ArticleClinical kidney journal2021
Advanced lipoprotein parameters could better explain atheromatosis in non-diabetic chronic kidney disease patients.
Article in Clinical kidney journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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
5 citing papers in PubMed.
- Effect of HDL disk and LDL dimer presence on lipoprotein particle number determination and subclassification.Analytical and bioanalytical chemistry · 2026Article
- Hypertriglyceridemia in chronic kidney disease: pathophysiological mechanisms, cardiovascular risk, and emerging therapeutics.Lipids in health and disease · 2026Review
- Therapeutic effect and potential mechanism of Fufang Danshen dripping pills for stable coronary heart disease: a randomized controlled trial.Frontiers in cardiovascular medicine · 2025Article
- Lipid Profile and Cardiovascular Risk Modification after Hepatitis C Virus Eradication.Pathogens (Basel, Switzerland) · 2024Review
- Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundChronic kidney disease (CKD) patients have a high burden of atheromatous cardiovascular disease (ASCVD) not fully explained by traditional lipid parameters. Lipoprotein composition and subclass particle number information could improve ASCVD risk assessment. The objective of this study is to investigate the association of advanced lipoprotein parameters with the risk of atheromatosis in a subpopulation of the NEFRONA study.
methodsThis was a cross-sectional study in 395 non-diabetic individuals (209 CKD and 186 non-diabetic and non-CKD) without statin therapy. Vascular ultrasound examination assessing 10 territories was combined with advanced lipoprotein testing performed by nuclear magnetic resonance spectroscopy. Logistic regression was used to estimate adjusted odds ratios (ORs) per 1 standard deviation increment.
resultsAtheromatosis was more prevalent in CKD patients (33.9% versus 64.6%). After adjusting for age, gender, smoking habit and CKD stage, the amount of triglycerides (TGs) within low-density lipoprotein (LDL) lipoproteins was independently and positively associated with atheromatosis [OR 1.33; 95% confidence interval (CI) 1.03-1.74; P = 0.03]. Similarly, total and medium LDL particles (LDL-Ps) showed a positive association (OR 1.29; 95% CI 1.00-1.68; P = 0.05 and OR 1.34; 95% CI 1.04-1.75; P = 0.03, respectively). TG-loaded medium LDL-Ps were higher in CKD patients compared with controls and showed an adjusted OR of 1.40 (95% CI 1.09-1.82; P = 0.01) in non-diabetic patients (CKD and non-CKD individuals). In contrast, non-diabetic CKD patients showed a similar coefficient but the significance was lost (OR 1.2; 95% CI 0.8-1.7; P = 0.359).
conclusionsNon-diabetic CKD patients showed a higher amount of TG-loaded medium LDL-Ps compared with controls. These particles were independently associated with atheromatosis in non-diabetic patients.
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.