Paediatric Behçet’s Disease: A Comprehensive Review with an Emphasis on Monogenic Mimics
Bibliographic record
Abstract
Behçet's disease (BD) is a polygenic condition with a complex immunopathogenetic background and challenging diagnostic and therapeutic concepts. Advances in genomic medicine have provided intriguing insights into disease pathogenesis over the last decade, especially into monogenic mimics of BD. Although a rare condition, paediatric BD should be considered an important differential diagnosis, especially in cases with similar phenotypes. Emerging reports of monogenic mimics have indicated the importance of genetic testing, particularly for those with early-onset, atypical features and familial aggregation. Treatment options ought to be evaluated in a multidisciplinary setting, given the complexity and diverse organ involvement. Owing to the rarity of the condition, there is a paucity of paediatric trials; thus, international collaboration is warranted to provide consensus recommendations for the management of children and young people. Herein, we summarise the current knowledge of the clinical presentation, immunopathogenetic associations and disease mechanisms in patients with paediatric BD and BD-related phenotypes, with particular emphasis on recently identified monogenic mimics.
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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 | 0.000 | 0.001 |
| 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) | 0.003 | 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".