Early endoscopic, laboratory and clinical predictors of poor disease course in paediatric ulcerative colitis
Bibliographic record
Abstract
OBJECTIVE: Data to support treatment algorithms in ambulatory paediatric UC are scarce. We aimed to explore the 1 year outcome in an inception cohort of paediatric UC patients and to identify early predictors of good outcome that might serve as short term treatment targets. DESIGN: A chart review of 115 children with new onset UC was performed (age 11 ± 4.1 years; 58 (50%) males; 86 (75%) extensive colitis; 70 (61%) moderate-severe disease; 63 (55%) received steroids at baseline). We assessed the Paediatric Ulcerative Colitis Activity Index (PUCAI) and laboratory variables at the time of diagnosis and at 3 months, and endoscopy at diagnosis. RESULTS: The 3 month PUCAI was the strongest predictor of 1 year sustained steroid free remission (SSFR) (area under the receiver operating characteristic curve (AUROC)=0.7 (95% CI 0.6 to 0.8) and colectomy by 2 years (AUROC=0.75 (0.6 to 0.89)). SSFR was achieved in 9/54 (17%) children who had active disease (PUCAI ≥ 10) at 3 months (negative predictive value (NPV)=83%) and by 4/46 (8.6%) of those with a PUCAI score >10; (NPV=91%, positive predictive value=52%; p<0.001), implying that PUCAI >10 at 3 months has a probability of 9% for achieving SSFR versus 48% with a PUCAI value of ≤10. None of the variables at baseline was predictive of SSFR or colectomy (endoscopic severity, disease extent, age, PUCAI or C reactive protein/erythrocyte sedimentation rate/albumin/haemoglobin; all AUROC<0.6, p>0.05) but baseline PUCAI predicted subsequent acute severe colitis and the need for salvage medical therapy. CONCLUSIONS: Completeness of the early response appears more important than baseline UC severity for predicting outcome in children, and supports using PUCAI<10 as a feasible treatment goal. Our data suggest that treatment escalation should be considered with a PUCAI value of ≥ 10 at 3 months.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".