Awareness among glaucoma patient at upper Egypt
Bibliographic record
Abstract
Aim: To assess the awareness among glaucoma patients at Upper Egypt Governorate hospitals.Research design: Descriptive cross sectional research design was used in this studySetting: The study was conducted in ophthalmology outpatient clinics (male & female) at Assiut University Hospital & Al-rmad Hospital, Elmina and Sohag Governorate.Subjects: The sample of this study total coverage of glaucoma patients included (1000), the researcher taking the sample during one year, this sample aged 50 years and above.Tool of study: One tool was used in this study include three parts, part I: patient demographic characteristics, part II: medical data, part III: knowledge about risk factors and self-practice regard glaucoma.Results: The most of patients age ranged between 60:80 year, nearly three quarter (74.6%) of them were females, and 80% of them comes from urban areas. The majority of studied sample (84.5%) unaware about glaucoma disease and show statistical significant difference between awareness of them and their education, P≤0.05. Also, there was no significant difference between knowledge of studied sample and their residence.Conclusion: The majority of glaucoma patients complain from poor of knowledge & practice.Recommendation: Design & implement of health educational program about glaucoma are needed to improve patient knowledge & practice regard glaucoma.
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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 | 0.000 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".