Glaucoma rehabilitation with action video games and exercise: study protocol of an active-controlled trial (GRADE)
Bibliographic record
Abstract
INTRODUCTION: Glaucoma is the second leading cause of moderate to severe visual impairment worldwide, primarily affecting peripheral vision and increasing the risk of falls due to impaired balance and mobility. While traditional physical training (PT) is used for fall prevention, its effectiveness may be limited by low patient engagement. Action video games (AVGs) may offer a more engaging alternative for improving balance and mobility in individuals with glaucoma. METHODS AND ANALYSIS: This prospective, two-arm, single-blind, active-control trial will involve 56 patients with glaucoma with moderate to severe peripheral field loss and intact cognitive function, who have not previously undergone balance training. Participants will be randomly assigned in a 1:1 ratio to either a physically interactive action video-game training (AVG) group or a conventional PT group. The AVG group will use a Nintendo Switch gaming station for 20 sessions of 45 min each, conducted two to three sessions per week over 8 weeks. These sessions will involve standing game exercises using game controllers or body sensors, focusing on muscle stretching and strengthening, balance improvement and fitness. The PT group will engage in traditional PT for the same duration and frequency. The primary outcome is the change in mobility function after 20 sessions, measured by the narrow path walking test. Secondary outcomes include balance function (modified Clinical Test of Sensory Interaction and Balance, motor control test, landing balance test, five-time sit-to-stand test and time up and go test), visual cognition (reaction time test and useful field of view test) and patient-reported outcomes (validated questionnaires). Exploratory outcomes include fall frequency, fear of falling, visual function and serum brain-derived neurotrophic factor levels (one of the biomarkers related to exercise). Assessments will occur at seven time points: baseline (T1), after 10 sessions (T2), after 20 sessions (T3), 1-month post-training (T4) and 3, 6 and 9 months after all training sessions (T5-T7). ETHICS AND DISSEMINATION: The human ethics approval was obtained from the respective ethics board of the Hong Kong Polytechnic University (ID: HSEARS20210722001). The study protocol will conform to the principles of the Declaration of Helsinki. Results will be disseminated through peer-reviewed journals and conferences. TRIAL REGISTRATION NUMBER: NCT06000865.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.036 | 0.006 |
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".