ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2023
Serum Lipoprotein(a) and High-Density Lipoprotein Cholesterol Associate with Diabetic Nephropathy: Evidence from Machine Learning Perspectives.
Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- Risk prediction models for diabetic nephropathy among type 2 diabetes patients in China: a systematic review and meta-analysis.Frontiers in endocrinology · 2024Pooled it
- The diagnostic value of radiomics based on two-dimensional ultrasound in staging diabetic nephropathy.BMC medical imaging · 2026Article
- Association between TyHGB and hyperuricemia and gout in patients with type-2 diabetes mellitus.BMC endocrine disorders · 2026Article
- Artificial intelligence-powered prediction of diabetic complications: from clinical data to molecular omics.Briefings in bioinformatics · 2026Article
- Association between the uric acid to high-density lipoprotein cholesterol ratio and estimated glomerular filtration rate decline in community-managed patients with type 2 diabetes: a retrospective cohort study.Frontiers in nutrition · 2026Article
- Association between uric acid to high-density lipoprotein cholesterol ratio and diabetic kidney disease in US adults.Scientific reports · 2025Article
- A SMOTE PCA HDBSCAN approach for enhancing water quality classification in imbalanced datasets.Scientific reports · 2025Article
- Association of diabetic nephropathy with lipid metabolism: a Mendelian randomization study.Diabetology & metabolic syndrome · 2025Article
- Immunomodulatory roles of quercetin in diabetic nephropathy: targeting inflammation, oxidative stress, and ferroptosis.Frontiers in pharmacology · 2025Review
- The nonlinear relationship between the ratio of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol and the risk of diabetic kidney disease in patients with type 2 diabetes mellitus.Frontiers in medicine · 2025Article
- Desmosterol-driven atypical macrophage polarization regulates podocyte dynamics in diabetic nephropathy.Molecular biology reports · 2024Article
- The causal relationship between 5 serum lipid parameters and diabetic nephropathy: a Mendelian randomization study.Frontiers in endocrinology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Diabetic nephropathy (DN) is a common complication of type 2 diabetes mellitus (T2DM) that significantly impacts the quality of life for affected patients. Dyslipidemia is a known risk factor for developing cardiovascular complications in T2DM patients. However, the association between serum lipoprotein(a) (Lp(a)) and high-density lipoprotein cholesterol (HDL-C) with DN requires further investigation. Patients and Methods: For this cross-sectional study, we randomly selected T2DM patients with nephropathy (DN, n = 211) and T2DM patients without nephropathy (T2DM, n = 217) from a cohort of 142,611 patients based on predefined inclusion and exclusion criteria. We collected clinical data from the patients to identify potential risk factors for DN using binary logistic regression and machine learning. After obtaining the feature importance score of clinical indicators by building a random forest classifier, we examined the correlations between Lp(a), HDL-C and the top 10 indicators. Finally, we trained decision tree models with top 10 features using training data and evaluated their performance with independent testing data. Results: Compared to the T2DM group, the DN group had significantly higher serum levels of Lp(a) ( Conclusion: Our findings indicate that serum Lp(a) and HDL-C are associated with DN and we have provided a decision tree model with uALB as a predictor for DN.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.