The Use of Infliximab for Treatment of Hospitalized Patients with Acute Severe Ulcerative Colitis
Bibliographic record
Abstract
BACKGROUND/AIM: The use of infliximab in severe ulcerative colitis (UC) is established; however, its role in severe acute UC requires clarification. The present multicentre case series evaluated infliximab in hospitalized patients with steroid-refractory severe UC. METHODS: Patients from six hospitals were retrospectively evaluated. Data collection included demographics, duration of disease and previous treatments. The primary end point was response to in-hospital infliximab; defined as discharge without colectomy. RESULTS: Twenty-one patients (median age 26 years) were admitted between May 2006 and May 2008 with severe UC requiring intravenous steroids and given infliximab (median time to infusion eight days). Sixteen (76%) patients were discharged home without colectomy; three of these underwent colectomy at a later date. Of the remaining 13 patients (62%), all but two did not require further courses of steroids; six patients had infliximab as a bridge to azathioprine and seven patients were maintained on regular infliximab. Five patients required in-hospital colectomy after the initial infliximab. CONCLUSIONS: In this real-life experience of infliximab in patients with steroid-refractory severe UC, infliximab appears to be a viable rescue therapy. The majority of patients were discharged without surgery and 62% maintained response either as a bridge to azathioprine or maintenance infliximab.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".