Postoperative outcomes after preoperative ustekinumab exposure in patients with Crohn’s disease: a systematic review and meta-analysis
Bibliographic record
Abstract
BackgroundRecent studies have reported conflicting data on the risk of postoperative complications in patients with Crohn's disease (CD) exposed to ustekinumab (UST) preoperatively.We performed a systematic review and meta-analysis to better assess and quantify the risk of postoperative complications in this population undergoing major abdomino-pelvic surgery.Methods We conducted a comprehensive search of multiple electronic databases and conference proceedings (earliest inception through October 2020) to identify studies that reported the postoperative outcomes in CD patients with preoperative UST exposure.We estimated and compared the pooled rates of postoperative complications, including intra-abdominal sepsis, surgical site infection, any infection, any adverse event, readmission, and reoperation. ResultsA total of 5 studies were included in the analysis.The last dose of the drug was at most 16 weeks prior to abdomino-pelvic surgery.A total of 172 CD patients (61% female; median age 35 years) were included.The pooled rate of any complication and any infectious complications was 23.5% (95% confidence interval [CI] 16-33.1)and 20.2% (95%CI 10.3-35), respectively.There was no difference in rates of intra-abdominal sepsis between the UST group (7.2%, 95%CI 3-16.4) and the anti-tumor necrosis factor (TNF) group (11.9%, 95%CI 5.9-22.5;P = 0.4).The rates of readmission and reoperation in the UST group were 17.4% (95%CI 7.9-34) and 14.6% (95%CI 9-22.7),respectively. ConclusionsThe postoperative complication rate in patients with preoperative UST exposure may be similar to that for anti-TNF medication.Preoperative exposure to UST does influence postoperative complication risk.Future prospective studies are needed to validate these findings.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.020 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".