Choroideremia: Effect of age on visual acuity in patients and female carriers
Bibliographic record
Abstract
BACKGROUND/AIMS: The extent and time course of vision loss in Choroideremia (CHM) is still unclear. We undertook this study to quantitate the change in visual acuity (VA) over time in order to gain a better understanding of the natural course of this retinal disorder. METHODS: Corrected VA of 120 males with CHM and 53 female carriers were collected from 24 studies and/or case reports published between 1981 and 2010, as well as from data on 15 patients examined at the Cole Eye Institute (Cleveland Clinic). Cross-sectional and longitudinal analyses were used to investigate the relationship between VA and age, as well as the progression rate of VA with age, respectively. Age grouping effects were investigated using ANOVA. RESULTS: The mean age of affected males was 36.6 ± 17.7 years. The mean logMAR VA was 0.35 ± 0.53. There was a significant 0.0072 decrease in logMAR VA per year (p = 1.22 × 10(-4)). There was a significant difference between VA of patients <50 years of age and those >50 years (0.27 ± 0.39 vs. 0.61 ± 0.81, p = 2.90 × 10(-5)). When we compared the rate of VA loss for patients <50 years vs. those >50 years, we also found a significant difference (0.01 ± 0.04 vs. 0.06 ± 0.08, p = 1.23 × 10(-2)). The average age of female carriers was 36.4 ± 17.7 years, with an average logMAR VA of 0.36 ± 0.6. There was no significant correlation between VA of female carriers and age (p = 0.12) with 46% of female carriers having a VA better than 20/20 at an average age of 33 years compared to 25% of affected males at 30 years. CONCLUSION: In affected males with CHM, VA decreases very slowly until subjects reach 50 years of age, at which time the rate and extent of vision loss become significantly higher. Additionally, VA decreases more rapidly as individuals get older. In contradistinction to affected males, VA loss in female carriers is much milder.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".