P6162Difference in progression to obstructive lesions according to the presence of high-risk plaque features
Bibliographic record
Abstract
Abstract Background It is still debatable whether the so-called high-risk plaque (HRP) simply represents a certain phase during the natural history of coronary atherosclerotic plaques or the disease progression would differ according to the presence of HRP. Purpose We determined whether the pattern of non-obstructive lesion progression into obstructive lesions would differ according to the presence of HRP. Methods Patients with non-obstructive coronary artery disease, defined as % diameter stenosis (%DS) ≥50%, were enrolled from a prospective, multinational registry of consecutive patients who underwent serial coronary computed tomography angiography at an inter-scan interval of ≥2 years. HRP was defined as lesions with ≥2 of positive remodelling, spotty calcification, and low-attenuation plaque. The total and compositional percent atheroma volume (PAV) at baseline and annualized PAV change were compared between non-HRP and HRP lesions. Results A total of 1,115 non-obstructive lesions were identified from 327 patients (61.1±8.9 years old, 66.0% male). There were 690 non-HRP and 425 HRP lesions. HRP lesions possessed greater PAV and %DS at baseline compared to non-HRP lesions. However, the annualized total and non-calcified PAV change were greater in non-HRP lesions than in HRP lesions. On multivariate analysis, addition of baseline PAV and %DS to clinical risk factors improved the predictive power of the model (Table). When clinical risk factors, PAV, %DS, and HRP were all adjusted on Model 3, only baseline PAV and %DS independently predicted the development of obstructive lesions (hazard ratio (HR) 1.046 [95% confidence interval (CI): 1.026–1.066] and HR 1.087 [95% CI: 1.055–1.119], respectively, all p<0.001), while HRP did not (p>0.05). Comparison of C-statistics of per-lesion analysis to predict progression to obstructive lesion C-statistics (95% CI) P Model 1: Baseline PAV 0.880 (0.879–0.884) – Model 2: Model 1 + baseline %DS 0.938 (0.937–0.939) vs. Model 1: <0.001 Model 3: Model 2 + HRP 0.935 (0.934–0.937) vs. Model 2: 0.004 Adjusted for age, male sex, hypertension, diabetes mellitus, hyperlipidemia, family history of coronary artery disease, smoking, body mass index, and statin use. Conclusion The pattern of individual coronary atherosclerotic plaque progression differed according to the presence of HRP. Baseline PAV was the most important predictor for lesions developing into obstructive lesions rather than the presence of HRP features at baseline. Acknowledgement/Funding This work was supported by the National Research Foundation of Korea funded by the Ministry of Science and ICT (Grant No. 2012027176).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".