Evidence map›Paper›PMID 20308998›Full record

ReviewNature reviews. Nephrology2010

HDL metabolism and activity in chronic kidney disease.

Nosratola D Vaziri, Mohamad Navab, Alan M Fogelman

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 86 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
86citing papers in PubMed, 1 pooled it
9.2field-weighted citation impact, top 1% 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

86 citing papers in PubMed, 1 synthesis or guideline pooled it, 155 citations in OpenAlex.

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26 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

3 authors at 2 institutions in 1 country.

Nosratola D VaziriDivision of Nephrology and Hypertension, School of Medicine, The City Drive, City Tower, Suite 400, Orange, CA 92868-3217, USA. ndvaziri@uci.edu
Mohamad Navab
Alan M Fogelman
University of California, Los Angeles · USHypertension Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic kidney disease (CKD) is associated with development of atherosclerosis and premature death from cardiovascular disease. The predisposition of patients with CKD to atherosclerosis is driven by inflammation, oxidative stress and dyslipidemia, all of which are common features of this condition. Markers of dyslipidemia in patients with advanced CKD are impaired clearance and heightened oxidation of apolipoprotein-B-containing lipoproteins and their atherogenic remnants, and a reduction of the plasma concentration, antioxidant, and anti-inflammatory properties of high-density lipoprotein (HDL). Studies in animal models of CKD indicate that the disease promotes lipid accumulation in the artery wall and kidney, leading to atherosclerosis, glomerulosclerosis and tubulointerstitial injury. These effects seem to be mediated by an increased cellular influx of lipids, elevated cellular production and reduced cellular catabolism of fatty acids, and impaired antioxidant, anti-inflammatory and reverse lipid transport properties of HDL. Available pharmacological therapies have been largely ineffective in ameliorating oxidative stress, inflammation, HDL deficiency and/or dysfunction, and the associated atherosclerosis and cardiovascular disease in patients with end-stage renal disease. This Review aims to provide an overview of the mechanisms and consequences of CKD-induced HDL deficiency and dysfunction.

Indexed as

AnimalsAntioxidantsAtherosclerosisDisease ProgressionDisease SusceptibilityDown-RegulationDyslipidemiasHumansKidney Failure, ChronicLipoproteins, HDLOxidative StressAntioxidantsLipoproteins, HDL

Identifiers

PMID20308998
OpenAlexW2038607614

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.