Utility and utilization of transabdominal ultrasound in pediatric patients with acute recurrent or chronic pancreatitis
Bibliographic record
Abstract
OBJECTIVES: Transabdominal ultrasound (TAUS) is frequently utilized in pediatric acute pancreatitis, but less is known about its use in acute recurrent (ARP) or chronic pancreatitis (CP). Our aim was to describe TAUS utilization and findings from the largest multicenter cohort of pediatric ARP and CP, the International Study Group of Pediatric Pancreatitis: In Search for a CuRE-2 (INSPPIRE-2). METHODS: Demographic and imaging data from physician questionnaires were obtained for patients with available TAUS data. Utilization and findings were compared between ARP and CP groups. Kappa statistics were used to compare agreement of TAUS to computed tomography (CT), magnetic resonance imaging/cholangiopancreatography (MRI/MRCP), endoscopic ultrasound (EUS), and endoscopic retrograde cholangiopancreatography (ERCP) for CP findings. RESULTS: There were 895 patients (460 ARP, 435 CP) included with 2531 TAUS examinations. Mean number of TAUS per year was similar between CP and ARP patients (0.90 vs. 0.90, p = 0.97). The pancreas was well visualized in 65% of examinations (60% ARP vs. 68% CP, p ≤ 0.001). TAUS and CT demonstrated the most consistent agreement among other modalities with kappa values ranging from 0 to 0.66 with substantial agreement for pancreatic duct irregularities (ĸ = 0.62) and moderate agreement for calcifications (ĸ = 0.57). Agreement between other modalities and TAUS was generally lower and diminished closer to CP diagnosis date. CONCLUSION: This is the largest report of TAUS findings in children with ARP or CP. TAUS has several benefits in the initial or emergent evaluation of ARP including availability and tolerance. The ability of TAUS to screen for progression of disease requires further study.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".