Causal Evaluation of Acute Recurrent and Chronic Pancreatitis in Children
Bibliographic record
Abstract
OBJECTIVES: Acute recurrent pancreatitis (ARP) and chronic pancreatitis (CP) have been diagnosed in children at increasing rates during the past decade. As pediatric ARP and CP are still relatively rare conditions, little quality evidence is available on which to base the diagnosis and determination of etiology. The aim of the study was to review the current state of the literature regarding the etiology of these disorders and to developed a consensus among a panel of clinically active specialists caring for children with these disorders to help guide the diagnostic evaluation and identify areas most in need of future research. METHODS: A systematic review of the literature was performed and scored for quality, followed by consensus statements developed and scored by each individual in the group for level of agreement and strength of the supporting data using a modified Delphi method. Scores were analyzed for the level of consensus achieved by the group. RESULTS: The panel reached consensus on 27 statements covering the definitions of pediatric ARP and CP, evaluation for potential etiologies of these disorders, and long-term monitoring. Statements for which the group reached consensus to make no recommendation or could not reach consensus are discussed. CONCLUSIONS: This consensus helps define the minimal diagnostic evaluation and monitoring of children with ARP and CP. Even in areas in which we reached consensus, the quality of the evidence is weak, highlighting the need for further research. Improved understanding of the underlying cause will facilitate treatment development and targeting.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".