Cognitive Level Enhancement through Vision Exams and Refraction (CLEVER): study protocol for a randomised controlled trial
Bibliographic record
Abstract
BACKGROUND: Longitudinal observational studies have found an association between vision impairment and accelerated decline in cognition. However, no randomised trials have assessed the possible benefit of vision correction on cognitive change. We present the protocol for a three-year randomised controlled trial designed to assess the impact of spectacles for distance and/or near vision correction on cognitive change among community-dwelling elderly participants in India. METHODS: Cognitive Level Enhancement through Vision Exams and Refraction (CLEVER) is a single-centre, open-label, parallel-group, individually-randomised trial. Participants (760 total, 380 in each arm) aged ≥ 60 years with correctable vision impairment at distance and/or near (presenting visual acuity < 6/18 in the better-seeing eye and improving to > = 6/18 with spectacles and/or presenting near vision worse than N6 at 40 cm and improving to N6 with spectacles), normal hearing (able to repeat at least three out of six words whispered from a 50 cm distance in the better ear) and normal cognition (Hindi Mini-mental Status Examination score > 18/31) will be enrolled. After a comprehensive eye examination, intervention group participants will receive distance, near, or bifocal spectacles, while controls will receive a prescription and spectacles at the end of the trial. The primary outcome will be the three-year change in Longitudinal Aging Study in India-Diagnostic Assessment of Dementia (LASI DAD) global cognitive factor score, with and without adjustment for baseline score, age, gender, education and other potential confounders. CONCLUSION: CLEVER is designed to assess the effectiveness of spectacles as a low-cost intervention to prevent or delay cognitive decline. TRIAL REGISTRATION: This trial is registered with ClinicalTrials.gov, number NCT05458323, February 15, 2023.
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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 | 0.032 | 0.034 |
| Meta-epidemiology (narrow) | 0.008 | 0.004 |
| Meta-epidemiology (broad) | 0.015 | 0.006 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.099 | 0.017 |
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".