Pattern of presentation and visual outcome of glaucoma in a tertiary hospital, Makurdi, Nigeria
Bibliographic record
Abstract
Background: About 15% of blindness in Africa is due to glaucoma. The Nigerian National Blindness and Visual Impairment Survey found that glaucoma accounted for 16.7% of blindness with regional variations. The purpose of the study was to find the regional pattern of presentation and visual outcome to implement preventive measures. Methods: This was a descriptive retrospective study of new patients who presented to the eye clinic of Benue State University Teaching Hospital, Makurdi and were diagnosed of glaucoma. Results: In this study, 795 consecutive new patients who fulfilled the diagnostic criteria for glaucoma were included. Their mean age was 45.5 ± 18.3. There were 450 (56.6%) males. More patients presented in the fourth and fifth decade of life ( n = 299, 37.6%). Primary open-angle glaucoma (inclusive of juvenile open-angle glaucoma, n =595, 74.8%, and normal tension glaucoma, n = 8, 1.0%) accounted for a total of 603 (75.8%). There were 145 (18.2%) glaucoma suspects, 23 (2.9%) primary angle-closure glaucoma, 20 (2.5%) secondary glaucoma, and four cases of congenital glaucoma. Vertical cup-to-disc ratio of ≥0.9 was in 634 (39.9%) of eyes; 274 (34.4%) were bilateral, and were all considered to have severe, advanced or end-stage glaucoma. About 203 (25.5%) had discs asymmetry of ≥0.2. About 355 (22.3%) patients’ eyes were blind: 95 (11.9%) bilateral and 165 (20.8%) uniocular. Conclusion: Open-angle glaucoma was most common, and patients presented at a young age with severe eye disease, visual impairment, and blindness.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".