A Critical Assessment of Items on the Pediatric Crohn's Disease Activity Index
Bibliographic record
Abstract
ABSTRACT Objectives Questions have been raised about the discriminative value of the three laboratory items (hematocrit, erythrocyte sedimentation rate, and albumin) and three physical items (height, perirectal disease, and extraintestinal manifestations) included in the Pediatric Crohn's Disease Activity Index (PCDAI). The aim of this study was to analyze the value of these six “criticized” items to the discriminative properties of the PCDAI. Methods Data from 71 children with Crohn's disease visiting an outpatient clinic were analyzed. Physician global assessment of disease activity was used as the gold standard. A “basic index” was calculated by subtracting the score of the six criticized items from the score of the PCDAI calculated in the standard fashion. Multivariate logistic regression procedures identified which items significantly contributed to the “basic index”. Receiver operating characteristic curves were produced comparing the standard PCDAI score to the “basic index” and a new “clinical index” which included only the criticized items truly contributing to the discriminatory ability of the “basic index”. Results Logistic regression models identified only perirectal disease as contributing to the discriminative abilities of the basic index. The clinical index therefore consists of the three history items (abdominal pain, number of liquid stools, and general well‐being), three physical examination items (weight loss, abdominal examination, and perirectal disease) and no laboratory tests. The clinical index had an area under the curve not significantly inferior to that of the original PCDAI (0.93 [95% confidence interval, 0.89–0.99] vs. 0.96 [95% confidence interval, 0.92–0.99]). Conclusions A clinical index consisting of three history items and three physical examination items has an accuracy equal to the standard PCDAI in distinguishing children with disease in remission from those with a relapse.
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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 | 0.012 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".