An approach to outreach patients with von Willebrand disease in Egypt by targeting women with heavy menstrual bleeding and/or bleeding symptoms
Bibliographic record
Abstract
von Willebrand disease (VWD) is frequently ignored as a cause of menorrhagia. We investigated Egyptian women complaining of heavy menstrual bleeding (HMB) and/or other bleeding symptoms to detect potential VWD cases. Seventy-five female patients complaining of HMB and/or bleeding symptoms and 38 age-matched healthy female controls went through a family history questionnaire, a physical examination and were evaluated for bleeding score, pictorial blood assessment chart (PBAC), complete blood count, serum ferritin, blood group, prothrombin time, activated partial thromboplastin time, factor VIII (FVIII) activity, von Willebrand factor (VWF) ristocetin cofactor (RCo) activity, antigen (Ag), and RCo/Ag ratio. Sixty-eight of 75 patients presented with HMB, out of which 46 had no organic pathology and 7 presented other bleeding symptoms. Six patients were diagnosed with VWD, three with HMB, two with other bleeding symptoms and one with family history of VWD. Two related VWD patients were diagnosed in the control group. There were significant differences in bleeding and PBAC scores, ferritin level, FVIII activity, VWF:RCo and VWF:Ag between VWD patients and controls. This study indicated a high prevalence of VWD among patients with HMB without organic pathology (6.5%) and demonstrated the sensitivity of diagnostic parameters of VWD patients in an outreach campaign. The inexpensive bleeding and PBAC scoring systems are valuable to exclude cases without objective bleeding symptoms. Raising gynaecologists awareness about hereditary bleeding disorders is important to ensure a proper diagnosis and possible referral of these patients. Management of these patients with comprehensive medical care services under a multidisciplinary team would be ideal.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".