Systematic Review and Meta-analysis: Optimal Salvage Therapy in Acute Severe Ulcerative Colitis
Bibliographic record
Abstract
BACKGROUND: Infliximab is an effective salvage therapy in acute severe ulcerative colitis; however, the optimal dosing strategy is unknown. We performed a systematic review and meta-analysis to examine the impact of infliximab dosage and intensification on colectomy-free survival in acute severe ulcerative colitis. METHODS: Studies reporting outcomes of hospitalized steroid-refractory acute severe ulcerative colitis treated with infliximab salvage were identified. Infliximab use was categorized by dose, dose number, and schedule. The primary outcome was colectomy-free survival at 3 months. Pooled proportions and odds ratios with 95% confidence intervals were reported. RESULTS: Forty-one cohorts (n = 2158 cases) were included. Overall colectomy-free survival with infliximab salvage was 79.7% (95% confidence interval [CI], 75.48% to 83.6%) at 3 months and 69.8% (95% CI, 65.7% to 73.7%) at 12 months. Colectomy-free survival at 3 months was superior with 5-mg/kg multiple (≥2) doses compared with single-dose induction (odds ratio [OR], 4.24; 95% CI, 2.44 to 7.36; P < 0.001). However, dose intensification with either high-dose or accelerated strategies was not significantly different to 5-mg/kg standard induction at 3 months (OR, 0.70; 95% CI, 0.39 to 1.27; P = 0.24) despite being utilized in patients with a significantly higher mean C-reactive protein and lower albumin levels. CONCLUSIONS: In acute severe ulcerative colitis, multiple 5-mg/kg infliximab doses are superior to single-dose salvage. Dose-intensified induction outcomes were not significantly different compared to standard induction and were more often used in patients with increased disease severity, which may have confounded the results. This meta-analysis highlights the marked variability in the management of infliximab salvage therapy and the need for further studies to determine the optimal dose strategy.
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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 | 0.013 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.036 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".