UEG and EAES rapid guideline: Update systematic review, network meta‐analysis, CINeMA and GRADE assessment, and evidence‐informed European recommendations on surgical management of GERD
Bibliographic record
Abstract
BACKGROUND: There are several options for the surgical management of GERD in adults. Previous guidelines and systematic reviews have compared the effects of total fundoplication versus pooled effects of different techniques of partial fundoplication. OBJECTIVE: To develop evidence-informed, trustworthy, pertinent recommendations on the use of total, posterior partial and anterior partial fundoplications for the management of GERD in adults. METHODS: We performed an update systematic review, network meta-analysis, and evidence appraisal using the GRADE and the Confidence in Network Meta-Analysis methodologies. An international, multidisciplinary panel of surgeons, gastroenterologists, and a patient representative reached unanimous consensus through an evidence-to-decision framework to select among multiple interventions, and a Delphi process to formulate the recommendation. The project was developed in an online authoring and publication platform (MAGICapp), and was overseen by an external auditor. RESULTS: We suggest posterior partial fundoplication over total posterior or anterior 90° fundoplication in adult patients with GERD. We suggest anterior >90° fundoplication as an alternative, although relevant comparative evidence is limited (weak recommendation). The guideline, with recommendations, evidence summaries and decision aids in user friendly formats can also be accessed in MAGICapp: https://app.magicapp.org/#/guideline/j20X4n. CONCLUSION: This rapid guideline was developed in line with highest methodological standards and provides evidence-informed recommendations on the surgical management of GERD. It provides user-friendly decision aids to inform healthcare professionals' and patients' decision making.
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 | 0.045 | 0.131 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.010 | 0.020 |
| Bibliometrics | 0.014 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.011 | 0.006 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.014 | 0.008 |
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".