DEVELOPMENT OF A PEDIATRIC ULCERATIVE COLITIS ACTIVITY INDEX (PUCAI)
Bibliographic record
Abstract
Background: No index of ulcerative colitis (UC) activity has been rigorously formulated, and none was developed among children. We developed an evaluative multi-item measure of UC activity for use in multi-center pediatric trials. Methods: A judgmental approach was used for item generation using a Delphi group of 48 pediatric IBD experts and literature review. Further item reduction and weighting was performed by regression analysis on a prospective cohort of pediatric UC patients (n = 10 patients/df) at 4 IBD centers. Physician global assessment of disease activity (PGA) was used as the dependent variable and PUCAI items as the predictors. β estimates of the model served to guide the weighting, governed by maximizing R square and aided by a correlation matrix. Reliability was assessed by Intra-Class Correlation coefficient (ICC) using ANOVA. Validation (using 2 constructs: predicted strong correlation with PGA and fair with endoscopic activity) and responsiveness testing of the weighted PUCAI are underway on a separate prospective cohort. Results: A list of 41 potential items was generated by the expert panel. Mean ratings and rank order of ratings were considered in item reduction, following 4 rounds of feedback to the group. Gradations for the 11 highest ranking items were selected by consensus following much iteration. The draft PUCAI was completed independently by 2 physicians assessing 150 children with UC (mean age 12.7 ± 3.8 yr, 52% males; 77% extensive UC; 34% moderate to severe; 19% mild and 47% quiescent). Reliability was excellent (ICC > 0.9 for all items). 6 items were most important in the regression analysis: stool number, consistency and blood, albumin, abdominal pain and nocturnal diarrhea together explained 93% of variation in PGA. In preliminary validation (n = 25) the weighted index correlates well with PGA and colonoscopic appearance and is responsive to change. Conclusions: The PUCAI was developed following a rigorous multi-step process, has excellent interobserver reliability, and provides a measure of pediatric UC activity.
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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 | 0.013 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".