Abstract 911: Usefulness of Coronary Fractional Flow Reserve Measurements to Guide Clinical Decisions in Intermediate Left Main Coronary Stenoses. Results of a Study Including 142 Consecutive Patients
Bibliographic record
Abstract
Background: Limited data exist on the use of fractional flow reserve (FFR) measurements to guide clinical decisions in patients with intermediate left main coronary artery (LMCA) stenosis. Objectives: To evaluate the usefulness of FFR measurements to guide the clinical decision in patients with intermediate LMCA stenosis and to determine the predictors of major adverse cardiac events [MACE] (cardiac death, myocardial infarction, coronary revascularization) in such cases. Methods: A total of 142 consecutive patients (mean age 62 ± 10 yrs) with intermediate LMCA stenosis (mean percent diameter stenosis 42 ± 13%) were included. All patients underwent FFR measurement after intracoronary (ic) administration of adenosine at a dose ≥30 μg. Special care was taken in cases with ostial lesions to pull the catheter out of the LMCA after adenosine administration. The clinical decisions were based on FFR as follows: coronary revascularization was recommended if FFR was <0.75, medical treatment if FFR was >0.80, and individualized decision based on additional clinical data if FFR was between 0.75 and 0.80. The occurrence of MACE was evaluated at 14 ± 11 months follow-up. Results: Mean FFR was 0.81 ± 0.09 after the administration of a mean dose of 176 ± 99 μg of ic adenosine. Based on FFR results, sixty patients (42%) underwent coronary revascularization and 82 patients (58%) received medical treatment. At follow-up, the incidence of MACE related to the LMCA stenosis was 13% in the medical treatment group and 7% in the coronary revascularization group (p=0.27). The incidence of cardiac death and myocardial infarction was 7% in both groups (p=1.0). In the medical treatment group, patients with MACE had received a lower dose of ic adenosine (86 ± 57 μg vs. 167 ± 102 μg, OR: 1.39 for each decrease of 30 μg of ic adenosine, 95% CI 1.02–1.89, p=0.04) and were more frequently diabetics (55% vs. 21%, OR: 4.40, 95% CI 1.17–16.42, p=0.02). Conclusions: FFR measurement is helpful in guiding the decision as to whether to revascularize patients with intermediate LMCA stenosis. However, diabetic patients remain at higher risk, and higher doses than previously recommended of ic adenosine should be used in the evaluation of LMCA to avoid cardiac events due to underestimation of stenosis severity.
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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 | 0.004 |
| 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) | 0.001 | 0.001 |
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".