Laparoscopic Surgery for Adhesive Small Bowel Obstruction Is Associated With a Higher Risk of Bowel Injury
Bibliographic record
Abstract
OBJECTIVE: We set out to compare the incidence of bowel repair and/or resection in a large cohort of patients with adhesive small bowel obstruction (SBO) managed operatively. BACKGROUND: Laparoscopic lysis of adhesions for adhesive SBO (aSBO) is becoming more common, yet might increase the risk of bowel injury given the distended and/or potentially compromised small bowel. METHODS: We used administrative discharge data derived from a large geographic region, identifying patients who underwent surgery for their first episode of aSBO during 2005 to 2014. Procedure codes were used to determine the exposure: either an open approach or a laparoscopic approach (including procedures converted to open). The primary outcome was incidence of bowel intervention, defined as intraoperative enterotomy, suture repair of intestine, or bowel resection. We estimated the odds of bowel intervention after adjusting for patient and clinical factors. RESULTS: A total of 8584 patients underwent operation for aSBO. Patients undergoing laparoscopic procedures were younger with fewer comorbid conditions. The rate of laparoscopic approaches increased more than 3-fold during the study period (4.3%-14.3%, P < 0.0001). The incidence of bowel intervention was 53.5% versus 43.4% in laparoscopic versus open procedures (P < 0.0001). After adjustment for potential confounders, the odds of bowel intervention among patients treated laparoscopically versus open was 1.6 (95% confidence interval: 1.4-1.9). CONCLUSIONS: Laparoscopic procedures for aSBO are associated with a greater likelihood of intervention for bowel injury and/or repair. This increase might be due to challenges inherent with laparoscopic approaches in patients with distended small bowel. Surgeons should approach laparoscopic lysis of adhesions with a higher level of awareness and use strategies to mitigate this risk.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".