P283 Predicting outcomes in paediatric Crohn’s disease: A systematic review
Bibliographic record
Abstract
Crohn’s disease (CD) developing during childhood and adolescence encompasses a spectrum of phenotypes and disease severity. Risk stratification to facilitate early, more individualised therapy is key to optimizing outcomes. We aimed to systematically review the evidence pertaining to prediction of chronically active inflammatory activity and disease complications in paediatric CD. We searched Pubmed and EMBASE from 1992 to 2017 for observational or controlled, English language studies reporting longitudinal associations between patient/disease characteristics and chronically active inflammatory disease or the following CD complications: B2/B3/perianal disease, linear growth impairment, bone disease, surgery, response to therapy and disease extension. Study selection was performed by two reviewers. Risk of bias was assessed with the Newcastle-Ottawa tool. The search identified 97 eligible studies (all observational). The majority focused on associations with surgery (n = 46), internal stricturing (B2) (n = 32) or penetrating (B3) (n = 30) complications; fewer on growth impairment (n = 20) or perianal fistulising disease (n = 19); and very few on chronically active inflammatory disease (n = 9) or bone disease (n = 10). In a large (n = 913) prospective study, older age and non-Caucasian ethnicity were associated with adjusted hazard ratios (aHRs) of 1.4 (95% confidence interval (CI) 1.2–1.8) and 3.2 (1.4–7.3), respectively, for B3 complications. Across several studies, ASCA IgG was associated with aHRs of 2.7 to 2.8 for B3 disease and CBir1 with aHRs of 2.3 to 3.0 for B2 and/or B3 disease. In a single large study, the aHR of OmpC for B2 and/or B3 disease was 2.4 (1.2–4.9). Across several studies, male sex was associated with HRs of 3.6 to 3.9 for linear growth impairment. Lower weight and BMI, and more active disease were associated with lower bone mineral density over time. Table 1 lists factors for which at least one study reported an association with an outcome of interest. The number of studies demonstrating a positive association, amongst all studies examining the predictor, is shown in brackets. No clear risk factors were identified for chronically active inflammatory disease. Factors with at least 1 study demonstrating an association with an outcome of interest (numbers in brackets indicate the number of studies showing an association amongst all studies examining that factor). Factors with at least 1 study demonstrating an association with an outcome of interest (numbers in brackets indicate the number of studies showing an association amongst all studies examining that factor). The majority of identified predictors are observed demographic or phenotypic associations. To date, only antimicrobial serology provides additional guidance for individualising treatment based on risk prediction. Molecular predictors of chronically active inflammatory disease and biologic treatment responsiveness are badly 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 | 0.005 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".