Impact of Optical Coherence Tomography-Based Post-PCI Physiology Assessment to Predict Clinical Outcomes
Bibliographic record
Abstract
BACKGROUND: A novel optical coherence tomography (OCT)-based physiology assessment technique, virtual flow reserve (VFR), has been demonstrated to perform as a reliable surrogate for invasive physiology. OBJECTIVES: The authors sought to examine the performance of post-percutaneous coronary intervention (PCI) VFR as a predictor of 2-year clinical outcomes independent from the OCT-based minimal stent area (MSA). METHODS: The ILUMIEN IV (Optical Coherence Tomography [OCT] Guided Coronary Stent Implantation Compared With Angiography: A Multicenter Randomized Trial in PCI) trial prospectively recruited 2,487 patients with diabetes or high-risk coronary lesions randomizing to OCT- vs angiography-guided drug-eluting stent implantation. All patients with single-lesion treatment who had a final OCT imaging available underwent retrospective post-PCI VFR analysis offline. Of 2,128 eligible patients, VFR analysis was successfully performed in 2,057 (96.6%). Independent OCT predictors for the primary endpoint of 2-year target vessel failure (TVF), a composite of cardiac death, target-vessel myocardial infarction, and ischemia-driven target vessel revascularization, were evaluated by multivariable analysis. RESULTS: ) and VFR (per 0.1 mm Hg/mm Hg) were independent predictors of 2-year TVF. Overall, MSA, proximal edge dissection and VFR independently predicted both TVF and target lesion failure. CONCLUSIONS: Post-PCI OCT-based VFR assessment is predictive of 2-year clinical outcomes independent of MSA. Online VFR analysis can provide operators with an immediate assessment of post-PCI physiology in addition to OCT anatomy, providing incremental value in assessing procedural success and informing on clinical prognosis (ILUMIEN IV [Optical Coherence Tomography (OCT) Guided Coronary Stent Implantation Compared With Angiography: A Multicenter Randomized Trial in PCI]; NCT03507777).
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".