Assessing disease activity using the pediatric Crohn’s disease activity index: Can we use subjective or objective parameters alone?
Bibliographic record
Abstract
BACKGROUND: The pediatric Crohn's disease activity index (PCDAI) is used as a standard tool to assess disease activity in clinical trials for pediatric Crohn's disease. AIM: To examine which items on the PCDAI drive assessment of disease activity, and how subgroups of subjective and objective items reflect change in disease state over time. METHODS: = 474). Change in individual PCDAI scores from baseline to Q1 and to Q4 were examined using the non-weighted PCDAI. RESULTS: < 0.05). Subjective and objective subgroups of items predicted less variance (18% and 22%) on total PCDAI scores at Q1 and Q4 compared to the full PCDAI, or a composite scale (both 32%) containing significant predictors. CONCLUSION: Although subjective items on the PCDAI change the most over time, the full PCDAI or a smaller composite of items including a combination of subjective and objective components classifies disease activity better than a subgroup of either subjective or objective items alone. Reliance on subjective or objective items as stand-alone proxies for disease activity measurement could result in misclassification of disease state.
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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 | 0.014 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".