Hemophilia B Leyden: characteristics and natural history in the International Pediatric Network of Hemophilia Management Registry
Bibliographic record
Abstract
BACKGROUND: A unique form of hemophilia B (HB) is HB Leyden. We evaluated the international Pediatric Network on Hemophilia Management Registry (PedNet) database to explore the natural history of HB Leyden, investigate genotype-phenotype associations, and guide clinical decision-making. OBJECTIVES: To assess the association between genetic variants, endogenous factor (F)IX levels over time, treatment, and bleeding phenotype in children with HB Leyden. METHODS: Data on genetic variants, FIX levels at diagnosis and over time, bleeding, and treatment details were extracted from the international PedNet in children with hemophilia born since 2000. RESULTS: Of 457 individuals with HB, 24 showed an HB Leyden genotype. The most frequent F9 variant was c.-35G>A, affecting 14 individuals, followed by c.-35G>C (n = 4), c.-49T>A (n = 2), and c.-52C>T, c.-34A>G, and c.-22delT (n = 1 each). Major clinical differences in bleeding and treatment modality were observed when comparing c.-35G>A with non-c.-35G>A genotypes. For all children with a c.-35G>A genotype, FIX levels increased before the age of 4 years but did not normalize over time, irrespective of initial severity. In children with non-c.-35G>A genotypes, an increase in FIX was less common (4/9) and occurred later. CONCLUSION: HB Leyden is caused by the variant c.-35G>A in >50% of cases in whom a FIX increase occurs at very young ages, which is associated with low bleeding rates. This contrasts with the phenotype of individuals with HB Leyden due to a non-c.-35G>A variant. Our study may thus help guide clinical decision-making in this rare HB entity.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".