The effect of preoperative Infliximab therapy in Crohnʼs patients on post-operative complications: A meta-analysis
Bibliographic record
Abstract
The impact of preoperative infliximab on post-operative complicatons in patients with Crohns disease is controversial. We conducted a systematic review and meta-analysis of studies comparing rates of post-operative complications among Crohn's disease patients treated with Infliximab therapy versus alternative therapies. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and searched 4 electronic databases along with major conference abstract databases (from inception of database until May, 2011) for all English-language articles and abstracts that evaluated post-operative complications among Crohn's disease patients. We applied meta-analysis with random effects model to calculate the overall odds ratio and its 95% confidence interval for total major complications as well as several secondary outcomes. Data were extracted from seven studies including 1226 patients among whom 464 complications were identified. The most common complications were wound infections, anastomotic leak and sepsis. The total major complication rate was significantly elevated among patients treated with Infliximab (Odds Ratio = 1.74 [95% Confidence Interval: 1.06 - 2.86]; p = 0.03). However, when minor complication rates, reoperation and 30 day mortality were considered, there was not a significant difference between the Infliximab treated group and the control group. The use of Infliximab during the preoperative period is associated with higher rates of major post-operative complications but not minor complications, reoperation or 30 day mortality rates. Forrest plot showing the random effects meta-analysis of total major* complications. *Major complications were defined as sepsis, anastomotic leak, peritonitis, local fistula or abscess, wound infection, wound failure, stoma complications, bowel perforation severe anemia and hemorrhage
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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 | 0.012 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.042 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".