Abstract 14304: Assessing the Association of Adherence to Fractional Flow Reserve Treatment Thresholds and Outcomes of Patients With Coronary Artery Disease
Bibliographic record
Abstract
Background: Although fractional flow reserve (FFR) thresholds have been established to guide the use of percutaneous coronary intervention (PCI) or medical therapy, little is known about the adherence to FFR thresholds for PCI in clinical practice and their association with clinical outcomes. Methods: Adults undergoing FFR assessment in a single vessel (excluding ST-segment elevation myocardial infarction [MI]) from April 1, 2013 to March 31, 2018 in Ontario, Canada were included. Patients were divided into two cohorts based on FFR ≤ 0.80 (ischemic) and > 0.80 (non-ischemic). Inverse probability of treatment weighting was used to balance confounders between patients treated with PCI vs. no PCI in each cohort. The primary outcome was major adverse cardiac events (MACE) defined by death, MI, unstable angina, or urgent revascularization. Results: We identified 9,106 patients who underwent single-vessel FFR measurement. Among the 2,693 patients with an ischemic FFR (mean age 65, 27.0% female), 75.3% of patients received PCI and 24.7% were treated only with medical therapy. Over a median follow-up of 2.6 years in the ischemic cohort, PCI was associated with a 20% lower rate of MACE compared to no PCI (24.0% vs. 31.6%; hazard ratio [HR]: 0.80, 95% CI: 0.66-0.96). However, among 6,413 patients with a non-ischemic FFR (mean age 66, 38.9% female), 12.6% received PCI and 87.4% were treated only with medical therapy. Over a median follow-up of 2.8 years in the non-ischemic cohort, PCI was associated with a 42% higher rate of MACE compared to no PCI (25.6% vs. 17.6%; HR: 1.42, 95% CI: 1.18-1.70). The increased rate of MACE was driven mainly by MI (HR 1.67, 95% CI: 1.20-2.31) but not death (HR 0.99, 95% CI: 0.72-1.35). Conclusions: In routine practice, we found 1 in 4 patients did not receive PCI for ischemic lesions while 1 in 8 received PCI for non-ischemic lesions. Performing PCI procedures according to recommended FFR cutoffs was associated with lower rates of clinical events.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".