Preoperative Anti–tumor Necrosis Factor Therapy in Patients with Ulcerative Colitis Is Not Associated with an Increased Risk of Infectious and Noninfectious Complications After Ileal Pouch–anal Anastomosis
Bibliographic record
Abstract
BACKGROUND: There are conflicting data regarding the effect of previous exposure to anti-tumor necrosis factor (anti-TNF) therapy on complication rates after pelvic pouch surgery for patients with ulcerative colitis (UC). In particular, there is concern surrounding the rates of pouch leaks and infectious complications, including pelvic abscesses, in anti-TNF-treated subjects who require ileal pouch-anal anastomosis (IPAA) surgery. METHODS: A retrospective study was performed in UC subjects who underwent IPAA between 2002 and 2013. Demographic data, clinical data, use of anti-TNF therapy, steroids, immunosuppressants, and surgical outcomes were assessed. RESULTS: Seven hundred seventy-three patients with UC/IPAA were reviewed. Fifteen patients were excluded from the analysis because of missing data. There were 196 patients who were exposed to anti-TNF therapy and 562 patients who were not exposed to anti-TNF therapy preoperatively. There were no significant differences in the postoperative IPAA leak rate between those exposed to anti-TNF therapy and the control group (n = 26 [13.2%] versus 66 [11.7%], respectively, P = 0.44). In addition, there were no significant differences in the postoperative 2-stage IPAA leak rate in those who had been operated on within 15 days from the last anti-TNF dose (n = 10), within 15 to 30 days (n = 17), or 31 to 180 days (n = 54) (10%, 5.9%, and 14.8% respectively, P = 0.43) nor were there differences based on the presence of detectable infliximab serum levels. CONCLUSIONS: Preoperative anti-TNF therapy in patients with UC is not associated with an increased risk of infectious and noninfectious complications after IPAA including pelvic abscesses, leaks, and wound infections.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".