A systematic review and meta-analysis of the effects of infliximab on the rate of colectomy and post-operative complications in patients with inflammatory bowel disease
Bibliographic record
Abstract
INTRODUCTION: Use of biological therapies may reduce or delay the surgical procedures in patients with inflammatory bowel disease (IBD). The aim of this meta-analysis and systematic review was to determine the impact of pre-operative infliximab (IFX) use on the rate of surgical interventions in patients with IBD and also the effect of preoperative IFX therapy on post-surgical complications. MATERIAL AND METHODS: Literature was searched for studies that investigated the efficacy of IFX on the rate of colectomy and post-operative complications/side effects in patients with IBD between 1966 and February 2011. RESULTS: Twelve articles were included in the meta-analysis. In comparison to control groups, patients who received IFX had a relative risk (RR) of 1.17 (p = 0.65) for the rate of colectomy, odds ratio of 3.34 (p = 0.09) in seven observational studies and RR of 0.74 (p = 0.79) in clinical trials for mortality. Summary RR of hospitalization was 0.61 (p = 0.005). Infections and anastomotic leak, pouch-related complications, sepsis and thrombotic events were more common in the patients under IFX therapy but post-operational hospitalization was lower. The patients with IBD who were under IFX therapy were most of the times refractive to other therapies and their disease was more severe. CONCLUSIONS: Although IFX does not decrease the rate of colectomy in patients with IBD, it would not increase most of the post-operational side effects in the patients.
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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 | 0.015 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.041 |
| Bibliometrics | 0.008 | 0.008 |
| 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".