Degenerative Aortic Valve Stenosis, but not Coronary Disease, Is Associated With Shorter Telomere Length in the Elderly
Bibliographic record
Abstract
Objective— The mechanisms responsible for the age-related increase in the incidence of calcific aortic valve stenosis (CAS) are unclear but may include telomere-driven cellular senescence. Because telomere length varies widely among individuals of the same age, we hypothesized that patients with shorter telomeres would be prone to develop CAS late in life. Methods and Results— Mean telomere length was measured in leukocytes from a cohort of 193 patients ≥70 years of age with and without CAS. Pilot experiments performed in 30 patients with CAS and controls pair-matched for age, sex, and presence or absence of coronary disease demonstrated significantly shorter telomeres in the CAS group both by Southern blot hybridization (5.75±0.55 kbp versus 6.27±0.7 kbp, P =0.0023) and by a quantitative polymerase chain reaction-based technique (relative telomere length 0.88±0.19 versus 1.0±0.19, P =0.01). This finding was then confirmed in the whole cohort (CAS n=64, controls n=129, relative telomere length=0.86±0.16 versus 0.94±0.12, P =0.0003). Both groups were comparable for potential confounding characteristics. Subgroup analysis according to the presence or absence of coronary disease demonstrated no association of this disorder with telomere length. Conclusions— In the elderly, calcific aortic stenosis, but not coronary disease, is associated with shorter leukocyte telomere length.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".