Premature Spinal Bone Loss in Women Living with HIV is Associated with Shorter Leukocyte Telomere Length
Bibliographic record
Abstract
With advances in combination antiretroviral therapy (cART), people living with HIV are now surviving to experience aging. Evidence suggests that individuals living with HIV are at greater risk for low bone mineral density (BMD), osteoporosis, and fractures. Better understanding of the pathophysiology of bone health in women living with HIV (WLWH) is important for treatment strategies. The goal of this study was to explore new biological factors linked to low BMD in WLWH. Standardized BMD measures of WLWH were compared to reference values from an unselected population of women from the same geographical region of the same age range. Linear regression analysis was used to assess relationships among health-related characteristics, cellular aging (measured by leukocyte telomere length; LTL), cART, and BMD of WLWH. WLWH (n = 73; mean age 43 ± 9 years) had lower BMD Z-scores at the lumbar spine (LS) (mean difference = −0.39, p < 0.001) and total hip (TH) (−0.29, p = 0.012) relative to controls (n = 290). WLWH between 50 and 60 years (n = 17) had lower Z-scores at the LS (p = 0.008) and TH (p = 0.027) compared to controls (n = 167). Among WLWH, LS BMD was significantly associated with LTL (R2 = 0.09, p = 0.009) and BMI (R2 = 0.06, p = 0.042). Spinal BMD was adversely affected in WLWH. Reduction of LTL was strongly associated with lower BMD and may relate to its pathophysiology and premature aging in WLWH.
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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 | 0.000 | 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".