Inflammation in calcific aortic stenosis is determined by the metabolic syndrome
Bibliographic record
Abstract
Introduction Calcific aortic stenosis (AS) is an inflammatory disease. We therefore hypothesized that metabolic syndrome (MS) might influence valve inflammatory activity during the development of AS. Methods We analyzed 35 AS valves to compare the relationship between the degree of valvular inflammation and the different atherosclerotic risk factors including the MS. Results Immunohistochemistry studies demonstrated that AS valves were heavily infiltrated by leukocytes. Age, gender, hypercholesterolemia, obesity, smoking, as well as treatment with statins had no significant effect on the extent of valve leukocytes infiltration (VLI). Factors that were associated with VLI were hypertension (36.5±7.6 leukocytes/400x field vs. 19.1±6.1 leukocytes/400x field; p=0.09) and MS (41.2±7.6 leukocytes/400x field vs. 15.3±5.2 leukocytes/400x field; p=0.0008). In multivariate analysis, MS was the only independent predictor of VLI. Lipid infiltration and deposition of apo B‐100 within the aortic valve was significantly increased in AS valves from patients with the MS and correlated with VLI (r=0.42; p=0.01). Furthermore, VLI was inversely correlated with plasma HDL cholesterol level (r=‐0.46; p=0.01), whereas it was not associated with total LDL, triglyceride, adiponectin, CRP, and Apo B100 blood level. Conclusion This is the first study to demonstrate that inflammation in calcific AS is independently associated with the MS. Reduced plasma HDL cholesterol level and enhanced lipid infiltration into the valve are among the main factors responsible for the association between the MS and the development of valvular inflammation.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".