Adalimumab and postoperative complications of elective intestinal resections in Crohn's disease: a propensity score case‐matched study
Bibliographic record
Abstract
BACKGROUND: data are scarce regarding the effect of preoperative Adalimumab (ADA) in postoperative complications in Crohn's disease (CD) patients. AIM: to compare the rates of postoperative complications after intestinal resections in CD, with and without previous exposure to ADA. METHOD: case-matched retrospective observational study of patients submitted to intestinal resections for CD. The patients were allocated to 2 groups, according to their previous exposure to ADA before surgery. The patients under ADA therapy were matched with controls (patients without previous biologics) with the propensity score method (PSM), according to age at surgery, CD location (Montreal L) and phenotype (Montreal B). Medical and surgical complications were compared. RESULTS: 123 patients were initially considered, 71 with previous biologics (32 under ADA therapy) and 52 without. The PSM selected 25 ADA patients to be matched with 25 controls from the non-biologics group. There was no difference regarding overall surgical complications (40% in the control vs 36% in the ADA group; p = 1.0000) or medical complications (36% vs 12% in the control and ADA groups, respectively; p = 0.095). In univariate analysis, previous ADA was not considered a risk factor for higher postoperative complication rates. Stomas were considered a risk factor for surgical complications, and previous steroids were associated to higher medical complication rates. CONCLUSIONS: preoperative ADA did not influence the rates of medical and surgical complications after elective intestinal resections for CD. This was the first study to include exclusively patients under ADA therapy. This article is protected by copyright. All rights reserved.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".