Bone microarchitecture declines in older men with impaired renal function—the prospective STRAMBO study
Bibliographic record
Abstract
CKD may be complicated by mineral and bone disorders (CKD-MBD). Data on the association between estimated glomerular filtration rate (eGFR) and bone microarchitecture are limited. We studied the link between eGFR and bone microarchitecture (baseline, changes) assessed by HR-pQCT in older men followed for 8 yr. In 826 men aged ≥60, eGFR was calculated using 3 equations based on creatinin and cystatin C: CKDEPI-2012, EKFC without race and sex, and CKDEPI-2021 without race. Bone microarchitecture was assessed at the distal radius and distal tibia by HR-pQCT at baseline, then after 4 and 8 yr. Reaction force and failure load were estimated by microfinite element analysis. Changes in bone measures across the eGFR classes were explored using linear mixed effect models. At baseline, distal radius bone microarchitecture did not differ across the eGFR groups (CKDEPI-2012), whereas distal tibia trabecular measures and failure load were higher in men with decreased eGFR. During the follow-up, lower eGFR was associated with a more rapid decrease in total BMD (Tt.BMD), cortical area (Ct.Ar) and BMD (Ct.BMD), trabecular BMD (Tb.BMD), and failure load at the distal radius. Low eGFR was also associated with a faster increase in trabecular area (Tb.Ar) and trabecular distribution heterogeneity (Tb.1/N.SD). At the distal tibia, low eGFR was associated with a more rapid decrease in Tt.BMD, Ct.Ar, Ct.BMD, Tb.1/N.SD, and failure load as well as with a faster increase in Tb.Ar. The patterns were similar for changes expressed as percentages. The patterns were similar for 2 other equations. Lower eGFR is associated with a faster decline in cortical bone microarchitecture and bone strength at the distal radius and tibia in older men. This phenomenon may contribute to the higher fracture risk in older adults with 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".