Disease Rarity, Carrier Status, and Gender: A Triple Disadvantage for Women with Fabry Disease
Bibliographic record
Abstract
Fabry disease is a multi-systemic X-linked genetic disorder which has progressive and deadly consequences for those it afflicts. Fabry disease symptoms are widely recognized as a substantive burden for affected males. In comparison, female heterozygotes have traditionally been viewed as relatively symptom-free, though a debate continues about whether and how much they suffer with the disease. Previous research suggests that females with Fabry disease may be triply disadvantaged in healthcare settings owing to: (1) disease rarity, (2) devalued carrier status, and (3) gender. The combined effects of these three factors suggest that female heterozygotes may suffer substantially with Fabry disease symptoms. A qualitative analysis of a brief disease-specific questionnaire provides supportive evidence. The female Fabry disease participants described experiencing significant symptoms that interfered with their lives. They also described unsatisfying experiences with healthcare professionals related to disease rarity, carrier status, and gender. The results of this study corroborate the suggestion that this triple disadvantage exists and may preclude appropriate management and treatment of females with Fabry disease. The role of healthcare professionals, including genetic counselors, in remedying this disadvantage is reviewed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".