Prevalence of diabetic retinopathy and its associated risk factors among adults in Ethiopia: a systematic review and meta-analysis
Bibliographic record
Abstract
Diabetic retinopathy is a complication of diabetes mellitus and a leading cause of blindness and visual impairment globally. Limited information existed on the epidemiology of diabetic retinopathy at the national level in Ethiopia. Thus, the objective of this review was to determine the pooled prevalence of diabetic retinopathy and its associated risk factors in Ethiopia. A systematic review and meta-analysis was conducted using previous primary studies that were found in electronic databases such as Web of Science, Scopus, PubMed, CINHAL, Google Scholar, and online African journals. We evaluated the quality of the included studies using the Newcastle-Ottawa Assessment Scale. The random-effects model was applied because heterogeneity was expected. I-Square and the Cochrane Q statistics were used to evaluate heterogeneity. Publication bias was examined using Egger’s test and a funnel plot. A random-effect meta-analysis was applied to pool the odds ratios of risk factors to determine the association between the independent and dependent variables. After 598 articles were found, 22 studies that met the eligibility requirements were included. The pooled prevalence of retinopathy among patients with diabetes in Ethiopia was 24.35% (95% CI: 18.88–29.83), with considerable heterogeneity (I 2 = 98.18%, p < 0.001). Ten years and longer with diabetes (AOR = 4.36, 95% CI: 1.71–7.01), hypertension (AOR = 2.54, 95% CI: 1.45–3.63), poor glycemic control (AOR = 3.83, 95% CI: 1.62–6.04), and positive proteinuria (AHR = 1.55, 95% CI: 1.02–2.07) were risk factors for diabetic retinopathy. Retinopathy affects one in four patients with diabetes. Diabetic patients with longer duration, hypertension, poor glycemic control, and positive proteinuria should receive special care.
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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 | 0.013 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.038 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".