Evidence map›Paper›PMID 19859072›Full record

ReviewNature reviews. Nephrology2009

Application of proteomic analysis to the study of renal diseases.

Matthew P Welberry Smith, Rosamonde E Banks, Steven L Wood, Andrew J P Lewington, Peter J Selby

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Nephrology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Trial
  2. Review
  3. Article
  4. Review
  5. Article
  6. Systems biology of kidney diseases.Kidney international · 2012
    Review
  7. Review
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

5 authors.

Matthew P Welberry SmithDepartment of Renal Medicine, St James's University Hospital, Leeds, UK. mattws1@google-mail.com
Rosamonde E Banks
Steven L Wood
Andrew J P Lewington
Peter J Selby

Funding

Medical Research Council G0701382
6 · The paper itself

Abstract

Proteomics-based approaches are generating considerable data in clinical nephrology covering almost all aspects of the discipline. Proteomic experiments commonly involve fractionation and protein separation, followed by mass spectrometric analysis to identify proteins and peptides. Biostatistical and bioinformatical input is essential in such experiments, from initial experimental design to analysis of data. Standardization of procedures is an important research objective. Depending on study design, results can lead to biomarker discovery, mechanistic insight and identification of potential avenues for therapeutic intervention and treatment evaluation. Understanding proteomic information and its place in current clinical research and practice is fundamental. This Review describes proteomic experimentation and the concepts behind it, and gives an overview of its application to important areas in clinical nephrology including acute kidney injury, chronic kidney disease, end-stage renal disease, genetic diseases and fluid and electrolyte disorders, with a particular focus on biomarker discovery. The importance of future developments, such as the establishment of an infrastructure for a 'biomarker pipeline' with structured validation pathways for candidate biomarkers and development of clinical assays, is also discussed and some future perspectives are presented.

Indexed as

HumansKidneyKidney DiseasesProteomics

Identifiers

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.