Abstract 3334: Comparison of Medical Treatment and Coronary Revascularization in Patients with Moderate Coronary Lesions and Borderline Fractional Flow Reserve Measurements
Bibliographic record
Abstract
Background. There is little information available regarding deferral of revascularization in cases of fractional flow reserve (FFR) measurements in the borderline range (between 0.75 to 0.80). The objectives of this study were to evaluate the clinical outcomes of patients with moderate coronary lesions and FFR measurements between 0.75 and 0.80, comparing those who underwent coronary revascularization (CR) to those who had medical treatment (MT), and to determine the predictive factors of major adverse cardiac events (MACE) at follow-up. Methods. A total of 107 consecutive patients (mean age 62 ± 10 years) with at least one moderate coronary lesion (mean percent diameter stenosis 47 ± 12%) evaluated by coronary pressure wire with FFR measurement between 0.75 and 0.80 (mean 0.77 ± 0.02) were included in the study. Maximal hyperemia was obtained by intracoronary administration of adenosine (mean dose 215 ± 84 μg). MACE (coronary revascularization, myocardial infarction, cardiac death) and the presence of angina were evaluated at follow-up. Results. A total of 63 patients (59%) underwent CR and 44 patients (41%) had MT, with no clinical differences between groups. At a mean follow-up of 13 ± 7 months, MACE related to the coronary lesion evaluated by FFR were higher in the MT group compared to CR group (23% vs 5%, difference 18%, 95% CI 5%–30%, p=0.005). FFR measurement in an artery supplying a territory with previous myocardial infarction was the only predictive factor of MACE in the MT group (odds ratio 14.1, 95% CI 1.3–39, p=0.03). The presence of angina at follow-up was more frequent in the MT group compared to the CR group (41% vs 9%, difference 32%, 95% CI 11%–49%, p<0.001). Conclusions. In patients with moderate coronary lesions and FFR measurements in the “grey zone” range deferral of revascularization was associated with a higher rate of cardiac events and a higher prevalence of angina at follow-up, especially in those with previous myocardial infarction in the territory evaluated by FFR. These results suggest that a FFR cut-off point of 0.80 rather than 0.75 might be more appropriate for deferring coronary revascularization in these cases.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".