Effects of low-vision rehabilitation on reading speed and depression in age-related macular degeneration: A systematic review and meta-analysis
Bibliographic record
Abstract
Age-related macular degeneration (AMD) is a prevalent eye disease, which can lead to vision loss, impacting daily functioning. This study aimed to evaluate the effect of low-vision rehabilitation techniques such as magnifiers, telescopes, and microperimeter feedback, on improving reading speed and reducing depression in AMD patients. This study is a systematic review and meta-analysis. A systematic search of databases MEDLINE (OVID), EMBASE (OVID), and CINHAL (EBSCO), gray literature including ClinicalTrials.gov and ProQuest Dissertations and Theses Global (ProQuest), Conferences of The Association for Research in Vision and Ophthalmology, American Academy of Ophthalmology, and Canadian Ophthalmological Society were done from inception to 27 July 2022. Fixed-effect and random-effect models were applied to account for heterogeneity between studies. Publication bias was checked through funnel plots. A total of 33 studies (2611 subjects) were included;14 studies were included in the meta-analysis (1123 subjects) and 19 were included in the qualitative analysis. We found a non-significant increase in reading speed (effect size [ES] = 0.02, 95% confidence interval [CI] = [−0.18, 0.23]) for studies comparing patients who received no low-vision rehabilitation, versus the intervention group of AMD patients who received low-vision rehabilitation. We also found a significant decrease in reading speed (ES = −0.92, 95% CI = [−1.46, −0.39]) between studies evaluating the difference in reading speed at baseline visits compared to the follow-up visits in AMD patients who received low-vision rehabilitation. Low-vision rehabilitation was also found to result in a decrease in depression severity when compared to control groups, as well as from initial assessment to subsequent follow-up visits. Individuals with AMD who engaged in low-vision rehabilitation demonstrated improved reading speeds compared to their own baseline and to those who did not receive any interventions. Furthermore, these interventions also contributed to a reduction in symptoms of depression.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.035 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".