Telomere Length in Young Patients: Relationship With Metabolic Syndrome and Its Components
Bibliographic record
Abstract
Background: Previous studies have reported inconsistent findings on the relationship between telomere length and metabolic syndrome (MS). The aim of the work was to study leukocyte telomere length in young patients without cardiovascular diseases and its relationship with MS and its components. Methods: This study included 450 Caucasian patients with a median age of 30 (21 - 42) years. Glycemic parameters and lipid profile components were determined using the CardioChek PA (USA, 2017). Integral metabolic indices were calculated in all patients. To investigate leukocyte telomere length, 45 were randomly selected from the total cohort of 450 participants. Results: The selected patients were divided into two groups according to the presence of MS. The median telomere length in MS patients (7.36 (6.96 - 8.67) pn) was significantly lower than in the comparison group (8.72 (8.37 - 8.96) pn) (P = 0.016). Correlation analysis was performed to assess the relationship between telomere length and various traditional cardiovascular risk factors (sex, age, smoking, and blood pressure levels), MS components, and integral metabolic indices. Several linear regression analysis models were constructed to assess the independent associations between various factors and telomere length. Age, smoking, neck circumference, triglycerides, high-density lipoprotein levels, LAP index, and the presence of dyslipidemia were significantly associated with telomere length. Conclusion: Our results are consistent with the notion of shorter leukocyte telomere length in individuals with MS and support an association with dyslipidemia in premature shortening of telomere length. The causal relationship between these changes requires further study.
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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".