Management of Paediatric Patients With Medically Refractory Crohn’s Disease Using Ustekinumab: A Multi-Centred Cohort Study
Bibliographic record
Abstract
BACKGROUND: Ustekinumab [UST] is effective in the treatment of adults with moderate to severe Crohn's disease [CD]. There is a paucity of data on its use in children. AIM: To evaluate the response to UST in children with moderate to severe CD. METHODS: This multicentre retrospective cohort study identified children under 18 years old with CD, who received open-labelled subcutaneous UST. The primary outcome was changes in mean abbreviated Paediatric Crohn's Disease Activity Index [aPCDAI] between baseline and 3 and 12 months, and rate of clinical remission at 3 and 12 months. Secondary outcomes were clinical response at the same time points, changes in C-reactive protein [CRP] and albumin, improvement in growth parameters, and rate of adverse events. RESULTS: A total of 44 patients who failed at least one biological treatment were identified. Linear mixed model [LMM] analysis revealed a statistically significant effect of UST (χ2[1] = 42.7, p = 1.2 × 10-8) which lowered the aPCDAI scores by about 16 ± 2.7 at 3 months, and 19.6 ± 2.9 at 12 months. At 12 months, 38.6% of the patients achieved clinical remission and 47.8% achieved clinical response. There was a significant increase in mean weight z-score of 0.48 [±0.13] [p <0.001] and in mean body mass index [BMI] z score of 0.66 [±0.16] [p <0.001]. The probability of remaining on UST at 12 months was 76.9%. The rate of adverse events was 12.4 per 1000 patient-months. CONCLUSIONS: Subcutaneous UST should be considered a viable therapeutic option for paediatric patients who are refractory to other biological agents. Prospective randomised trials are needed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".