Evidence map›Paper›PMID 23776353›Full record

ArticleThe application of clinical genetics2010

Genetic contribution and associated pathophysiology in end-stage renal disease.

Suraksha Agrawal, Ss Agarwal, Sita Naik

Open access · goldAbstract read
In one paragraph

Article in The application of clinical genetics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.4field-weighted citation impact, top 23% 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

5 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Observational
  5. Article
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 1 institution in 1 country.

Suraksha AgrawalDepartment of Medical Genetics, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, India.
Ss Agarwal
Sita Naik
Sanjay Gandhi Post Graduate Institute of Medical Sciences · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

End-stage renal disease (ESRD) or chronic kidney disease (CKD) is the terminal state of the kidney when its function has been permanently and irreversibly damaged. A wide variety of etiologies and pathological processes culminate in ESRD, and both environmental and genetic factors contribute to its development and progression. Various reports suggest that susceptibility to develop ESRD has a significant genetic component. These studies include familial aggregation studies, comparisons of incidence rates between different racial or ethnic populations, and segregation analysis. Genetic approaches have been used to identify genes that contribute to genetic susceptibility. Many studies have now been carried out assessing the contribution of specific "candidate genes", which correlate with different functions that are involved in the renal pathogenesis. Independent studies for specific associated genes have frequently provided contradictory results. This may be due, in part, to the modest contribution to genetic susceptibility which these genes impart. With the availability of different genomewide association studies, chromosomal regions harboring novel, previously unrecognized, genes that may contribute to renal diseases have been recently reported. We have focused on different genetic studies conducted on ESRD and have discussed the strength and weaknesses of these studies. The nonmuscle myosin heavy chain 9 gene (MYH9) and renin-angiotensin system (RAS) have been discussed in detail.

Indexed as

end-stage renal diseasegenetic polymorphism MYH9genome-wide analysis (WGA or GWA)renin-angiotensin system (RAS)

Identifiers

PMID23776353
PMCPMC3681165
OpenAlexW2018847186

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.