RESPONSE TO CORTICOSTEROIDS IN SEVERE ULCERATIVE COLITIS
Bibliographic record
Abstract
15% of UC patients will develop a severe attack, but the rate is higher in children. Colectomy is a life-saving procedure for patients with severe UC who fail medical therapy. Predictors of intravenous corticosteroids (IVCS) failure and outcomes are variably reported. We aimed to systematically review studies that reported the short-term outcome in patients receiving IVCS for severe UC, or reported variables that could predict medical treatment failure. 2 independent investigators performed a systematic literature search for cohort studies and controlled trials published between 1974 and 2006 without language restrictions. A meta-regression was performed to explore the relationship between colectomy rates over time weighted by the inverse variance method. 33 studies met the inclusion criteria: 16 reported the short-term outcome and predictors of therapy failure, 14 reported only outcome and three only predictors. In the pooled analysis, 644 of 2175 patients with severe UC required colectomy (30%, 95% CI 28-31) and 22 died (1%, 95% CI 0.7-1.5). In a meta-regression, colectomy rate did not change in the last 30 years (r = 0.08, P = 0.6). Nine studies reported the use of cyclosporine in the cohort, but the colectomy rate (29%, 95% CI 25-32) did not differ from reports in which cyclosporine was not used (29%, 95% CI 27-32). The pooled reported short-term success rate of cyclosporine was only 51%, lower than previously published. Only 3 small studies evaluated outcome of IVCS in children. Over 20 variables were identified in 19 studies to predict medical therapy failure but only a few were consistently reproduced: disease extent, stool frequency, temperature, heart rate, CRP, albumin, and radiological assessment. The short-term colectomy rate in severe UC has remained stable over the last 30 years, despite the introduction of cyclosporine. Variables that predict outcome of IVCS could aid in the development of guidelines for introduction of rescue therapies in severe UC. Further studies in pediatric UC patients are required.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".