Diabetic Dyslipidemia and Its Determinants Among People With Diabetes in South Africa: Protocol for a Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Diabetic dyslipidemia (DD), characterized by a classical triad of abnormal lipid profiles among the diabetic population, presents a major public health concern in South Africa, particularly among Black South Africans. The increasing prevalence of DD significantly contributes to the development of atherosclerotic cardiovascular disease. With the incidence of diabetes rising from 4.5% in 2010 to 12.7% in 2021, urgent preventive measures and effective treatments are crucial to tackle the risk of premature mortality. Objective: This systematic review and meta-analysis protocol aims to examine the existing literature on DD, providing an understanding of its prevalence and associated predictors among the diabetic population in South Africa, with the intention of informing more effective clinical and public health interventions. Methods: The protocol is registered in PROSPERO (International Prospective Register of Systematic Reviews) and will adhere to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The available literature on DD will be systematically searched in common scholarly databases and reviewed accordingly. All published and unpublished studies conducted in South Africa prior to 2024 and written in English will be included. Two members (MN and FA) of the review team will independently screen the studies identified through the database search and assess risk of bias using the revised JBI critical appraisal tools. The review will integrate both quantitative and qualitative data synthesis. Results from both qualitative and quantitative data synthesis will be presented through forest plots, subgroup forest plots, and summary tables, which will present findings on pooled prevalence, odds ratios for predictors, heterogeneity statistics, and sensitivity analyses. Results: The protocol was finalized in January 2025. The literature search was conducted between October 2024 and March 2025. Title and abstract screening began in April 2025, and full-text review was completed by July 2025, with data extraction scheduled for completion by September 2025. The completion of statistical analyses is expected by October 2025. We anticipate submission of the completed systematic review and meta-analysis for publication in December 2025. Conclusions: The findings of the study protocol will inform the design of targeted interventions and policies aimed at advancing the management of DD and subsequently reducing the increased risk of atherosclerotic cardiovascular disease among the diabetic population.
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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 | 0.081 | 0.123 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.016 | 0.023 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.073 | 0.007 |
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".