A meta-analysis of antimycobacterial therapy for Crohn's disease
Bibliographic record
Abstract
OBJECTIVE: Various therapies have been studied for the treatment of Crohn's disease, including antimycobacterial therapy. Meta-analysis was used to evaluate the effect of antimycobacterial therapy in patients with Crohn's disease. METHODS: Randomized, controlled trials comparing antimycobacterial therapy with placebo were identified. Key outcome data were abstracted and the results were pooled to yield odds ratios for maintenance of remission in treated versus control groups. RESULTS: A total of eight randomized trials were identified. Six trials were fully published and were included in the primary analysis. Two trials used antimycobacterial therapy in combination with corticosteroids to induce remission in patients with active Crohn's disease, followed by maintenance therapy with antimycobacterial agents. In these trials, control patients received corticosteroids to induce remission but no antimycobacterial therapy. Pooling of these trials yielded an odds ratio of maintenance of remission in treatment versus control of 3.37 (95% confidence interval [CI], 1.38-8.24) in favor of antimycobacterial therapy. The remaining four trials used antimycobacterial therapy combined with standard therapy in patients with Crohn's disease. In these trials, control patients received standard therapy alone. Pooling of these trials yielded an odds ratio of maintenance of remission in treatment versus control of 0.69 (95% CI, 0.39-1.21) in favor of standard therapy. CONCLUSIONS: These results suggest that antimycobacterial therapy is effective in maintaining remission in patients with Crohn's disease after a course of corticosteroids combined with antimycobacterial therapy to induce remission. Treatment of Crohn's disease with antimycobacterial therapy does not seem to be effective without a course of corticosteroids to induce remission. Because of the small number of studies included in this meta-analysis, the results should be interpreted with caution.
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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 | 0.021 | 0.038 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.055 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".