3210Long-term follow-up of patients with non-obstructive coronary artery disease presenting with stable angina
Bibliographic record
Abstract
Background: Non-obstructive coronary artery disease (stenosis <50%; NOCAD) is a common finding on coronary angiography, with up to 65% of patients with stable angina (SA) being diagnosed with NOCAD. In the past, prognosis of these patients was deemed favourable but recent studies showed increased cardiovascular event rates in these patients compared to patients with normal coronaries. Our goal was to evaluate in a large cohort the long-term prognosis of NOCAD patients in comparison to patients with obstructive coronary artery disease (CAD). Furthermore, we sought to examine the rate of development of obstructive CAD, and future interventions in NOCAD patients, and whether NOCAD patients presenting with an acute coronary syndrome (ACS) have an increased risk of all cause-mortality compared to NOCAD patients with SA. Methods: The study cohort consisted of patients with normal EF (≥50%) who presented with SA, and underwent invasive coronary angiography between 1995 and 2012. Patients with valvular disease, left main disease, prior PCI or CABG were excluded. The main NOCAD cohort consisted of 7478 patients with SA. The first comparison group contained 10906 patients with stable obstructive CAD, whereas the second comparison group consisted of 7344 patients with NOCAD presenting with an ACS. The primary endpoint was all-cause mortality of NOCAD SA patients in comparison to CAD patients. Secondary endpoints were repeat angiogram, future obstructive CAD on angiogram, and future percutaneous intracoronary intervention (PCI) of SA patients. Predictors of all-cause mortality were determined by multivariate analyses. All-cause mortality of NOCAD ACS patients was compared to SA patients.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".