ArticleEClinicalMedicine2024
Dose-response association of diabetic kidney disease with routine clinical parameters in patients with type 2 diabetes mellitus: a systematic review and meta-analysis.
Article in EClinicalMedicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Associations of metabolic score for insulin resistance with type 2 diabetes, cancer, and all-cause mortality: a meta-analysis of cohort studies.Frontiers in endocrinology · 2026Pooled it
- Protective Role of The SIGLEC14 Null Allele Against Type 2 Diabetes Mellitus: Evidence From an Egyptian Case-Control Study.Molecular biology reports · 2026Article
- Development and validation of a predictive model for diabetic kidney disease risk in patients with T2DM: a hospital data platform study.Frontiers in endocrinology · 2026Article
- Circ-0069561 as a novel diagnostic biomarker for progression of diabetic kidney disease.Renal failure · 2025Article
- An analytical pipeline for dose-response effect: laboratory tests assessment and early pregnancy preeclampsia risk.BMC pregnancy and childbirth · 2025Article
- The Contribution of Genetic Risk and Lifestyle Factors in the Progression of Diabetes to Diabetic Kidney Disease: A Prospective Cohort Study.Journal of diabetes · 2025Article
- Sex-specific and metabolic subgroup heterogeneity in high-density lipoprotein cholesterol associations with diabetic kidney disease risk: a retrospective cohort study.Lipids in health and disease · 2025Article
- Association of diabetic nephropathy with lipid metabolism: a Mendelian randomization study.Diabetology & metabolic syndrome · 2025Article
- High-Density Lipoprotein in Patients with Diabetic Kidney Disease: Friend or Foe?International journal of molecular sciences · 2025Review
- Predicting rapid decline in kidney function among type 2 diabetes patients: A machine learning approach.Heliyon · 2025Article
- Association Between DNA Methylation ofJournal of diabetes research · 2025Article
- A Machine Learning Model for Predicting Diabetic Nephropathy Based on TG/Cys-C Ratio and Five Clinical Indicators.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025Article
- Gut microbiota-derived short-chain fatty acids mediate the antifibrotic effects of traditional Chinese medicine in diabetic nephropathy.Frontiers in endocrinology · 2025Review
- Predictive value of serum uric acid-to-albumin ratio for diabetic kidney disease in patients with type 2 diabetes mellitus: a case-control study.Frontiers in endocrinology · 2025Article
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Authors and funding
17 authors.
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Abstract
Background: Diabetic kidney disease (DKD) is a leading cause of end-stage kidney disease and is associated with high mortality rates. The influence of routine clinical parameters on DKD onset in patients with type 2 diabetes mellitus (T2DM) remains uncertain. Methods: In this systematic review and meta-analysis, we searched multiple databases, including PubMed, Embase, Scopus, Web of Science, and Cochrane Library, for studies published from each database inception until January 11, 2024. We included cohort studies examining the association between DKD onset and various clinical parameters, including body mass index (BMI), hemoglobin A1c (HbA1c), systolic blood pressure (SBP), diastolic blood pressure (DBP), total cholesterol (TC), triglycerides (TG), low-density lipoprotein (LDL), high-density lipoprotein (HDL), and serum uric acid (UA). Random-effect dose-response meta-analyses utilizing one-stage and/or cubic spline models, were used to estimate correlation strength. This study is registered in PROSPERO (CRD42022326148). Findings: This analysis of 46 studies involving 317,502 patients found that in patients with T2DM, the risk of DKD onset increased by 3% per 1 kg/m Interpretation: BMI, HbA1c, SBP, TG, HDL and UA are potential predictors of DKD onset in patients with T2DM. Given high heterogeneity between included studies, our findings should be interpreted with caution, but they suggest monitoring of these clinical parameters to identify individuals who may be at risk of developing DKD. Funding: Shenzhen Science and Innovation Fund, the Hong Kong Research Grants Council, and the HKU Seed Funds, and Scientific and technological innovation project of China Academy of Chinese Medical Sciences.
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