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Record W4400852746 · doi:10.1186/s13643-024-02593-2

Diabetic dyslipidemia and its predictors among people with diabetes in Ethiopia: systematic review and meta-analysis

2024· review· en· W4400852746 on OpenAlexaboutno aff
Abere Woretaw Azagew, Hailemichael Kindie Abate, Chilot Kassa Mekonnen, Habtamu Sewunet Mekonnen, Zewdu Baye Tezera, Gashaw Jember

Bibliographic record

VenueSystematic Reviews · 2024
Typereview
Languageen
FieldMedicine
TopicDiabetes, Cardiovascular Risks, and Lipoproteins
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDyslipidemiaMeta-analysisPublication biasFunnel plotPopulationDiabetes mellitusSubgroup analysisInternal medicineMEDLINEDemographyEnvironmental healthEndocrinology

Abstract

fetched live from OpenAlex

Abstract Background Dyslipidemia is an imbalance of lipid profiles. It increases the chance of clogged arteries and may cause heart attacks, strokes, and other circulatory disorders. Dyslipidemia affects the general population, but its severity is higher in diabetic populations. As a result, the chance of dyslipidemia-associated morbidity and mortality is highest in diabetic patients. In Ethiopia, around 2 to 6.5% of the population live with diabetes, but their lipid profiles are inconsistent across the studies. Therefore, this study aimed to estimate the pooled prevalence of diabetic dyslipidemia and its predictors among people with diabetes in Ethiopia. Method A systematic review and meta-analysis was conducted. The searches were carried out in MEDLINE via PubMed and OVID, EBSCO, Embase, and other supplementary gateways such as Google and Google Scholar, for articles published up to June 2023. The articles were searched and screened by title (ti), abstract (ab), and full text (ft). The quality of the eligible studies was assessed by the Newcastle–Ottawa scale. The heterogeneity was detected by the Cochrane Q statistic test and the I-squared ( I 2 ) test. Then subgroup analysis and meta-regression analysis were used to identify the source of the variations. A random or fixed-effect meta-analysis model was used to estimate the overall pooled prevalence and average effects. The publication bias was assessed by the funnel plot asymmetry test and/or Begg and Mazumdar’s test for rank correlation ( p -value < 0.05). The protocol has been registered in an international database, the prospective register of systematic reviews (PROSPERO), with reference number CRD42023441572. Result A total of 14 articles with 3662 participants were included in this review. The pooled prevalence of diabetic dyslipidemia in Ethiopia was found to be 65.7% (95% confidence interval (CI): 57.5, 73.9), I 2 = 97%, and p -value < 0.001. The overall prevalence of triglycerides (TG) and high-density lipoprotein cholesterol (HDL-c) were found to be 51.8% (95% CI : 45.1, 58.6) and 44.2% (95% CI : 32.8, 55.7), respectively, among lipid profiles. In meta-regression analysis, the sample size ( p value = 0.01) is the covariate for the variation of the included studies. Being female (adjusted odds ratio (AOR): 3.9, 95% CI : 1.5, 10.1), physical inactivity ( AOR : 2.6, 95% CI : 1.5, 4.3), and uncontrolled blood glucose ( AOR : 4.2, 95% CI : 1.9, 9.4) were found to be the determinants of dyslipidemia among diabetic patients. Conclusion This review revealed that the prevalence of diabetic dyslipidemia is high among people with diabetes in Ethiopia. Being female, having physical inactivity, and having uncontrolled blood glucose were found to be predictors of dyslipidemia among people with diabetes. Therefore, regular screening of lipid profiles and the provision of lipid-lowering agents should be strengthened to reduce life-threatening cardiovascular complications. Furthermore, interventions based on lifestyle modifications, such as regular physical activity and adequate blood glucose control, need to be encouraged.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.339
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0690.008
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.053
GPT teacher head0.320
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations6
Published2024
Admission routes1
Has abstractyes

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