Four intestinal ultrasound scores and bowel wall thickness alone correlated well with pediatric ulcerative colitis disease activity
Bibliographic record
Abstract
Abstract Objectives Intestinal ultrasound (IUS) is a noninvasive tool in ulcerative colitis (UC), but scoring systems have mostly been developed for adults, Crohn's disease, and flaring UC. Our aim was to evaluate the performance of bowel wall thickness (BWT) and four IUS scores in pediatric patients with newly diagnosed UC. Methods Patients <18 years old with suspected UC were prospectively enrolled. Baseline IUS was done, and ulcerative colitis intestinal ultrasound score (UC‐IUS), Milan criteria, simple pediatric activity ultrasound score (SPAUSS), and Civitelli Index were calculated. Mayo endoscopic segment subscore, pediatric ulcerative colitis activity index (PUCAI), and biomarkers were correlated with IUS using nonparametric and receiver operating characteristic analyses. Results Fifty‐two patients (56% male, median age 13.9 years, interquartile range [IQR] 11.2–16.3) with 206 colon segments were included. Patients who needed hospitalization ( n = 27/52) had significantly worse IUS (BWT and all scores) compared to those not hospitalized. For all patients, IUS scores and BWT significantly correlated with baseline endoscopic, clinical, and biochemical disease activity ( p = 0.32–0.67, p < 0.05). BWT ( τ b = 0.53), UC‐IUS ( τ b = 0.55), and Milan ( τ b = 0.52) had the strongest endoscopic correlations. For differentiating between endoscopic disease severity, BWT, UC‐IUS, and Milan, had the highest areas under the curve (0.89–0.93). Using BWT alone, a thinner cut‐off had improved sensitivity while maintaining high specificity: ≥2.5 mm for moderate/severe endoscopic inflammation (sensitivity 66%; specificity 94%) and ≥3.5 mm for severe endoscopic inflammation (sensitivity 92%; specificity 86%). Conclusions BWT and all four IUS scores correlated well with endoscopic, clinical, and biochemical disease activity, and was another useful marker of severity in identifying patients needing hospitalization. Pediatric patients needed a thinner BWT cut‐off, which should be accounted for when developing pediatric‐specific scores. BWT alone may be just as clinically useful as composite US scores.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".