A SIMPLE ULTRASOUND SCORE FOR THE ACCURATE DETECTION AND MONITORING OF PEDIATRIC INFLAMMATORY BOWEL DISEASE
Bibliographic record
Abstract
BACKGROUND: Inflammatory bowel disease (IBD) can lead to long-term, irreversible complications and morbidity in adulthood. Cross-sectional imaging is essential to early diagnosis and optimal disease management. As such, there is a need for a safe and accessible imaging modality for monitoring pediatric IBD. The gold standard, endoscopy, requires general anesthesia in children. Magnetic resonance imaging provides excellent visualization, but is expensive and availability is limited. Alternatively, computed tomography (CT) is associated with radiation risk and is not recommended for repeated use. Ultrasound is accurate in the detection of disease activity, and our team has previously developed a simple score for inflammatory activity in adults based on a retrospective population with prospective score validation. OBJECTIVES: The aim of this study was to establish the most significant parameters in predicting severity of inflammatory disease activity in a retrospective population and develop a simple transabominal ultrasound score for further validation in the pediatric population. DESIGN/METHODS: 86 children were retrospectively included from an established database of children with IBD, and cross-referenced with Picture Archiving and Communication (PACs) imaging database. Only patients that had endoscopy and sonography within 60 days were included for comparison. Ultrasound parameters included: bowel wall thickness, mesenteric fat, hyperemia and lymphadenopathy. The weighted kappa statistic was calculated to assess agreement between sonographic and endoscopic findings. Using a proportional odds model and ordinal logistic regression, 4 statistically significant (p<0.05) parameters predicting disease activity were identified in the retrospective cohort and used to generate a grey-scale ultrasound (US) score that was then compared to gold standard endoscopy. Variables with significance were weighted to classify individuals into different severity classes (normal, mild, moderate and severe). Receiver operating characteristic curves (ROC) were plotted to demonstrate the discriminative and predictive capacity of the score. RESULTS: There was moderate agreement in disease severity between sonographic and endoscopic findings for all disease locations, including: ileocolonic, colonic and sigmoid disease (weight kappa=0.59) and substantial agreement in disease severity between imaging modalities for ileocolonic disease (weight kappa=0.72). Significant clinical predictors of pediatric IBD disease severity were bowel wall thickness and hyperemia (p<0.05). The AUC was 86.3% for normal vs mild and active disease and 76.8% for normal and mild vs active disease, indicating a good performance of the developed severity score. An ultrasound score of >=7 provided the best result in terms of combined sensitivity (74.32%) and specificity (100%) with regard to accurately predicting disease severity. CONCLUSION: Bowel wall thickness and hyperemia are the transabominal ultrasound parameters that best predict disease severity in children with IBD. These parameters can be combined into an accurate simple predictive score, effective in the detection of inflammatory activity in children with IBD.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".