Vision screening at two years does not reduce the prevalence of reduced vision at four and a half years of age
Bibliographic record
Abstract
BACKGROUND: There is currently insufficient evidence to recommend vision screening for children < 36 months of age. This study assessed the effect of comprehensive vision screening, as well as the sensitivity of age-appropriate vision tests, at two years of age on habitual visual acuity at 4.5 years of age. METHODS: Children born at risk of neonatal hypoglycaemia (n = 477) underwent vision assessment at 54 ± 2 months of age including measurement of monocular and binocular habitual visual acuity, assessment of binocularity and stereopsis. Of these children, 355 (74.4 per cent) had also received vision screening at two years of age (mean age = 24± 1 months), while 122 were not screened. RESULTS: Eighty (16.8 per cent) children were classified as having reduced vision at 4.5 years of age, but the prevalence of reduced vision did not differ between children who had previously been screened at two years of age and those who had not (15.5 per cent versus 20.5 per cent, p = 0.153). However, children with reduced vision at 4.5 years of age were more likely to have had visual abnormalities requiring referral detected at two years of age (p = 0.02). Visual acuity and mean spherical equivalent autorefraction measurements were also worse (higher values) in two-year-old children who were later classified with reduced habitual visual acuity (p = 0.031 and p = 0.001, respectively). Nevertheless, unaided binocular visual acuity, non-cycloplegic refractive error, and stereopsis at two years all showed poor sensitivity and specificity for predicting visual outcomes at 4.5 years of age. CONCLUSION: Our findings do not support the adoption of early vision screening in children as current vision tests suitable for use with two-year-old children have poor sensitivity for predicting mild-moderate habitual vision impairment at 4.5 years of age.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".