Coronary Physiology Derived from Invasive Angiography: Will it be a Game Changer?
Bibliographic record
Abstract
There is a large body of evidence suggesting that having knowledge of the presence and extent of coronary atheroma and whether it is causing downstream myocardial ischaemia facilitates optimal diagnosis and management for patients presenting with chest pain. Despite this, the use of coronary pressure wire in routine practice is surprisingly low and routine assessment of all diseased vessels before making a bespoke management plan is rare. The advent of angiogram-derived models of physiology could change diagnostic practice completely. By offering routine assessment of the physiology of all the major epicardial coronary vessels, angiogram-derived physiology has the potential to radically modify current practice by facilitating more accurate patient-level, vessel-level, and even lesion-level decision-making. In this article, the authors review the current state of angiogram-derived physiology and speculate on its potential impact on clinical practice.
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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 | 0.016 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".