TREATMENT OF ESTABLISHED BONE LOSS AFTER RENAL TRANSPLANTATION WITH ETIDRONATE1
Bibliographic record
Abstract
BACKGROUND: Osteoporosis is a well-documented complication of organ transplantation. Bisphosphonates have been shown to be effective in preventing corticosteroid-induced osteoporosis in renal transplant recipients, but data are lacking for treatment of established osteoporosis. This study reports our clinical experience of treatment with the bisphosphonate etidronate in a single renal transplant center. METHODS: To establish the effectiveness of etidronate in treating established low bone mineral density (BMD), all newly transplanted patients treated with etidronate were compared with controls. Twenty-five patients treated with etidronate (14 males, 11 females) and 24 controls (15 males, 9 females) were identified from the cohort of patients who underwent transplantation between January 1, 1994, and December 31, 1996. RESULTS: There was no difference in mean age, weight, or cumulative dose of corticosteroids between the treatment and control groups. The baseline BMD measurement was performed at 10.4 +/- 5.3 months after transplantation for treated patients and at 10.7 +/- 4.5 months for controls (P=0.78). Over the subsequent 1-year study period, patients treated with etidronate demonstrated a greater increase in BMD at sites with a preponderance of trabecular bone. Lumbar spine BMD increased 4.3 +/- 6.1% in the treatment group versus 0.55 +/ -5.3% in controls (P<0.03) and trochanter BMD increased 10.3 +/- 11.9% and 2.2 +/- 5.7%, respectively, in the treatment and control groups (P<0.02). CONCLUSIONS: This study establishes the effectiveness of etidronate for treatment of low BMD in renal transplant recipients. Patients selected for treatment had lower baseline BMD than control subjects, yet still showed a clinically important increase in BMD.
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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 | 0.000 |
| 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 | 0.001 |
| 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 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".