Feasibility and applicability of computer‐assisted myocardial blush quantification after primary percutaneous coronary intervention for ST‐segment elevation myocardial infarction
Bibliographic record
Abstract
OBJECTIVES: The aim of the study was to evaluate whether the "Quantitative Blush Evaluator" (QuBE) score is associated with measures of myocardial reperfusion in patients with ST-segment elevation myocardial infarction (STEMI) treated in two hospitals with 24/7 coronary intervention facilities. BACKGROUND: QuBE is an open source computer program to quantify myocardial perfusion. Although QuBE has shown to be practical and feasible in the patients enrolled in the Thrombus Aspiration during Percutaneous Coronary Intervention in Acute Myocardial Infarction Study (TAPAS), QuBE has not yet been verified on reperfusion outcomes of primary percutaneous coronary intervention (PCI) patients treated in other catheterization laboratories. METHODS: Core lab adjudicated angiographic outcomes and QuBE values were assessed on angiograms of patients who were enrolled in the PRoximal Embolic Protection in Acute myocardial infarction and Resolution of ST-Elevation (PREPARE) trial. ST-segment resolution immediately after PCI measured by continuous ST Holter monitoring was calculated by a blinded core lab. RESULTS: The QuBE score could be assessed on 229 of the 284 angiograms (81%) and was significantly associated with visually assessed myocardial blush grade (P < 0.0001). Patients with improved postprocedural Thrombolysis in Myocardial Infarction-graded flow, myocardial blush grade, ST-segment resolution immediately after PCI, or a small infarct size measured by peak CK-MB had a significant better QuBE score. CONCLUSIONS: QuBE is feasible and applicable at angiograms of patients with STEMI recorded at other catheterization laboratories and is associated with measures of myocardial reperfusion.
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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 | 0.004 | 0.012 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".