Frequency of Bone Mineral Density Testing in Adult Kidney Transplant Recipients from Ontario, Canada: A Population-Based Cohort Study
Bibliographic record
Abstract
BACKGROUND: We lack consensus on the clinical value, frequency, and timing of bone mineral density (BMD) testing in kidney transplant recipients. This study sought to determine practice patterns in BMD testing across kidney transplant centres in Ontario, Canada, and to compare the frequency of testing in kidney transplant recipients to non-transplant reference groups. METHODS: Using healthcare databases from Ontario, Canada we conducted a population-based cohort study of adult kidney transplant recipients who received a transplant from 1994-2009. We used logistic regression to determine if there was a statistically significant difference across transplant centres in the decision to perform at least one BMD test after transplantation, adjusting for covariates that may influence a physician's decision to order a BMD test. We used the McNemar's test to compare the number of recipients who had at least one BMD test to non-transplant reference groups (matching on age, sex, and date of cohort entry). RESULTS: In the first 3 years after transplant, 4821 kidney transplant recipients underwent 4802 BMD tests (median 1 test per recipient, range 0 to 6 tests), costing $600,000 (2014 CAD equivalent dollars). Across the six centres, the proportion of recipients receiving at least one BMD test varied widely (ranging from 15.6 to 92.1 %; P < 0.001). Over half (58 %) of the recipients received at least one BMD test post-transplant, a value higher than two non-transplant reference groups (general population with a previous non-vertebral fracture [hip, forearm, proximal humerus], 13.8 %; general population with no previous non-vertebral fracture, 8.5 %; P value <0.001 for each of the comparisons). CONCLUSIONS: There is substantial practice variability in BMD testing after transplant. New high-quality information is needed to inform the utility, optimal timing, and frequency of BMD testing in kidney transplant recipients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".