The impact of preoperative steroid use on short-term outcomes following surgery for inflammatory bowel disease
Bibliographic record
Abstract
BACKGROUND: Inflammatory bowel disease (IBD) patients are frequently treated with steroids prior to surgery. We characterized the association between preoperative steroid use and postoperative complications in a large prospective cohort. METHODS: We identified patients who underwent major IBD-related abdominal surgery in the American College of Surgeon's National Surgical Quality Improvement Program (ACS-NSQIP) between 2005 and 2012. We compared the risk of postoperative complications and 30-day mortality between preoperative steroid users and non-users. RESULTS: We identified 8260 Crohn's disease (CD) and 7235 ulcerative colitis (UC) patients who underwent major abdominal surgery. Preoperative steroid use was associated with higher risk of postoperative complications, excluding death, in both CD (22.6% vs. 18.5%, P<0.0001) and UC (30.1% vs. 22.5%, P<0.0001). The adjusted odds ratio for any postoperative complication associated with steroids was 1.26 (95% CI: 1.12-1.41) for CD and 1.44 (95% CI: 1.28-1.61) for UC. Infectious complications were more frequent with steroid use in both CD (15.2% vs. 12.9%, P=0.004) and UC (19.4% vs. 15.6%, P<0.0001), specifically intra-abdominal infections and sepsis. Steroid use was associated with increased risk of venous thromboembolism (VTE) in both CD (OR, 1.66; 95% CI: 1.17-2.35) and UC (OR, 2.66; 95% CI: 2.01-3.53). 30-day mortality did not differ among steroid users and non-users (6.8/1000 vs. 5.8/1000, P=0.58 for CD; 13.5/1000 vs. 15.2/1000, P=0.55 for UC). CONCLUSIONS: Preoperative steroids are associated with higher risk of postoperative sepsis and VTE in IBD. Increased infectious control measures and VTE prophylaxis may reduce adverse events.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| 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) | 0.001 | 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".