Inclusion of diabetic retinopathy screening strategies in national-level diabetes care planning in low- and middle-income countries: a scoping review
Bibliographic record
Abstract
BACKGROUND: Diabetes is a major public health concern, with approximately 80% of the burden falling on low- and middle-income countries (LMICs). Diabetic retinopathy (DR) is one of the most common microvascular complications of diabetes, and early detection through diabetic eye screening programmes is essential to prevent visual impairment and blindness. Careful planning at a national level is crucial for effective implementation of such programmes. METHODS: A scoping review was conducted, and the protocol was published previously to explain the methods in detail. Data were collected from databases and searches, including grey literature. Furthermore, consultations were conducted with key informants from LMICs. RESULTS: Lower-middle-income countries (29/50, 58%) and upper-middle-income countries (27/59, 45.8%) are making more progress than low-income countries (4/29, 13.8%) in terms of DR policy planning. However, no identified data for published policies have actually implemented national DR policies. Compared to low-income and lower-middle-income countries, upper-middle-income countries are making the most progress in implementing national diabetic eye screening programmes; however, their progress is still slow, with only 5/59 (8.5%) having such programmes. CONCLUSION: There are significant gaps in the literature, with no data reported for 78/138 (56.5%) LMICs. Further research is clearly needed to support and document DR policy development in LMICs.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".