Diagnostic Yield and Clinical Utility of Coronary Angiography Versus Coronary Function Testing in Women With Angina and Nonobstructive Coronary Arteries
Bibliographic record
Abstract
Background Approximately 50% of women referred for invasive coronary angiography have angina and nonobstructive coronary arteries, which includes coronary microvascular dysfunction, vasospastic angina, and other vasomotor disorders. We sought to determine the real‐world diagnostic yield of invasive coronary angiography and coronary function testing in women with angina and nonobstructive coronary arteries. Methods and Results From 2018 to 2023, we enrolled 198 women who underwent either coronary angiography (CA) alone (n=99) or coronary function testing (CFT; n=99). Mean±SD age was 62±10 years (CA alone) compared with 57±10 years (CFT). Coronary angiography was interpreted as nonobstructive coronary artery disease more frequently after CA alone (79% versus 52%). Of the women who underwent CFT, 82% (N=81) were found to have vasomotor disorders, including coronary microvascular dysfunction (27%), vasospastic angina (32%), mixed coronary microvascular dysfunction/vasospastic angina (16%), endothelial dysfunction (10%; without spasm), elevated resting flow (2%), or symptomatic myocardial bridging (4%). Compared with women undergoing CA alone, medications were changed more frequently after CFT at 24 hours (41% versus 65%; P =0.001) and between 24 hours and 30 days (30% versus 44%; P =0.04) with intensification of antianginal therapy (79% versus 92%; P< 0.0001) and increased use of calcium channel blockers (36% versus 63%; P< 0.0001). Conclusions Our findings demonstrate that women presenting with suspected ischemic heart disease undergoing CA alone only received an anatomic diagnosis, whereas >80% of women undergoing CFT received a specific diagnosis of a coronary vasomotor disorder and greater intensification of antianginal therapy.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".