Association between the progression of aortic valve calcification and coronary atherosclerotic plaque volume
Bibliographic record
Abstract
Abstract Background It is unclear whether the annual progression of aortic valve calcification (AVC) is associated with the progression of coronary atherosclerosis. Purpose We explored the association between AVC and the total and compositional plaque volume (PV) progression. Methods We performed a prospective multinational registry of consecutive patients who underwent serial coronary computed tomography angiography (CTA) at ≥2-year intervals. AVC, and total and compositional PV at baseline and follow-up were quantitatively analyzed. Multivariate linear regression models were constructed. Results Overall, 594 patients (56% male, 61.5±9.7 years old) were included (mean coronary CTA interval, 3.9±1.5 years). At baseline, AVC was 30.9±117.3. Normalized total PV at baseline was 122.3±219.4mm3, encompassing 41.9±116.8mm3 of calcified PV and 80.4±131.5mm3 of non-calcified PV. After adjustment of age, sex, clinical risk factors, and drug use, AVC at baseline was independently associated with total and all compositional PVs (all p<0.001). However, at follow-up, the annual progression of AVC was only associated with the annual progression of calcified PV (β=0.149, p=0.0089), but not with total and non-calcified PVs (all p>0.05) (Table, Figure). Conclusion The overall burden of coronary atherosclerosis is associated with AVC at baseline. However, the progression of AVC is associated only with the progression of calcified PV but not with that of total and non-calcified PV. Representative case Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): The National Research Foundation (NRF) of Korea funded by the Ministry of Science and ICT (MSIT)
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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 | 0.003 |
| 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 | 0.000 |
| Research integrity | 0.000 | 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".