Guidelines for treatment of umbilical and epigastric hernias from the European Hernia Society and Americas Hernia Society
Bibliographic record
Abstract
BACKGROUND: Umbilical and epigastric hernia repairs are frequently performed surgical procedures with an expected low complication rate. Nevertheless, the optimal method of repair with best short- and long-term outcomes remains debatable. The aim was to develop guidelines for the treatment of umbilical and epigastric hernias. METHODS: The guideline group consisted of surgeons from Europe and North America including members from the European Hernia Society and the Americas Hernia Society. The Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach, the Scottish Intercollegiate Guidelines Network (SIGN) critical appraisal checklists, and the Appraisal of Guidelines for Research and Evaluation (AGREE) instrument were used. A systematic literature search was done on 1 May 2018, and updated on 1 February 2019. RESULTS: Literature reporting specifically on umbilical and epigastric hernias was limited in quantity and quality, resulting in a majority of the recommendations being graded as weak, based on low-quality evidence. The main recommendation was to use mesh for repair of umbilical and epigastric hernias to reduce the recurrence rate. Most umbilical and epigastric hernias may be repaired by an open approach with a preperitoneal flat mesh. A laparoscopic approach may be considered if the hernia defect is large, or if the patient has an increased risk of wound morbidity. CONCLUSION: This is the first European and American guideline on the treatment of umbilical and epigastric hernias. It is recommended that symptomatic umbilical and epigastric hernias are repaired by an open approach with a preperitoneal flat mesh.
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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 | 0.008 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.007 |
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".