A simple integrated primary health care based model for detection of diabetic retinopathy in resource-limited settings in Pakistani population
Bibliographic record
Abstract
Objective: To find out prevalence of Diabetic Retinopathy in general population of three districts in Pakistan.Methods: A community based cross-sectional survey was conducted in three large districts of Pakistan namely Rawalpindi in Punjab, Peshawar in Khyber Pakhtoonkhwa and Hyderabad in Sindh between January 2013 and August 2015. Lady Health Workers identified individuals at high risk for diabetes based on pre-defined criteria. High risk population was tested for dysglycemia. Fundoscopic evaluation for evidence of DR was performed in all individuals with a random blood glucose >190mg/dl. Individuals with the evidence of DR were referred to affiliated tertiary care ophthalmology departments.Results: A total of 42,629 individuals reported at the project sites and 63% (n=26,859) were female. Fifty one percent (n=21,989) individuals met high risk criteria. Out of these 21,989 individuals, dysglycemia was found in 3,869 (17.6%). Fundoscopy showed evidence of DR in 1,042 (27%) individuals. Amongst high risk population, dysglycemia was significantly more common in females as compared to males. The frequency of DR in dysglycemic patients was comparable across both gender groups.Conclusion: The prevalence of DR in Pakistani population is alarmingly high. This preventable cause of blindness is largely undiagnosed in our population and a simple integrated model based on primary health care facilities can help identify and treat a large population of DR patients.doi: http://dx.doi.org/10.12669/pjms.325.10955How to cite this:Jawa A, Assir MZK, Riaz SH, Chaudhary R, Awan F, Akram J. A simple integrated primary health care based model for detection of diabetic retinopathy in resource-limited settings in Pakistani population. Pak J Med Sci. 2016;32(5):1102-1106.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".