Metabolic Syndrome Is Associated With Faster Degeneration of Bioprosthetic Valves
Bibliographic record
Abstract
BACKGROUND: Several studies have reported similarities between calcification of the native aortic valve and atherosclerosis. Recent studies also suggested that hypercholesterolemia may be a risk factor for calcific degeneration of bioprosthetic valves. The metabolic syndrome (MS) is associated with a higher risk of vascular atherosclerosis. We thus hypothesized that the atherogenic features of MS could accelerate bioprosthetic valve degeneration. METHODS AND RESULTS: We included 217 patients who underwent aortic valve replacement with a bioprosthetic valve in the study. Of these patients, 71 patients (33%) had MS defined according to the modified criteria proposed by the National Cholesterol Education Program Adult Treatment Panel III. The annualized increase in mean transprosthetic gradient and the worsening of transprosthetic regurgitation measured by Doppler echocardiography were used to assess the deterioration of valve hemodynamic function. Patients with MS had higher progression of gradient (+4+/-5 mm Hg/year versus +2+/-2 mm Hg/year, P<0.001), higher proportion of > or = 1/3 degree worsening of regurgitation (25% versus 12%, P=0.02), and higher proportion of valve function deterioration defined as regurgitation worsening and/or > or = 3 mm Hg/year increase in gradient (41% versus 25%, P=0.02) when compared with patients without MS. On multivariate analysis, MS was an independent predictor of gradient progression (P=0.01), regurgitation worsening (P=0.02), and valve function deterioration (P=0.02). The other independent predictors were diabetes, renal insufficiency, and higher mean gradient at baseline. CONCLUSIONS: This is the first study to report that the MS is independently associated with faster bioprosthetic valve degeneration. This study could pave the way for the development of a new medical therapy able to significantly reduce the structural valve deterioration of bioprostheses.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".