Evidence map›Paper›PMID 20440276›Full record

ReviewNature reviews. Nephrology2010

Role of triglyceride-rich lipoproteins in diabetic nephropathy.

John C Rutledge, Kit F Ng, Hnin H Aung, Dennis W Wilson

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Nephrology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 81 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
81citing papers in PubMed, 2 pooled it
4.7field-weighted citation impact, top 5% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

81 citing papers in PubMed, 2 syntheses or guidelines pooled it, 150 citations in OpenAlex.

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21 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

John C RutledgeDivision of Cardiovascular Medicine, University of California Davis School of Medicine, University of California, Davis, CA 95616, USA. jcrutledge@ucdavis.edu
Kit F Ng
Hnin H Aung
Dennis W Wilson
University of California, Davis · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetic nephropathy is an increasingly important cause of morbidity and mortality worldwide. A large body of evidence suggests that dyslipidemia has an important role in the progression of kidney disease in patients with diabetes. Lipids may induce renal injury by stimulating TGF-beta, thereby inducing the production of reactive oxygen species and causing damage to the glomeruli and glomerular glycocalyx. Findings from basic and clinical studies strongly suggest that excess amounts of a variety of lipoproteins and lipids worsens diabetes-associated microvascular and macrovascular disease, increases glomerular injury, increases tubulointerstitial fibrosis, and accelerates the progression of diabetic nephropathy. The increasing prevalence of obesity, type 2 diabetes mellitus, and diabetic nephropathy means that interventions that can interrupt the pathophysiological cascade of events induced by lipoproteins and lipids could enable major life and cost savings. This Review discusses the structural, cellular, and microscopic findings associated with diabetic nephropathy and the influence of lipoproteins, specifically triglyceride-rich lipoproteins (TGRLs), on the development and perpetuation of diabetic nephropathy. Some of the accepted and hypothesized mechanisms of renal injury relating to TGRLs are also described.

Indexed as

AnimalsDiabetic NephropathiesDyslipidemiasHumansHypolipidemic AgentsLipoproteinsTriglyceridesHypolipidemic AgentsLipoproteinslipoprotein triglycerideTriglycerides

Identifiers

PMID20440276
OpenAlexW2023130651

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.