Determination of Bone Architecture and Strength in Men and Women with Stage 5 Chronic Kidney Disease
Bibliographic record
Abstract
Fractures are common in men and women with dialysis-dependent chronic kidney disease (stage 5D CKD) and are associated with substantial morbidity and mortality. The clinical utility of dual energy X-ray absorptiometry (DXA) and peripheral quantitative computed tomography (pQCT), noninvasive measures of bone mass and architecture that reflect fracture risk in healthy men and women, is uncertain in patients with stage 5D CKD. This review will outline the epidemiology and etiology of fractures and will summarize the published data that describe the association between fractures, bone mass, and bone strength in stage 5D CKD. Fracture risk assessment in stage 5D CKD is complicated as the etiology of fractures is multifactorial and includes impairments in bone quantity and quality. Cross-sectional data suggest that bone density by DXA is lower among stage 5D CKD patients with fractures compared with those without, and that this may be particularly true at cortical sites. However, DXA does not capture bone microarchitecture and cannot differentiate between cortical and trabecular bone. Some, but not all studies, that measure cortical and trabecular bone by pQCT in stage 5D CKD, demonstrate a preferential decrease in cortical bone; however, these studies are limited by small sample sizes and cross-sectional study design. No studies have reported on longitudinal relationships between bone architecture, strength, and incident fractures in patients with stage 5D CKD. Further research is needed to identify noninvasive measures of bone strength that can be used for fracture risk assessment in stage 5D CKD.
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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) | 0.003 | 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".