Blau Syndrome and Early-Onset Sarcoidosis: A Six Case Series and Review of the Literature
Bibliographic record
Abstract
OBJECTIVES: This study aims to discuss the clinical, laboratory and genetic findings, and treatment options for six patients who were diagnosed with Blau syndrome (BS)/early-onset sarcoidosis (EOS). PATIENTS AND METHODS: The study included four patients (2 males,2 females; mean age 7 years; range 4 to 10 years) with EOS and two siblings (1 male, 1 female; mean age 10 years; range, 9 to 11 years) with BS. Age, age of initial symptoms, age of diagnosis; articular involvement, presence of uveitis, dermatitis, or fever, other organ involvement, laboratory findings, results of metabolic tests for mucopolysaccharidosis and mucolipidosis, results of genetic, pathologic, and immunologic tests, radiologic findings to evaluate skeletal dysplasia, and treatment options were collected. RESULTS: The median age at diagnosis of all patients was 6 years (range, 1 to 10 years). Five patients had camptodactyly and bilateral boggy synovitis in the wrists and ankles, one had granulomatous inflammatory changes in the liver and kidney biopsy, and one had attacks of fever and granulomatous dermatitis. None had uveitis. The detected mutations in nucleotide-binding oligomerization domain containing 2 (NOD2) were P268S (rs2066842), M513T (rs104895473), R702W (rs2066844), V955I (rs5743291), H343Y (rs199858111), and M491L (16:50745293). The treatments of patients included corticosteroids, non-steroid anti-inflammatory drugs, methotrexate, infliximab, adalimumab, anakinra, and canacinumab. CONCLUSION: Camptodactyly and boggy synovitis are important signs of BS/EOS. Methotrexate and tumor necrosis factor blockers are more effective in patients with predominantly articular symptoms. In patients 5 and 6 and their mother, we determined a novel M491L mutation in the NOD2 gene. Currently, this work is in progress towards identifying the pathogenesis and treatment options for this disease.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".