EUROPEAN GUIDELINE FOR THE DIAGNOSIS AND THERAPY OF PANCREATIC EXOCRINE INSUFFICIENCY: UEG, EPC, EDS, ESPGHAN, ESDO, AND ESPCG EVIDENCE-BASED STATEMENTS
Bibliographic record
Abstract
Pancreatic exocrine insufficiency (PEI) is defined as a reduction in pancreatic exocrine secretion below a level that allows normal digestion of nutrients. Pancreatic disease and pancreatic surgery are the main causes of PEI, but other conditions and upper gastrointestinal surgery can affect the digestive function of the pancreas. PEI can cause symptoms of nutrient malabsorption and nutritional deficiencies, which affect quality of life and increase morbidity and mortality. There is no test allowing for the diagnosis of PEI. Diagnosis should therefore be based on a global assessment of symptoms, nutritional status and a pancreatic secretion test (e.g. faecal elastase). Pancreatic enzyme replacement therapy, together with dietary advice and support, are the cornerstones of PEI therapy. The diagnosis and treatment of PEI varies widely between countries and centres, and there is considerable discrepancies as to whom and how to diagnose and treat. Following the UEG framework for the development of high-quality clinical guidelines, the European multidisciplinary guideline on the diagnosis and treatment of PEI has been developed. This evidence-based guideline summarises the prevalence, clinical impact and general diagnostic and therapeutic approach to PEI, as well as the specifics of PEI in different clinical conditions. Finally, unmet needs for future research are discussed.
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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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".