Early diagnosis of hereditary angioedema in children: genetic testing should be prioritized
Bibliographic record
Abstract
BACKGROUND: When a member of a family has been diagnosed with hereditary angioedema (HAE) before a child is born, the question of early diagnosis arises. Indeed, the first attacks may occur at birth. Early diagnosis is complicated by biological issues. Due to the immaturity of the complement system, C1 Inhibitor (C1 INH) and C4 levels can be low at birth, generally in the range of 60 to 100% of adult reference values. Like most complement proteins, their levels generally normalize after one year of life. However, this is not always the case, and we report two counter-examples here. CASE PRESENTATION: A woman with well-documented HAE due to type II C1 INH deficiency gave birth to two children 4 years apart. Functional C1 INH assays performed at 8 and 7 months of age returned normal C1 INH inhibitory activity. However, a genetic exploration revealed the presence of the mother's pathogenic gene variant in both children. Subsequent monitoring of C1 INH activity at 3 and 4 years of age confirmed a pathological reduction in C1 INH inhibitory activity. CONCLUSION: For the early detection of HAE in children, these cases lead us to recommend genetic testing for the index parent's pathological variant rather than reliance on results of C1 INH assays.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| 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".