Risedronate improves bone mineral density in Crohn's disease: A two year randomized controlled clinical trial
Bibliographic record
Abstract
BACKGROUND: Patients with Crohn's disease have an increased frequency of osteopenia and osteoporosis. This randomized, controlled, double-blind study assessed the efficacy of risedronate versus placebo in treating low bone mineral density (BMD) in patients with Crohn's disease. METHODS: 88 Crohn's disease outpatients with BMD T-score<-1.0 by dual-energy X-ray absorptiometry were randomly assigned to one of two treatment groups for the two year study duration: one group received risedronate 35 mg weekly while another received placebo. Both groups received daily calcium (Ca; 500 mg) and vitamin D (D; 400 IU) supplementation. Percent change in BMD relative to baseline was compared between the two therapies at 12 and 24 months. RESULTS: Using intent-to-treat analysis, at 12 months, risedronate+Ca+D increased BMD, relative to baseline, more than placebo+Ca+D in the femoral trochanter (1.4±3.4% vs -0.1±3.1%; p=0.03) and total hip (1.1±2.7% vs -0.1±2.5%;p=0.04). This trend in greater BMD continued for the 24 month duration of the study. There was no difference between the two treatment groups for changes in spine BMD. Subgroup analysis revealed that risedronate+Ca+D resulted in significantly better improvement in femoral trochanter BMD in non-smokers (p=0.01), males (p=0.01), those with a history of corticosteroid use in the preceding year (p=0.01), and current users of immunosuppressants (p=0.04). CONCLUSIONS: Risedronate, in addition to daily calcium and vitamin D supplementation, is superior to calcium and vitamin D alone in improving femoral trochanter and total hip BMD in patients with Crohn's disease.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".