Bibliographic record
Abstract
PURPOSE OF REVIEW: Skeletal fractures are more common in HIV, and impact the medical, functional and economic status of frequently vulnerable patients. Identifying asymptomatic patients with low bone mineral density (BMD)/osteoporosis requiring intervention can be expected to reduce fracture risk and complications. Clinical tools are available to determine fracture risk in the general population and are being evaluated in HIV patients. The FRAX calculator, incorporating demographics and risk factors for osteoporosis, with or without BMD results, has been investigated most often in HIV patients. RECENT FINDINGS: The few published studies that have calculated the 10-year FRAX risk for both major osteoporosis and hip fractures without BMD generally show limited precision in predicting the presence of osteoporosis severe enough to initiate treatment. It remains uncertain whether using HIV as a secondary risk factor and adding dual X-ray absorptiometry (DXA)-BMD information improves case-finding compared with using DXA results only. Not incorporating risks relevant to aging HIV patients such as antiretroviral exposure, hepatitis C virus coinfection and history of falls is other potential limitation. SUMMARY: Accurate screening tools using clinical risk factors alone to determine fracture risk in HIV are not yet available. Further research and validation studies are necessary.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".