Prevalence of hyperuricemia among type 2 diabetes mellitus patients in Africa: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Hyperuricemia increases morbidity and mortality in type 2 diabetic individuals. It is linked to the expansion of diabetes and cardiovascular diseases indicators, as well as being a significant predictor of coronary artery disease. It also leads to a poor prognosis and increment of diabetic complications including diabetic neuropathy, retinopathy, and nephropathy. Therefore, this systematic review and meta-analysis was aimed to determine the pooled prevalence of hyperuricemia among type 2 diabetes mellitus patients in Africa. Methods We conducted a systematic review and meta-analysis following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. To identify relevant articles, we searched electronic databases such as PubMed, Google Scholar, African Journal Online, Science Direct, Embase, ResearchGate, Scopus, and Web of Sciences. The quality of the included studies was assessed using the Newcastle-Ottawa Quality Assessment Scale. Statistical analysis was performed using Stata 14.0 software. To evaluate heterogeneity, we utilized Cochran’s Q test and I2 statistics. Publication bias was assessed through the examination of a funnel plot and Egger’s test. The pooled prevalence was estimated using a random effect model. Furthermore, sub-group and sensitivity analyses were conducted. Results The overall pooled prevalence of hyperuricemia among type 2 diabetic patients in Africa was 27.28% (95% CI: 23.07, 31.49). The prevalence was highest in Central Africa 33.72% (95% CI: 23.49, 43.95), and lowest in North Africa 24.72% (95% CI: 14.38, 35.07). Regarding sex, the pooled prevalence of hyperuricemia among female and male type 2 diabetic patients was 28.02% (95% CI: 22.92, 33.48) and 28.20% (95% CI: 22.92, 33.48), respectively. Conclusion This systematic review and meta-analysis showed a high prevalence of hyperuricemia among type 2 diabetic patients. So, regular screening and diagnosis of hyperuricemia required for preventing its pathological effects and contribution to chronic complications of diabetes. Systematic review registration : PROSPERO (2022: CRD42022331279).
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 | 0.015 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.042 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".