Diagnostic Testing for von Willebrand Disease: Trends and Insights from North American Laboratories over the Last Decade
Bibliographic record
Abstract
Accurate diagnosis of von Willebrand disease (VWD) depends on the quality, precision, and variability of the laboratory assays. The North American Specialized Coagulation Laboratory Association (NASCOLA) is a provider of external quality assessment (EQA) for approximately 60 specialized coagulation laboratories in North America. In this report, NASCOLA EQA data from 2010 to 2021 are reviewed for trends in methodology and precision among various assays. In particular, recent ASH ISTH NHF WFH (American Society of Hematology, International Society on Thrombosis and Haemostasis, National Hemophilia Foundation, and World Hemophilia Federation) guidelines for diagnosis of VWD are reviewed in light of EQA data. In contrast to other geographic regions, laboratories in North America predominantly use three-assay screening panels (antigen, platelet-binding activity, and factor VIII [FVIII] activity) rather than four-assay panels (antigen, platelet-binding activity, FVIII activity, and collagen-binding activity). They also use latex immunoassays rather than chemiluminescence immunoassays, and the classic ristocetin cofactor (VWF:RCo) assay and monoclonal antibody (VWF:Ab) assay to assess VWF platelet-binding activity over newer recommended assays (VWF:GPIbM and VWF:GPIbR). Factors that may be influencing these North American practice patterns include lack of Food and Drug Administration approval of the VWF:GPIbM, VWF:GPIbR, collagen binding assays, and chemiluminescence methodologies, and the influence of the 2008 National Heart, Lung, and Blood Institute guidelines on laboratory practice. Lastly, systems-based solutions are urgently needed to improve the overall accuracy of laboratory testing for VWD by minimizing preanalytical variables and adopting assay standardization.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".