Recurrence of Small Bowel Obstruction in Adults After Operative Management of Adhesive Small Bowel Obstruction: A Systematic Review
Bibliographic record
Abstract
The objective of this article is to review the existing literature on postoperative recurrence of adhesive small bowel obstruction (ASBO). We performed a systematic review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, searching PubMed, Cochrane Library, and Google Scholar, to identify randomized controlled trials (RCTs) and observational studies investigating recurrence after operative management of ASBO. Our search yielded one RCT, one prospective study, and eight retrospective studies, totaling 36,178 patients. We used Cochrane risk-of-bias tool and the Newcastle-Ottawa scale to assess the risk of bias in the reviewed studies (RCTs and observational studies, respectively). Operative management was associated with a lower risk of recurrence than conservative management, while the difference in recurrence between laparoscopic and open surgery was inconclusive. Diffuse adhesions were associated with a greater risk of recurrence than single band adhesions. We conclude that the "common knowledge" that surgery increases the risk for recurrence of ASBO is outdated and should no longer be applied when determining treatment modalities for ASBO. While conservative treatment still has its place, we need not fear the possibility of shifting patients to operative management earlier.
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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".