysis showed that the VP group had significantly higher rates of the primary and secondary endpoints (9.17 vs 3.76 events per 100 PY; RR, 2.44; 95% CI, 1.16-5.60; P = .01 and 13.45 vs 5.63 events per 100 PY; RR, 2.39; 95% CI, 1.30-4.62; P < .01). Conclusions In a population with DM, medically treated nonischemic, TCFA-carrying target lesions were associated with higher risk of reoccurring adverse cardiac events compared to target lesions that underwent complete revascularization, opening the discussion about whether a focal preventive revascularization strategy could be contemplated for highly vulnerable lesions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".