Exploring the impact of Choroideremia on women with phenotypic and/or genotypic evidence of disease: insights from a global survey
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction Choroideremia (CHM) is an X-linked inherited retinal disease mostly affecting males. However, women with phenotypic and/or genotypic evidence of CHM may develop degenerative visual disability with advancing age. Our objective was to determine the visual impacts of phenotypic and/or genotypic evidence of CHM in women and its associated psychosocial burden and influence on activities of daily living (ADLs).Methods We conducted an international cross-sectional survey from April to December 2022 using an e-questionnaire distributed through not-for-profit stakeholder organizations and social media plat-forms.Results With a total of 55 respondents (n = 55), most women with phenotypic and/or genotypic evidence of CHM (76%) reported a change in their visual acuity. When assessing its impact on ADLs, Pearson’s correlation coefficient showed a negative correlation between driving (p = 0.046) and mobility capabil-ities (0.046) with the respondent’s age. More than half of women reported being afraid, anxious, and stressed, with women below the age of 50 years old reporting a significantly higher level of distress and hopelessness (p = 0.003), anxiety (p = 0.00007), issues with relaxing (p = 0.025), and negative personal thoughts (p = 0.042).Conclusion Overall, this survey outlines both physical and psychological burden of being a woman with phenotypic and/or genotypic evidence of CHM. Given the limited clinical research in females affected by CHM, this patient-centered survey is a crucial advocacy tool for these individuals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it