FRAX Predicts Fracture Risk in Kidney Transplant Recipients
Bibliographic record
Abstract
BACKGROUND: The World Health Organization Fracture Risk Assessment Tool (FRAX) estimates the 10-year fracture probability. We assessed the prognostic value of FRAX in kidney transplant recipients, as its utility in recipients is unknown. METHODS: We considered 458 individuals (mean age 45 years, 64% men) who received a kidney transplant in the province of Manitoba, Canada at the time of their first bone mineral density (BMD) test posttransplant (mean 1.1 years posttransplant; transplant years 1996-2011). FRAX probabilities were calculated from baseline information (age, sex, clinical risk factors, with or without BMD). Recipients were followed a mean of 6.4 years (interquartile range 3.0-10.0 years) after cohort entry for an incident major osteoporotic fracture. RESULTS: In follow-up, 21 (4.6%) recipients experienced a major osteoporotic fracture. The observed 10-year major osteoporotic fracture risk of 6.3% (95% CI, 3.4-9.2%) was concordant with FRAX predictions (5.0% with BMD, 5.6% without BMD). Major osteoporotic fracture scores showed significant fracture prediction (hazard ratio per standard deviation, FRAX without BMD 1.66, 95% CI, 1.10-2.50; FRAX with BMD 1.64, 95% CI, 1.07-2.51). Area under the curve (AUC) for incident major osteoporotic fracture discrimination (AUC: FRAX with BMD 0.62, 95% CI, 0.50-0.74) was similar to the general population. CONCLUSIONS: FRAX scores categorized most kidney transplant recipients as a low-risk fracture group, and the low observed fracture rates were consistent with the 10-year fracture predictions. FRAX showed modest fracture prediction and discrimination similar to the general population. Independent validation is needed before clinicians can routinely use FRAX in kidney transplant recipients.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".