Pancreatin therapy in patients with insulin‐treated diabetes mellitus and exocrine pancreatic insufficiency according to low fecal elastase 1 concentrations. Results of a prospective multi‐centre trial
Bibliographic record
Abstract
BACKGROUND: Recently, high prevalence of exocrine dysfunction in diabetic populations has been reported. Patients with fecal elastase 1 concentration (FEC) <100 microg/g have also been demonstrated to suffer from steatorrhea in about 60% of cases, indicating the need of pancreatic enzyme replacement therapy. Until now, there have only been a few reports on the use of enzyme replacement therapy in diabetic patients with exocrine pancreatic insufficiency. This investigation was designed to evaluate the impact of enzyme-replacement therapy on glucose metabolism and diabetes treatment in a prospective study of insulin-treated patients with diabetes mellitus. METHODS: A total of 546 patients with diabetes mellitus requiring insulin treatment were screened for exocrine dysfunction by FEC measurements. One hundred and fifteen patients (21.1%) had FEC <100 microg/g (normal >200 microg/g). Of these, 95 patients entered the study and 80 patients were randomized to receive either pancreatin (Creon) (39 patients) or placebo (41 patients) in a double-blind manner. Parameters of glucose metabolism, diabetes therapy and clinical symptoms were recorded in standardized protocols for 16 weeks. RESULTS: During the observation phase of 16 weeks, there were no significant differences between both groups concerning HbA(1c), fasting glucose levels, 2-h pp glucose levels, clinical parameters and safety parameters. A reduction in mild and moderate hypoglycemia was observed in the pancreatin group at the end of the study. CONCLUSIONS: Pancreatin therapy can be used safely in patients with diabetes mellitus and exocrine dysfunction. Parameters of glucose metabolism were not improved by enzyme replacement therapy.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".