Type 3 VWD and an inhibitor to VWF: Challenges in diagnosis
Bibliographic record
Abstract
Abstract Developing an inhibitor to von Willebrand factor (VWF) is extremely uncommon. Consequently, patients with von Willebrand disease (VWD) tend not to be routinely evaluated for inhibitors, leading to the possibility of delay in inhibitor diagnosis. We present such an occurrence to raise awareness, with a view to avoiding such delays. A 1-year-old male with no family history of bleeding disorders or parental consanguinity presented with a tongue bleed lasting three days. Investigations confirmed a diagnosis of Type 3 VWD. Over the next few months, the patient received seven exposures to Humate-P (a plasma derived FVIII containing von Willebrand factor concentrate), but developed an anaphylactic reaction necessitating adrenalin and Benadryl (diphenhydramine). The reaction quickly abated and did not recur with further exposure to Humate-P. In 2013, due to recurrent epistaxis and tonsillar bleeding, the patient was commenced on prophylaxis receiving Humate-P 50 RCo U/kg twice weekly. Despite this regimen, he continued to experience recurrent epistaxis, leading to escalation of prophylaxis to 3/week. In November 2014, he showed persistent tonsillar bleeding, despite having received two doses of Humate-P (each 40 RCo U/kg) in the previous 12 hours. Testing revealed reduced VWF:Ag, VWF:RCo and FVIII:C recoveries. Further testing revealed an anti-VWF antibody (2.6 BU) of unspecified Ig type. Since diagnosis of the inhibitor, he has received 100 RCo U/kg daily for prophylaxis and immune tolerance. He is now bleed-free; however, monthly inhibitor testing shows that his inhibitor persists. Given the limited experience and literature on inhibitors in VWD, the prognosis for such cases is unknown.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".