Health-Related Quality of Life and Angina in Fractional Flow Reserve- Versus Angiography-Guided Coronary Artery Bypass Grafting: FARGO Trial (Fractional Flow Reserve Versus Angiography Randomization for Graft Optimization)
Bibliographic record
Abstract
Background: In coronary artery bypass grafting (CABG), the use of fractional flow reserve (FFR) is insufficiently investigated. Stenosis assessment usually relies on visual estimates of lesion severity. This study evaluated health-related quality of life (HRQoL) and angina after FFR- versus angiography-guided CABG. Methods: One hundred patients referred for CABG were randomized to FFR- or angiography-guided CABG. In the FFR group, lesions with FFR>0.80 were deferred, while the surgeon was blinded to the FFR values in the angiography group. Before and 6 months after CABG, HRQoL was assessed by the health state classifier EQ-5D of the EuroQoL 5-level instrument and angina status based on the Canadian Cardiovascular Society classification system were registered. Results: Six-month angiography included FFR evaluations of deferred lesions. In total, completed EQ-5D of the EuroQoL 5-level instrument questionnaires were available in 86 patients (43 in the FFR versus 43 in the angiography-guided group). HRQoL was significantly improved and angina significantly decreased from baseline to 6 months after CABG with no difference between the randomization groups. Graft failure rates and clinical outcomes were similar in both groups. Patients with graft failure or FFR<0.80 of the previous deferred lesions had significantly lower visual analogue scale scores (78.7±14.2 versus 86.8±14.7, P =0.004) and more angina compared with patients without graft failure or FFR≥0.80 at 6-month follow-up. Conclusions: FFR- versus angiography-guided CABG demonstrated similar improvements in HRQoL and angina 6 months after CABG. Graft failure or low FFR in deferred lesions were associated with low HRQoL and angina. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02477371
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".