Telomere Length and Coronary Atherosclerosis in Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: Telomeres protect against chromosomal end damage and shorten with each cell division; their length may be a marker of cardiovascular and overall biological aging. We examined the hypothesis that reduced telomere length is associated with increased coronary atherosclerosis in rheumatoid arthritis (RA). METHODS: We performed a cross-sectional study in 145 patients with RA and 87 control subjects frequency-matched for age, race, and sex. Coronary artery calcium score was determined by noncontrast cardiac computed tomography. Telomere length was measured from whole blood DNA, using real-time quantitative polymerase chain reaction and expressed as telomeric product to a single-copy gene product ratio (T/S ratio). Associations between telomere length, coronary artery calcium score, and 28-joint Disease Activity Score (DAS28) were assessed with Spearman correlation, proportional odds logistic regression, and linear regression, adjusting for age, race, and sex. RESULTS: Telomere length was significantly inversely correlated with age in patients with RA (ρ = -0.37, p < 0.001) and control subjects (ρ = -0.39, p = 0.001). Among patients with RA, for every interquartile range (IQR) decrease in telomere length (T/S ratio), the odds of higher coronary artery calcium score increased by 38% (95% CI: 4-60) after adjusting for age, race, and sex (p adjusted = 0.03). Telomere length was not associated with DAS28 (p adjusted = 0.17). Telomere length was not significantly different in patients with RA [median (IQR): 1.02 units (0.9-1.11)] compared to control subjects [1.05 units (0.95-1.17); p = 0.10]. CONCLUSION: Telomere length is inversely associated with coronary artery calcium score, independent of age, race, and sex in patients with RA.
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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 | 0.001 | 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) | 0.002 | 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".