Durchführung und Interpretation der Ösophagusmanometrie: Empfehlungen der Deutschen Gesellschaften für Neurogastroenterologie und Motilität (DGNM), für Verdauungs- und Stoffwechselerkrankungen (DGVS) und für Allgemein- und Viszeralchirurgie (DGAV)
Bibliographic record
Abstract
Esophageal manometry examines the pressure profiles of the tubular esophagus and of the esophageal sphincters during resting conditions and in response to swallowing. It is regarded as the reference method for detection of esophageal motility disturbances but, up to date, performance of the procedure is not standardized among centers. This review depicts the recommendations of the German Societies for Neurogastroenterology and Motility, for Digestive and Metabolic Disturbances and for General and Visceral Surgery on indications, performance and analysis of conventional esophageal manometry. In addition to concise recommendations we give detailed background information so that the article can serve as a practical guideline for inexperienced investigators as well as an exensive review for the experienced one. Moreover, recommendations on the use of newer and/or supplementary diagnostic techniques, that is long-term and high resolution manometry as well as esophageal impedance measurements are also given.
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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".