Novel use of Autoinflammatory Diseases Activity Index (AIDAI) captures skin and extracutaneous features to help manage pediatric DITRA: A case report and a proposal for a modified disease activity index in autoinflammatory keratinization disorders
Bibliographic record
Abstract
Generalized pustular psoriasis (GPP) is a severe form of psoriasis, which is rare in pediatric and adult patients. It is characterized by sterile pustular lesions that appear on erythematous skin, associated with systemic features. A recent identification of mutations in the IL36RN gene in some GPP patients has led to a diagnosis of new autoinflammatory disease, interleukin-36-receptor antagonist deficiency (DITRA). DITRA represents an emerging group of autoinflammatory diseases with hyperkeratotic skin involvement, called autoinflammatory keratinization diseases (AIKD). DITRA diagnosis and management are challenging as neither DITRA-specific clinical assessment tools nor treatment trials exist. Autoinflammatory Diseases Activity Index (AIDAI) is a validated tool originally developed to evaluate disease activity and treatment response in other inherited autoinflammatory diseases with systemic and skin involvement. We report the first use of AIDAI in a pediatric DITRA patient with the following goals: (a) to describe the contribution of AIDAI to our patient's management; (b) to identify potential limitations of AIDAI in DITRA; (c) to review literature for current psoriasis assessment tools; and (d) to propose a preliminary DITRA/AIKD disease activity index (DITRA/AIDAI) to be validated in future studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".