Long-term Emergency Department Visits and Readmissions After Laparoscopic Roux-en-Y Gastric Bypass: a Systematic Review
Bibliographic record
Abstract
PURPOSE: There is considerable evidence on short-term outcomes after laparoscopic Roux-en-Y gastric bypass (LRYGB), but data on long-term outcome is scarce, especially on postoperative emergency department (ED) visits and readmissions. We aim to systematically review evidence on the incidence, indications, and risk factors of ED visits and readmissions beyond 30 days after LRYGB. MATERIALS AND METHODS: A systematic search in PubMed, Scopus, Embase.com , Cochrane Library, and PsycINFO was performed. All studies reporting ED visits and readmissions > 30 days after LRYGB, with ≥ 50 patients, were included. PRISMA statement was used and the Newcastle-Ottawa Scale for quality assessment. RESULTS: Twenty articles were included. Six studies reported on ED visits (n = 2818) and 19 on readmissions (n = 276,543). The rate of patients with an ED visit within 90 days after surgery ranged from 3.9 to 32.6%. ED visits at 1, 2, and 3 years occurred in 25.6%, 30.0%, and 31.1% of patients. Readmissions within 90 days and at 1-year follow-up ranged from 4.1 to 20.5% and 4.75 to 16.6%, respectively. Readmission was 29% at 2 years and 23.9% at 4.2 years of follow-up. The most common reason for ED visits and readmissions was abdominal pain. CONCLUSION: Emergency department visits and readmissions have been reported in up to almost one in three patients on the long-term after LRYGB. Both are mainly indicated for abdominal pain. The report on indications and risk factors is very concise. A better understanding of ED visits and readmissions after LRYGB is warranted to improve long-term care, in particular for patients with abdominal pains.
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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 | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".