The functional assessment of patients with non-obstructive coronary artery disease: expert review from an international microcirculation working group
Bibliographic record
Abstract
Symptomatic non-obstructive coronary artery disease (NOCAD) is an increasingly recognised entity that is associated with poor cardiovascular outcomes. Nearly half of those undergoing coronary angiography for appropriate indications, such as typical angina, or a positive stress test have no obstructive lesion. There are no guideline recommendations as to how to care properly for these patients. Physiologic assessment of the coronary arteries beyond two-dimensional angiography is not standardised, yet it can provide valuable information in patients presenting with typical angina in the setting of NOCAD. In this consensus document, we detail steps for the interventional cardiologist to evaluate the patient with symptomatic NOCAD in the cardiac catheterisation laboratory, first with the assessment of coronary flow reserve (CFR), and then with delineation of deficiencies in non-endothelium-dependent CFR (CFRne) versus endothelium-dependent CFR (CFRe) using provocative agents such as adenosine and acetylcholine, respectively, followed by the evaluation of smooth muscle function with nitroglycerine (NTG). Once the mechanism behind the anginal symptoms is established, one can identify the appropriate treatment strategies to address the physiologic deficiency that is present. Despite an established safety profile, a comprehensive assessment may be considered for selected patients which requires an understanding of the appropriate invasive evaluation by the practising interventional cardiologist when evaluating not only patients with obstructive CAD but also those with NOCAD.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".