Evidence map›Paper›PMID 26441970›Full record

ReviewFrontiers in immunology2015

Animal Models to Study Links between Cardiovascular Disease and Renal Failure and Their Relevance to Human Pathology.

Tim D Hewitson, Stephen G Holt, Edward R Smith

Abstract readReview
In one paragraph

Review in Frontiers in immunology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
–field-weighted citation impact
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

30 citing papers in PubMed.

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  10. Mesenchymal stem cells: A new therapeutic tool for chronic kidney disease.Frontiers in cell and developmental biology · 2022
    Review
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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.

Tim D HewitsonDepartment of Nephrology, Royal Melbourne Hospital (RMH) , Melbourne, VIC , Australia ; Department of Medicine - RMH, University of Melbourne , Melbourne, VIC , Australia.
Stephen G HoltDepartment of Nephrology, Royal Melbourne Hospital (RMH) , Melbourne, VIC , Australia ; Department of Medicine - RMH, University of Melbourne , Melbourne, VIC , Australia.
Edward R SmithDepartment of Nephrology, Royal Melbourne Hospital (RMH) , Melbourne, VIC , Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The close association between cardiovascular pathology and renal dysfunction is well documented and significant. Patients with conventional risk factors for cardiovascular disease like diabetes and hypertension also suffer renal dysfunction. This is unsurprising if the kidney is simply regarded as a "modified blood vessel" and thus, traditional risk factors will affect both systems. Consistent with this, it is relatively easy to comprehend how patients with either sudden or gradual cardiac and or vascular compromise have changes in both renal hemodynamic and regulatory systems. However, patients with pure or primary renal dysfunction also have metabolic changes (e.g., oxidant stress, inflammation, nitric oxide, or endocrine changes) that affect the cardiovascular system. Thus, cardiovascular and renal systems are intimately, bidirectionally and inextricably linked. Whilst we understand several of these links, some of the mechanisms for these connections remain incompletely explained. Animal models of cardiovascular and renal disease allow us to explore such mechanisms, and more importantly, potential therapeutic strategies. In this article, we review various experimental models used, and examine critically how representative they are of the human condition.

Indexed as

animal modelscardiorenal syndromeheartkidneyreview

Identifiers

PMID26441970
PMCPMC4585255

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.