Bone Mineral Density Declines Twice as Quickly Among HIV-Infected Women Compared With Men
Bibliographic record
Abstract
BACKGROUND: Initial declines in bone mineral density (BMD) after antiretroviral therapy initiation in HIV are well described, but data on long-term changes and risk factors for decline, particularly among women, are limited. METHODS: HIV-infected men and women in the Modena Metabolic Clinic underwent dual-energy X-ray absorptiometry (DXA) scans every 6-12 months for up to 10 years (median 4.6 years). Mixed effect regression models in combined and sex-stratified models determined annual rates of decline and clinical factors associated with BMD. Models included demographics, HIV-specific factors, and bone-specific factors; a final model added a sex × time interaction term. RESULTS: A total of 839 women and 1759 men contributed ≥2 DXA scans. The majority (82%) were 50 years and younger; 76% had HIV-1 RNA <50 copies per milliliter at baseline; 15% of women were postmenopausal and 7% of men had hypogonadism; and 30% and 27%, respectively, had hepatitis C virus (HCV) coinfection. The adjusted slopes in BMD among women and men were significantly different at both the femoral neck (women -0.00897 versus men -0.00422 g/cm per year; P < 0.001) and L-spine (women -0.0127 versus men -0.00763 g/cm per year; P < 0.001). Modifiable risks associated with BMD decline included antiretroviral therapy exposure (greater decline with tenofovir disoproxil fumarate and less decline with integrase strand transfer inhibitor therapy), HCV, physical activity, and vitamin D insufficiency. CONCLUSIONS: Among HIV-infected individuals, bone density at the femoral neck, a significant predictor of fracture risk, declined twice as quickly among women compared with men. Female sex was independently associated with both lower femoral neck and lumbar BMD over time in adjusted models.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".