Bibliographic record
Abstract
Deficiencies of factor VIII (FVIII)/von Willebrand factor (VWF) or factor IX (FIX) are underappreciated as potential reasons for heavy menstrual bleeding, recurrent nosebleeds, and easy bruising in girls and women. Bleeding is usually not attributed to hemophilia because clinically significant deficiencies in clotting factors VIII and IX are thought to only affect males. While severe hemophilia is more commonly observed in boys and men, women with mutations in the FVIII or FIX genes ( f8 or f9) may have widespread bruising and even joint bleeding. They might be heterozygotes with a hemophilic allele on one X chromosome and a normal allele on the other or rarely homozygotes with hemophilic alleles on both X chromosomes. If most or all of an X chromosome is missing (X-chromosome hemizygosity or Turner syndrome) and a hemophilic mutation is present on the other X chromosome, the affected woman will have a severe bleeding tendency. Other inherited disorders that affect women as well as men are von Willebrand disease, combined deficiencies of factor V (FV) and FVIII, and combined deficiencies of the vitamin K-dependent clotting factors. Women as well as men with autoimmune diseases or even those previously well might acquire a severe hemorrhagic disorder due to autoantibodies directed against FVIII, FIX, or VWF. Lastly, easy bruising and mildly decreased FVIII levels are occasionally observed in both men and women with hypothyroidism or panhypopituitarism. The purpose of this brief review is to increase clinician awareness that these bleeding disorders can affect girls and women. An accurate diagnosis and appropriate therapy will greatly benefit patients and their families. J Hematol. 2024;13(4):137-141 doi: https://doi.org/10.14740/jh1298
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".