Identifying hemophilia B carriers: Utility of aPTT, factor IX levels and ratios of factor IX to other Vitamin K dependent factors
Bibliographic record
Abstract
INTRODUCTION: Diagnosing hemophilia B (HB) carrier status is important to manage bleeding in carriers and to prevent bleeding in potential offspring. Without a family history of hemophilia, diagnosing HB carrier status is challenging. Genetic testing is the gold-standard, however it is reserved for individuals with a high suspicion of carrier status. AIMS: To describe the distribution of activated partial thromboplastin time (aPTT) and factor IX coagulant (FIX:C) levels in HB carriers and assess the ratio of FIX:C to other Vitamin K dependent factors (FII:C, FVII:C, FX:C) as an indicator of HB carrier status. METHODS: In this retrospective, single-centre cohort study, subjects were included if they were obligate or genetically proven HB carriers. Distributions of aPTT and FIX:C were described and the relationship between FIX:C levels in carriers and severity of familial HB was analysed. Ratios of FIX:C to FII:C, FVII:C, FX:C were calculated. RESULTS: Seventy-two female HB carriers (median age: 34 years; IQR 24-43) were included. Median aPTT and FIX:C levels were 33.0 s [IQR 30.0-37.0] and 57 IU/dL [IQR 43-74]. Fifteen carriers (21%) had mild HB (FIX:C levels of 10-40 IU/dL). FIX:C levels trended higher in carriers of mild HB versus carriers of moderate/severe HB. In six carriers, the median ratio of FIX:C to other Vitamin K dependent factors was 0.44, with 92% of ratios being ≤ 0.75. CONCLUSION: aPTT and FIX:C levels were unreliable in diagnosing HB carrier status. A low ratio of FIX:C to other Vitamin K dependent factors may be a useful marker of HB carrier status.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".