Bibliographic record
Abstract
Background: Hyper IgE syndrome (HIES) is a primary immunodeficiency with sporadic, autosomal dominant (STAT3 mutation) and autosomal recessive (DOCK8 and TYK2 mutations) inheritance patterns. HIES is characterized by recurrent Staphylococcus infections including lung infections, skin and visceral abcesses, pulmonary pneumatoceles, mucocutaneous candidiasis, and eczematous rash with associated elevated IgE. Patients with STAT3 mutations have additional features including connective tissue, skeletal, dental, and vascular abnormalities. Methods: This case series highlights the clinical presentation, radiographic findings, and immunologic investigations of 4 siblings with HIES caused by STAT3 mutation. Results: Our patients presented with infections including Staphylococcus aureus visceral abscesses, skin lesions, pneumonia with associated pneumatocele, and minimal signs of inflammation such as fever. Additional characteristic features included eczematous rash, scoliosis, fractures, and delayed shedding of primary teeth. Immune investigations were essentially unremarkable apart from elevated IgE and eosinophil counts. Detailed imaging identified infectious processes and associated noninfectious features of STAT3 mutations. Conclusion: Patients presenting with recurrent Staphylococcal cutaneous and visceral infections, pneumatoceles, candidiasis, and eczematous rash with associated elevated IgE should be investigated for STAT3 mutations. This case series highlights the important role of radiographic imaging to identify infectious processes as well as noninfectious associated features in patients with STAT3 mutations. Statement of novelty: Detailed images of morbidity associated with a STAT3 deficiency.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".