The Roles of Endoscopic Ultrasound and Endoscopic Retrograde Cholangiopancreatography in the Evaluation and Treatment of Chronic Pancreatitis in Children
Bibliographic record
Abstract
INTRODUCTION: Pediatric chronic pancreatitis is increasingly diagnosed. Endoscopic methods [endoscopic ultrasound (EUS), endoscopic retrograde cholangiopancreatography (ERCP)] are useful tools to diagnose and manage chronic pancreatitis. Pediatric knowledge and use of these modalities is limited and warrants dissemination. METHODS: Literature review of publications relating to use of ERCP and EUS for diagnosis and/or management of chronic pancreatitis with special attention to studies involving 0--18 years old subjects was conducted with summaries generated. Recommendations were developed and voted upon by authors. RESULTS: Both EUS and ERCP can be used even in small children to assist in diagnosis of chronic pancreatitis in cases where cross-sectional imaging is not sufficient to diagnose or characterize the disease. Children under 15 kg for EUS and 10 kg for ERCP can be technically challenging. These procedures should be done optimally by appropriately trained endoscopists and adult gastroenterology providers with appropriate experience treating children. EUS and ERCP-related risks both include perforation, bleeding and pancreatitis. EUS is the preferred diagnostic modality over ERCP because of lower complication rates overall. Both modalities can be used for management of chronic pancreatitis -related fluid collections. ERCP has successfully been used to manage pancreatic duct stones. CONCLUSION: EUS and ERCP can be safely used to diagnose chronic pancreatitis in pediatric patients and assist in management of chronic pancreatitis-related complications. Procedure-related risks are similar to those seen in adults, with EUS having a safer risk profile overall. The recent increase in pediatric-trained specialists will improve access of these modalities for children.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".