Prognostic significance of plaque location in non-obstructive coronary artery disease: from the CONFIRM registry
Bibliographic record
Abstract
AIM: Obstructive coronary artery disease (CAD) in proximal coronary segments is associated with a poor prognosis. However, the relative importance of plaque location regarding the risk for major adverse cardiovascular events (MACE) in patients with non-obstructive CAD has not been well defined. METHODS AND RESULTS: From the Coronary CT Angiography Evaluation for Clinical Outcomes: An International Multicenter (CONFIRM) registry, 4644 patients without obstructive CAD were included in this study. The degree of stenosis was classified as 0 (no) and 1-49% (non-obstructive). Proximal involvement was defined as any plaque present in the left main or the proximal segment of the left anterior descending artery, left circumflex artery, and right coronary artery. Extensive CAD was defined as segment involvement score of >4. During a median follow-up of 5.2 years (interquartile range 4.1-6.0), 340 (7.3%) MACE occurred. Within the non-obstructive CAD group (n = 2065), proximal involvement was observed in 1767 (85.6%) cases. When compared to non-obstructive CAD patients without proximal involvement, those with proximal involvement had an increased MACE risk (log-rank P = 0.033). Multivariate Cox analysis showed when compared to patients with no CAD, proximal non-obstructive CAD was associated with increased MACE risk [hazard ratio (HR) 1.90, 95% confidence interval (CI) 1.47-2.45, P < 0.001] after adjusting for extensive CAD and conventional cardiovascular risk factors; however, non-proximal non-obstructive CAD did not increase MACE risk (HR 1.26, 95% CI 0.79-2.01, P = 0.339). CONCLUSIONS: Independent of plaque extent, proximal coronary involvement was associated with increased MACE risk in patients with non-obstructive CAD. The plaque location information by coronary computed tomography angiography may provide additional risk prediction over CAD extent in patients with non-obstructive CAD.
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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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.001 | 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".