Different visual development: norms for visual acuity in children with Down’s syndrome
Bibliographic record
Abstract
BACKGROUND: Visual acuity is known to be poorer in children with Down's syndrome than in age-matched controls. However, to date, clinicians do not have access to norms for children with Down's syndrome that allow differential discrimination of healthy from anomalous visual development in this population. METHODS: The Down's Syndrome Vision Research Unit at Cardiff University has been monitoring visual development in a large cohort of children since 1992. Cross-sectional data on binocular visual acuity were retrospectively analysed for 159 children up to 12 years of age in order to establish binocular acuity norms. Longitudinal binocular acuity data were available for nine children who were seen regularly over the 12 years age-range. Monocular acuity was successfully recorded less often in the cohort, but analysis of scores for 69 children allowed assessment of inter-ocular acuity differences and binocular summation. RESULTS: In comparison with published norms for the various acuity tests used, binocular acuity was consistently poorer in children with Down's syndrome from the age of three years and stabilised at around 0.25 logMAR from the age of four years. Inter-ocular acuity difference and binocular summation were both 0.06 logMAR, which is similar to the reported values in children without Down's syndrome. CONCLUSIONS: The study provides eye-care practitioners with the expected values for binocular acuity in children with Down's syndrome and demonstrates the visual disadvantage that children with Down's syndrome have when compared with their typically developing peers. The results emphasise the responsibility that practitioners have to notify parents and educators of the relatively poor vision of children with Down's syndrome, and the need for classroom modifications.
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.
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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".