How to predict and treat increased fracture risk in chronic kidney disease
Bibliographic record
Abstract
Men and women with chronic kidney disease (CKD) are at an increased risk of fracture, and this risk increases as kidney function deteriorates. Fractures are associated with morbidity, mortality and economic costs. Despite this, there is a paucity of data regarding how to evaluate risk for fractures in CKD and how to treat high-risk patients. Evidence suggests that bone mineral density (BMD) as assessed by dual-energy X-ray absorptiometry (DXA) is associated with fractures and can also predict future fractures in predialysis (stages 1-3) patients with CKD. In the absence of considerable abnormalities in markers of mineral metabolism, treatment with antiresorptive agents in men and women with early CKD at high fracture risk may be appropriate. Of note, recent data suggest that low BMD as measured by DXA can also predict fractures in patients with more advanced CKD (stages 4, 5 and 5D). However, treatment in patients with advanced CKD requires bone biopsy, the gold standard to assess bone turnover, prior to treatment. Further research, focusing on noninvasive methods to assess fracture risk and bone turnover, together with randomized controlled trials of treatments to reduce fractures in patients at all stages of CKD, is required.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 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".