EHS and AHS guidelines for treatment of primary ventral hernias in rare locations or special circumstances
Bibliographic record
Abstract
BACKGROUND: Rare locations of hernias, as well as primary ventral hernias under certain circumstances (cirrhosis, dialysis, rectus diastasis, subsequent pregnancy), might be technically challenging. The aim was to identify situations where the treatment strategy might deviate from routine management. METHODS: The guideline group consisted of surgeons from the European and Americas Hernia Societies. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach was used in formulating the recommendations. The Scottish Intercollegiate Guidelines Network (SIGN) critical appraisal checklists were used to evaluate the quality of full-text papers. A systematic literature search was performed on 1 May 2018 and updated 1 February 2019. The Appraisal of Guidelines for Research and Evaluation (AGREE) instrument was followed. RESULTS: Literature was limited in quantity and quality. A majority of the recommendations were graded as weak, based on low quality of evidence. In patients with cirrhosis or on dialysis, a preperitoneal mesh repair is suggested. Subsequent pregnancy is a risk factor for recurrence. Repair should be postponed until after the last pregnancy. For patients with a concomitant rectus diastasis or those with a Spigelian or lumbar hernia, no recommendation could be made for treatment strategy owing to lack of evidence. CONCLUSION: This is the first European and American guideline on the treatment of umbilical and epigastric hernias in patients with special conditions, including Spigelian and lumbar hernias. All recommendations were weak owing to a lack of evidence. Further studies are needed on patients with rectus diastasis, Spigelian and lumbar hernias.
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 | 0.019 | 0.095 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.011 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".