Usefulness of fractional flow reserve in determining the indication of target lesion revascularization
Bibliographic record
Abstract
The objective of this study was to examine the usefulness of fractional flow reserve (FFR) in determining the indication of target lesion revascularization (TLR) at follow-up angiography after percutaneous coronary intervention (PCI). One hundred forty-seven patients with 155 lesions that had intermediate restenosis took part in this study. FFR was measured in all patients for the evaluation of stenosis severity. Then TLR was performed when FFR was < 0.75, and TLR was deferred when FFR was > or = 0.75. Patients in whom TLR was deferred were followed up clinically (25 +/- 11 months). In 98 patients (67%) who underwent stress myocardial scintigraphy before angiography, the results of the scintigraphy were compared with FFR results. TLR was performed in 34 lesions (22%). After TLR, the Canadian Cardiovascular Society class decreased significantly (from 1.5 +/- 0.7 to 1.1 +/- 0.5; P < 0.05). In 113 patients who did not undergo TLR, only 4 patients (3.5%) had cardiac events (re-PCI in 1 patient and a positive SPECT in 3 patients). Discordance between the results of scintigraphy and FFR was observed in 30 patients (30%), but the patients who had good values of FFR > or = 0.75 showed a nil event rate (0%). FFR might be useful for the determination of the indication of TLR.
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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 | 0.010 |
| 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 | 0.001 | 0.000 |
| 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".