Clinical Features and Outcome of Patients With IRAK-4 and MyD88 Deficiency
Bibliographic record
Abstract
Autosomal recessive interleukin-1 receptor-associated kinase (IRAK)-4 and myeloid differentiation factor (MyD)88 deficiencies impair Toll-like receptor (TLR)- and interleukin-1 receptor-mediated immunity. We documented the clinical features and outcome of 48 patients with IRAK-4 deficiency and 12 patients with MyD88 deficiency, from 37 kindreds in 15 countries.The clinical features of IRAK-4 and MyD88 deficiency were indistinguishable. There were no severe viral, parasitic, and fungal diseases, and the range of bacterial infections was narrow. Noninvasive bacterial infections occurred in 52 patients, with a high incidence of infections of the upper respiratory tract and the skin, mostly caused by Pseudomonas aeruginosa and Staphylococcus aureus, respectively. The leading threat was invasive pneumococcal disease, documented in 41 patients (68%) and causing 72 documented invasive infections (52.2%). P. aeruginosa and Staph. aureus documented invasive infections also occurred (16.7% and 16%, respectively, in 13 and 13 patients, respectively). Systemic signs of inflammation were usually weak or delayed. The first invasive infection occurred before the age of 2 years in 53 (88.3%) and in the neonatal period in 19 (32.7%) patients. Multiple or recurrent invasive infections were observed in most survivors (n = 36/50, 72%).Clinical outcome was poor, with 24 deaths, in 10 cases during the first invasive episode and in 16 cases of invasive pneumococcal disease. However, no death and invasive infectious disease were reported in patients after the age of 8 years and 14 years, respectively. Antibiotic prophylaxis (n = 34), antipneumococcal vaccination (n = 31), and/or IgG infusion (n = 19), when instituted, had a beneficial impact on patients until the teenage years, with no seemingly detectable impact thereafter.IRAK-4 and MyD88 deficiencies predispose patients to recurrent life-threatening bacterial diseases, such as invasive pneumococcal disease in particular, in infancy and early childhood, with weak signs of inflammation. Patients and families should be informed of the risk of developing life-threatening infections; empiric antibacterial treatment and immediate medical consultation are strongly recommended in cases of suspected infection or moderate fever. Prophylactic measures in childhood are beneficial, until spontaneous improvement occurs in adolescence.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".