Treatment of Crohn’s Disease With Infliximab and Subsequent Development of Takayasu’s Arteritis
Bibliographic record
Abstract
A 23-year-old man was diagnosed with Crohn's disease (CD) of the large intestine after colonoscopy revealed longitudinal ulcers, and pathology revealed non-caseating epithelioid cell granulomas and anal fistulas. The CD relapsed, and therefore prednisolone (PSL) and infliximab (IFX) treatment was initiated. The PSL was gradually tapered. Steroid-free remission was maintained with IFX. The patient subsequently developed a high fever and headache, while CD-related symptoms did not worsen. Laboratory data showed white blood cells at 14,200/µL and C-reactive protein at 17.2 mg/dL. Contrast-enhanced computed tomography revealed thoracoabdominal aortitis, and the patient was consequently diagnosed with Takayasu's arteritis (TA). We therefore again initiated PSL treatment that immediately reduced the fever and headache. The PSL dose was again tapered and the administration of IFX was resumed to maintain CD remission. No further episodes of aortitis relapse were noted after restarting IFX, and the CD currently remains in remission. This is a rare case of TA onset during IFX treatment for CD, and, as such, contributes to the limited literature on such cases. More specifically, this case highlights that when patients with CD present with symptoms such as fever or headache, it is necessary to investigate the possibility of vasculitis.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".