The Safety and Tolerability of Methotrexate for Treating Patients With Crohn's Disease
Bibliographic record
Abstract
GOALS: To determine the safety and tolerance of methotrexate for treating patients with Crohn's disease in clinical practice. BACKGROUND: Methotrexate is effective for treating patients with Crohn's disease. However, concerns about potential toxicity, particularly to the liver, have limited its use. STUDY: A retrospective chart review was performed of Crohn's disease patients in our practice treated with methotrexate. Data related to the safety and tolerance of methotrexate was extracted and analyzed. RESULTS: Of 92 patients treated with methotrexate, there was enough data for 79 patients for analysis (49 women and 30 men; mean age 28.8 y). Forty-two patients (53%) had previously received azathioprine. Overall, 40 patients (51%) achieved and maintained remission on methotrexate, including 13 of 30 (43%) who concomitantly received anti-tumor necrosis factor therapy. The mean total accumulated dose of methotrexate was 1727 mg [SD 1572 mg], with a mean total duration of methotrexate use of 25.4 months (SD 43.1 mo). The most common adverse events were nausea (22%) and elevated liver enzymes (10%). Only 6% of patients stopped methotrexate therapy because of persistently abnormal liver enzymes. No patients underwent liver biopsy. CONCLUSIONS: This retrospective study showed that methotrexate is safe and well-tolerated in treating patients with Crohn's disease in clinical practice.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".