Vitreoretinal interface abnormalities in middle-aged adults with visual impairment in the UK Biobank study: prevalence, impact on visual acuity and associations
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to determine the prevalence of vitreoretinal interface abnormalities (VRIA), the degree of visual impairment and associations with VRIA among adults, aged 40-69 years, in the UK Biobank study. METHODS AND ANALYSIS: Colour fundus photographs and spectral domain optical coherence tomography images were graded for 25% of the 8359 UK Biobank participants with mild visual impairment or worse (LogMAR >0.3 or Snellen <6/12) in at least one eye. The prevalence and contribution of VRIA to visual impairment was determined and multinomial logistic regression models were used to investigate association with known risk factors and other predetermined socioeconomic, biometric, lifestyle and medical variables for cases and matched controls. RESULTS: The minimum prevalence of any VRIA was 17.6% and 8.1% in the eyes with and without visual impairment, respectively. VRIA were identified as the primary cause of visual impairment in 3.6% of eyes. Although epiretinal membrane and vitreomacular traction were the most common VRIA, the degree of visual impairment was typically milder with these than with other VRIA. Visual impairment with a VRIA was positively associated with increasing age (relative risk ratio (RRR) 1.22 (95% CI 1.07 to 1.40)), female gender (RRR 1.28; 1.08 to 1.52) and Asian or Asian British ethnicity (RRR 1.60; 1.10 to 2.32). CONCLUSIONS: VRIA are common in middle-aged adults in the UK Biobank study, especially in eyes with visual impairment. VRIA were considered to be the primary cause of visual impairment in 3.6% of all eyes with visual impairment, although there was variation in the degree of visual impairment for each type of VRIA.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".