Impact of Visual Impairment on the Wellbeing and Functional Disability of Patients with Glaucoma in India
Bibliographic record
Abstract
Purpose: To investigate the impact of glaucoma-associated vision loss on quality of life and social functioning in Indians. Methods: A cross-sectional study with prospective enrollment was conducted. Participants were divided as: mild, moderate, and severe. Severity of glaucoma was stratified by the degree of binocular visual field loss in accordance with the Nelson Glaucoma Severity Scale (NGSS). The Glaucoma Quality of Life-15 (GQL-15) and a self-developed social function scale (SFS) were utilized to assess patients' wellbeing. Results: A total of 260 patients (mean ± SD age = 58.1 ± 12.01 years; 106 females) participated in the study. Univariate analyses revealed a significant relationship between final quality of life score and number of anti-glaucoma medications ( P = 0.01), previous surgeries ( P = 0.00), patients age ( P = 0.00), patients education level ( P = 0.02), and severity of glaucoma ( P = 0.00). Previous surgeries ( P = 0.04) and severity of glaucoma ( P = 0.00) were significant predictors of GQL-15 summary score. With increasing glaucoma severity, patients noted greater difficulty with peripheral vision, glare and dark adaptation, and outdoor tasks ( P < 0.0001). Severe glaucoma also impacted patients' functional performance—a significant decline was observed in sense of personal ( P < 0.0001) and social wellbeing ( P < 0.0001). Conclusions: Patients with advanced glaucoma report significant decline in functioning, their ability to interact in community, take care of self, and do leisure activities. Glaucoma imposes greater social burden on the elderly by impacting their sense of personal safety. Targeted visual and social rehabilitative programs are necessary to improve their wellbeing and independent functioning.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".