-
BMC Endocrine Disorders Jan 2024The current systematic review aimed to elucidate the effects of lipid variability on microvascular complication risk in diabetic patients. The lipid components studied... (Meta-Analysis)
Meta-Analysis
BACKGROUND AND AIMS
The current systematic review aimed to elucidate the effects of lipid variability on microvascular complication risk in diabetic patients. The lipid components studied were as follows: High-density lipoprotein (HDL), High-density lipoprotein (LDL), Triglyceride (TG), Total Cholesterol (TC), and Remnant Cholesterol (RC).
METHOD
We carried out a systematic search in multiple databases, including PubMed, Web of Science, and SCOPUS, up to October 2nd, 2023. After omitting the duplicates, we screened the title and abstract of the studies. Next, we retrieved and reviewed the full text of the remaining articles and included the ones that met our inclusion criteria in the study.
RESULT
In this research, we examined seven studies, comprising six cohort studies and one cross-sectional study. This research was conducted in Hong Kong, China, Japan, Taiwan, Finland, and Italy. The publication years of these articles ranged from 2012 to 2022, and the duration of each study ranged from 5 to 14.3 years. The study group consisted of patients with type 2 diabetes aged between 45 and 84 years, with a diabetes history of 7 to 12 years. These studies have demonstrated that higher levels of LDL, HDL, and TG variability can have adverse effects on microvascular complications, especially nephropathy and neuropathic complications. TG and LDL variability were associated with the development of albuminuria and GFR decline. Additionally, reducing HDL levels showed a protective effect against microalbuminuria. However, other studies did not reveal an apparent relationship between lipid variations and microvascular complications, such as retinopathy. Current research lacks geographic and demographic diversity. Increased HDL, TG, and RC variability have been associated with several microvascular difficulties. Still, the pathogenic mechanism is not entirely known, and understanding how lipid variability affects microvascular disorders may lead to novel treatments. Furthermore, the current body of this research is restricted in its coverage. This field's lack of thorough investigations required a more extensive study and comprehensive effort.
CONCLUSION
The relationship between lipid variation (LDL, HDL, and TG) (adverse effects) on microvascular complications, especially nephropathy and neuropathic (and maybe not retinopathy), is proven. Physicians and health policymakers should be highly vigilant to lipid variation in a general population.
Topics: Humans; Middle Aged; Aged; Aged, 80 and over; Diabetes Mellitus, Type 2; Cross-Sectional Studies; Cholesterol, HDL; Triglycerides; Cholesterol; Lipoproteins, HDL
PubMed: 38167035
DOI: 10.1186/s12902-023-01526-9 -
Machine learning prediction models for diabetic kidney disease: systematic review and meta-analysis.Endocrine Jun 2024Machine learning is increasingly recognized as a viable approach for identifying risk factors associated with diabetic kidney disease (DKD). However, the current state... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Machine learning is increasingly recognized as a viable approach for identifying risk factors associated with diabetic kidney disease (DKD). However, the current state of real-world research lacks a comprehensive systematic analysis of the predictive performance of machine learning (ML) models for DKD.
OBJECTIVES
The objectives of this study were to systematically summarize the predictive capabilities of various ML methods in forecasting the onset and the advancement of DKD, and to provide a basic outline for ML methods in DKD.
METHODS
We have searched mainstream databases, including PubMed, Web of Science, Embase, and MEDLINE databases to obtain the eligible studies. Subsequently, we categorized various ML techniques and analyzed the differences in their performance in predicting DKD.
RESULTS
Logistic regression (LR) was the prevailing ML method, yielding an overall pooled area under the receiver operating characteristic curve (AUROC) of 0.83. On the other hand, the non-LR models also performed well with an overall pooled AUROC of 0.80. Our t-tests showed no statistically significant difference in predicting ability between LR and non-LR models (t = 1.6767, p > 0.05).
CONCLUSION
All ML predicting models yielded relatively satisfied DKD predicting ability with their AUROCs greater than 0.7. However, we found no evidence that non-LR models outperformed the LR model. LR exhibits high performance or accuracy in practice, while it is known for algorithmic simplicity and computational efficiency compared to others. Thus, LR may be considered a cost-effective ML model in practice.
Topics: Humans; Machine Learning; Diabetic Nephropathies
PubMed: 38141061
DOI: 10.1007/s12020-023-03637-8 -
Journal of Diabetes Dec 2023Long noncoding RNAs (lncRNAs) may be associated with the development of type 2 diabetes mellitus and its complications; however, the findings remain controversial. We...
AIMS
Long noncoding RNAs (lncRNAs) may be associated with the development of type 2 diabetes mellitus and its complications; however, the findings remain controversial. We aimed to synthesize the available data to assess the diagnostic utility of lncRNAs for identification of type 2 diabetes mellitus and its consequences.
MATERIALS AND METHODS
We performed a systematic review and meta-analysis, searching PubMed, Embase, and Web of Science for articles published from September 11, 2015 to December 27, 2022. We evaluated human case-control or cohort studies on differential lncRNA expression in type 2 diabetes mellitus or its associated comorbidities. We excluded studies if they were non-peer reviewed or published in languages other than English. From 2387 identified studies, we included 17 (4685 participants).
RESULTS
Analysis of the pooled data showed that lncRNAs had a diagnostic area under the curve (AUC) of 0.84 (95% CI: 0.80-0.87), with a sensitivity of 0.79 (95% CI: 0.74-0.83) and a specificity of 0.75 (95% CI: 0.69-0.80). LncRNAs had an AUC of 0.65 for the diagnosis of prediabetes, with 82% sensitivity and 65% specificity.
CONCLUSIONS
LncRNAs may be promising diagnostic markers for type 2 diabetes mellitus and its complications.
PubMed: 38140829
DOI: 10.1111/1753-0407.13510 -
Computational and Mathematical Methods... 2023[This retracts the article DOI: 10.1155/2022/9671768.].
[This retracts the article DOI: 10.1155/2022/9671768.].
PubMed: 38094458
DOI: 10.1155/2023/9813031 -
Food & Function Jan 2024Garlic ( L.) is a popular spice that is widely used for food and medicinal purposes and has shown potential effects on diabetic kidney disease (DKD). Nevertheless,... (Meta-Analysis)
Meta-Analysis Review
Garlic ( L.) is a popular spice that is widely used for food and medicinal purposes and has shown potential effects on diabetic kidney disease (DKD). Nevertheless, systematic preclinical studies are still lacking. In this meta-analysis and systematic review, we evaluated the role and potential mechanisms of action of garlic and its derived components in animal models of DKD. We searched eight databases for relevant studies from the establishment of the databases to December 2022 and updated in April 2023 before the completion of this review. A total of 24 trials were included in the meta-analysis. It provided preliminary evidence that supplementing with garlic could improve the indicators of renal function (BUN, Scr, 24 h urine volume, proteinuria, and KI) and metabolic disorders (BG, insulin, and body weight). Meanwhile, the beneficial effects of garlic and its components in DKD could be related to alleviating oxidative stress, suppressing inflammatory reactions, delaying renal fibrosis, and improving glucose metabolism. Furthermore, time-dose interval analysis exhibited relatively greater effectiveness when garlic products were supplied at doses of 500 mg kg with interventions lasting 8-10 weeks, and garlic components were administered at doses of 45-150 mg kg with interventions lasting 4-10 weeks. This meta-analysis and systematic review highlights for the first time the therapeutic potential of garlic supplementation in animal models of DKD and offers a more thorough evaluation of its effects and mechanisms to establish an evidence-based basis for designing future clinical trials.
Topics: Animals; Antioxidants; Biological Products; Diabetes Mellitus; Diabetic Nephropathies; Dietary Supplements; Garlic; Oxidative Stress; Disease Models, Animal
PubMed: 38051214
DOI: 10.1039/d3fo02407e -
The Journal of Clinical Endocrinology... Apr 2024Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease. Measures to prevent and treat DKD require better identification of patients most at risk....
CONTEXT
Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease. Measures to prevent and treat DKD require better identification of patients most at risk. In this systematic review, we summarize the existing evidence of genetic risk scores (GRSs) and their utility for predicting DKD in people with type 1 or type 2 diabetes.
EVIDENCE ACQUISITION
We searched MEDLINE, Embase, Web of Science, and Cochrane Reviews in June 2022 to identify all existing and relevant literature. Main data items sought were study design, sample size, population, single nucleotide polymorphisms of interest, DKD-related outcomes, and relevant summary measures of result. The Critical Appraisal Skills Programme checklist was used to evaluate the methodological quality of studies.
EVIDENCE SYNTHESIS
We identified 400 citations of which 15 are included in this review. Overall, 7 studies had positive results, 5 had mixed results, and 3 had negative results. Most studies with the strongest methodological quality (n = 9) reported statistically significant and favourable findings of a GRS's association with at least 1 measure of DKD.
CONCLUSION
This systematic review presents evidence of the utility of GRSs to identify people with diabetes that are at high risk of developing DKD. In practice, a robust GRS could be used at the first clinical encounter with a person living with diabetes in order to stratify their risk of complications. Further prospective research is needed.
Topics: Humans; Diabetic Nephropathies; Diabetes Mellitus, Type 2; Genetic Risk Score; Kidney Failure, Chronic
PubMed: 38039081
DOI: 10.1210/clinem/dgad704 -
PeerJ 2023High-sensitivity cardiac troponin (hs-cTn) is associated with cardiovascular outcomes in the general population, but the prognostic value of hs-cTn in the diabetic... (Meta-Analysis)
Meta-Analysis
BACKGROUND
High-sensitivity cardiac troponin (hs-cTn) is associated with cardiovascular outcomes in the general population, but the prognostic value of hs-cTn in the diabetic population remains inconclusive. This study aimed to systematically review current evidence regarding the association between hs-cTn and the prognosis of diabetic patients.
METHODS
MEDLINE, Embase, and the Cochrane Database were searched from inception to May, 2023. Observational studies that investigated the prognostic value of hs-cTn in diabetic patients were included in this meta-analysis. Studies were excluded if they did not report outcomes of interest, or urine hs-cTn were measured. Two independent investigators extracted and analyzed the data according to the PRISMA guidelines. The primary outcome was long-term major adverse cardiovascular events (MACE).
RESULTS
We included 30 cohort studies of 62,419 diabetic patients. After a median follow-up of 5 (4.1-9.5) years, the pooled results suggested elevation of hs-cTn was associated with a significantly increased risk of MACE (adjusted hazard ratio (HR) per standard deviation (SD) change 1.15, 95% CI [1.06-1.25], I = 0%) and heart failure (adjusted HR per SD change 1.33, 95% CI [1.08-1.63], I = 0%) in patients with diabetes. No significant association was found regarding the association between elevation of hs-cTn and risk of all-cause mortality (adjusted HR per SD change 1.24, 95% CI [0.98-1.57], I = 0%). The results of sensitivity analyses were similar in prospective cohort studies, high-quality studies, or population without major cardiovascular comorbidities at baseline. hs-cTn may represent a strong and independent predictor of MACE and heart failure in diabetic patients. Future research is warranted to determine the appropriate cutoff value for hs-cTn with different comorbidities, for instance, diabetic nephropathy, peripheral artery diseases, etc.
Topics: Humans; Prognosis; Prospective Studies; Heart Failure; Troponin; Diabetes Mellitus; Observational Studies as Topic
PubMed: 38025710
DOI: 10.7717/peerj.16376 -
Translational Research : the Journal of... Mar 2024Diabetic kidney disease (DKD) is a major microvascular complication of diabetes mellitus (DM) that poses a serious risk as it can lead to end-stage renal disease (ESRD).... (Review)
Review
Diabetic kidney disease (DKD) is a major microvascular complication of diabetes mellitus (DM) that poses a serious risk as it can lead to end-stage renal disease (ESRD). DKD is linked to changes in the diversity, composition, and functionality of the microbiota present in the gastrointestinal tract. The interplay between the gut microbiota and the host organism is primarily facilitated by metabolites generated by microbial metabolic processes from both dietary substrates and endogenous host compounds. The production of numerous metabolites by the gut microbiota is a crucial factor in the pathogenesis of DKD. However, a comprehensive understanding of the precise mechanisms by which gut microbiota and its metabolites contribute to the onset and progression of DKD remains incomplete. This review will provide a summary of the current scenario of metabolites in DKD and the impact of these metabolites on DKD progression. We will discuss in detail the primary and gut-derived metabolites in DKD, and the mechanisms of the metabolites involved in DKD progression. Further, we will address the importance of metabolomics in helping identify potential DKD markers. Furthermore, the possible therapeutic interventions and research gaps will be highlighted.
Topics: Humans; Diabetic Nephropathies; Biomarkers; Kidney Failure, Chronic; Metabolomics; Diabetes Mellitus
PubMed: 37952771
DOI: 10.1016/j.trsl.2023.11.002 -
PloS One 2023Diabetic kidney disease (DKD) is a health burden of rising importance. Slowing progression to end stage kidney disease is the main goal of drug treatment. The aim of... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Diabetic kidney disease (DKD) is a health burden of rising importance. Slowing progression to end stage kidney disease is the main goal of drug treatment. The aim of this analysis is to compare drug treatments of DKD by means of a systemic review and a network meta-analysis.
METHODS
We searched Medline, CENTRAL and clinicaltrials.gov for randomized, controlled studies including adults with DKD treated with the following drugs of interest: single angiotensin-converting-enzyme-inhibitor or angiotensin-receptor-blocker (single ACEi/ARB), angiotensin-converting-enzyme-inhibitor and angiotensin-receptor-blocker combination (ACEi+ARB combination), aldosterone antagonists, direct renin inhibitors, non-steroidal mineralocorticoid-receptor-antagonists (nsMRA) and sodium-glucose cotransporter-2 inhibitors (SGLT2i). As primary endpoints, we defined: overall mortality and end-stage kidney disease, as secondary endpoints: renal composite outcome and albuminuria and as safety endpoints: acute kidney injury, hyperkalemia and hypotension. Under the use of a random effects model, we computed the overall effect estimates using the statistic program R4.1 and the corresponding package "netmeta". Risk of bias was assessed using the RoB 2 tool and the quality of evidence of each pairwise comparison was rated according to GRADE (Grading of Recommendations Assessment, Development and Evaluation).
RESULTS
Of initial 3489 publications, 38 clinical trials were found eligible, in total including 42346 patients. Concerning the primary endpoints overall mortality and end stage kidney disease, SGLT2i on top of single ACEi/ARB compared to single ACEi/ARB was the only intervention significantly reducing the odds of mortality (OR 0.81, 95%CI 0.70-0.95) and end-stage kidney disease (OR 0.69, 95%CI 0.54-0.88). The indirect comparison of nsMRA vs SGLT2i in our composite endpoint suggests a superiority of SGLT2i (OR 0.60, 95%CI 0.47-0.76). Concerning safety endpoints, nsMRA and SGLT2i showed benefits compared to the others.
CONCLUSIONS
As the only drug class, SGLT2i showed in our analysis beneficial effects on top of ACEi/ARB treatment regarding mortality and end stage kidney disease and by that reconfirmed its position as treatment option for diabetic kidney disease. nsMRA reduced the odds for a combined renal endpoint and did not raise any safety concerns, justifying its application.
Topics: Adult; Humans; Angiotensin-Converting Enzyme Inhibitors; Diabetic Nephropathies; Angiotensin Receptor Antagonists; Network Meta-Analysis; Sodium-Glucose Transporter 2 Inhibitors; Kidney Failure, Chronic; Angiotensins; Diabetes Mellitus
PubMed: 37917640
DOI: 10.1371/journal.pone.0293183 -
International Urology and Nephrology May 2024This review aimed to assess the utility of urinary N-acetyl-β-D-glucosaminidase (uNAG) as a prognostic biomarker for nephropathy in patients with type 2 diabetes... (Meta-Analysis)
Meta-Analysis Review
OBJECTIVE
This review aimed to assess the utility of urinary N-acetyl-β-D-glucosaminidase (uNAG) as a prognostic biomarker for nephropathy in patients with type 2 diabetes mellitus.
METHODS
The search for relevant studies was conducted across multiple databases, including PubMed (Medline), EMBASE, LILACS, CENTRAL, IBECS, and gray literature. We employed a random effects model to calculate the standardized mean difference and 95% confidence interval. Furthermore, we assessed heterogeneity using Cochrane's Q test and Higgins' I2 statistics.
RESULTS
This review included a total of 16 articles involving 1669 patients, with 13 being case-control studies and three being cohorts. The meta-analysis conducted across all studies revealed significant heterogeneity. However, subgroup analysis of four studies indicated that an increase in uNAG among normoalbuminuric patients was associated with the development of macroalbuminuria (DMP = - 1.47; 95% CI = - 1.98 to 0.95; p < 0.00001; I = 45%). Conversely, it did not demonstrate effectiveness in predicting the development of microalbuminuria (DMP = 0.26; 95% CI = - 0.08 to 0.60; p = 0.13; I = 17%).
CONCLUSIONS
Elevated uNAG levels in normoalbuminuric patients may indicate an increased risk for the development of macroalbuminuria, but not microalbuminuria. However, the high heterogeneity observed among the studies highlights the necessity for further research to validate these findings.
Topics: Humans; Diabetic Nephropathies; Diabetes Mellitus, Type 2; Acetylglucosaminidase; Prognosis; Biomarkers; Albuminuria
PubMed: 37898960
DOI: 10.1007/s11255-023-03843-3