Longitudinal Assessment of Bone Mineral Density in Women Living With and Without HIV Across Reproductive Phases
Bibliographic record
Abstract
BACKGROUND: Women living with HIV commonly experience low areal bone mineral density (BMD), but whether this is affected by low ovarian hormonal states (prolonged amenorrhea or menopause) is unknown. We compared rates of BMD loss between women living with HIV and HIV-negative control women and investigated its association with low ovarian hormonal states. SETTING: Women living with HIV were enrolled from Vancouver Canada and controls from 9 Canadian sites. METHODS: This longitudinal analysis included age-matched women living with HIV in the Children and Women: AntiRetrovirals and Markers of Aging cohort and controls in the population-based Canadian Multicentre Osteoporosis Study. Rate of change/year in BMD at the total hip and lumbar spine (L1-L4) between 3 and 5 years was compared between groups, adjusting for sociodemographic and clinical variables. RESULTS: Ninety-two women living with HIV (median [interquartile range] age: 49.5 [41.6-54.1] years and body mass index: 24.1 [20.7-30.8] kg/m 2 ) and 278 controls (age: 49.0 [43.0-55.0] years and body mass index: 25.8 [22.9-30.6] kg/m 2 ) were included. Total hip BMD loss was associated with HIV (β: -0.003 [95% CI: -0.006 to -0.0001] g/cm 2 /yr), menopause (β: -0.007 [-0.01 to -0.005] g/cm 2 /yr), and smoking (β: -0.003 [-0.006 to -0.0002] g/cm 2 /yr); BMD gain was linked with higher body mass index (β: 0.0002 [0.0007-0.0004] g/cm 2 /yr). Menopause was associated with losing L1-L4 BMD (β: -0.01 [-0.01 to -0.006] g/cm 2 /yr). Amenorrhea was not associated with BMD loss. CONCLUSIONS: HIV and menopause negatively influenced total hip BMD. These data suggest women living with HIV require hip BMD monitoring as they age.
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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 | 0.001 | 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".