Evidence map›Paper›PMID 34343625›Full record

ArticleTranslational research : the journal of laboratory and clinical medicine2021

Comparison of proteomic methods in evaluating biomarker-AKI associations in cardiac surgery patients.

Richard X Liu, Heather R Thiessen-Philbrook, Ramachandran S Vasan, Josef Coresh, Peter Ganz, Joseph V Bonventre, Paul L Kimmel, Chirag R Parikh

Open access · greenAbstract readComparative StudyMulticenter Study
In one paragraph

Article in Translational research : the journal of laboratory and clinical medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
3.6field-weighted citation impact, top 6% 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

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Review
  5. Review
  6. Proteome-Wide Genetic Investigation of Large Artery Stiffness.JACC. Basic to translational science · 2024
    Article
  7. Article
  8. Article
  9. Review
  10. MS-Based Proteomics of Body Fluids: The End of the Beginning.Molecular & cellular proteomics : MCP · 2023
    Article
  11. Article
  12. Article
  13. Article
  14. High-throughput proteomics: a methodological mini-review.Laboratory investigation; a journal of technical methods and pathology · 2022
    Review
  15. Article
  16. Article
  17. Article
  18. Review
  19. Review
  20. Proteomics in thrombosis research.Research and practice in thrombosis and haemostasis · 2022
    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

8 authors at 6 institutions in 1 country.

Richard X LiuDivision of Nephrology, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Heather R Thiessen-PhilbrookDivision of Nephrology, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Ramachandran S VasanDepartments of Medicine and Epidemiology, Boston University Schools of Medicine and Public Health, Boston, Massachusetts.
Josef CoreshDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, Maryland.
Peter GanzDivision of Cardiology, Zuckerberg San Francisco General Hospital and University of California, San Francisco, California.
Joseph V BonventreDivision of Renal Medicine, Brigham and Women's Hospital, Boston, Massachusetts; Department of Medicine, Harvard Medical School, Boston, Massachusetts.
Paul L KimmelNational Institute of Diabetes, Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland.
Chirag R ParikhDivision of Nephrology, Johns Hopkins University School of Medicine, Baltimore, Maryland. Electronic address: chirag.parikh@jhmi.edu.
Johns Hopkins University · USBoston Public Schools · USHarvard University · USJohns Hopkins Medicine · USNational Institute of Diabetes and Digestive and Kidney Diseases · USSan Francisco General Hospital · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
FRAMINGHAM HEART STUDY - YEAR 5 EXAM75N92019D00031 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI RAMACHANDRAN, VASAN · 2019 to 2024
$29.8M
Renal Physiology and Phenotyping CoreP30DK079310 · NIDDK · YALE UNIVERSITY · PI ARONSON, PETER S. · 2008 to 2022
$16.8M
Novel Biomarkers in Cardiac Surgery to Detect Acute Kidney InjuryR01HL085757 · NHLBI · YALE UNIVERSITY · PI PARIKH, CHIRAG R · 2007 to 2019
$10.3M
KIDNEY INJURY MOLECULE-1 IN EPITHELIAL REPAIRR01DK072381 · NIDDK · BRIGHAM AND WOMEN'S HOSPITAL · PI BONVENTRE, JOSEPH VINCENT · 2005 to 2025
$8.6M
Urinary Biomarkers of Chronic Kidney Disease Pathology and ProgressionU01DK085660 · NIDDK · BRIGHAM AND WOMEN'S HOSPITAL · PI BONVENTRE, JOSEPH VINCENT, WAIKAR, SUSHRUT S. · 2009 to 2019
$5.3M
Progression of Acute Kidney Injury to Chronic Kidney DiseaseU01DK082185 · NIDDK · YALE UNIVERSITY · PI PARIKH, CHIRAG R · 2008 to 2017
$5.1M
Plasma Proteome and Risk of Alzheimer Dementia and Related Endophenotypes in the Framingham StudyRF1AG063507 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI GERSZTEN, ROBERT E, RAMACHANDRAN, VASAN S · 2019 to 2019
$4.2M
Proteomic Pathway Discovery in Cardiovascular DiseaseR01HL132320 · NHLBI · BETH ISRAEL DEACONESS MEDICAL CENTER · PI GERSZTEN, ROBERT E, RAMACHANDRAN, VASAN S · 2016 to 2019
$3.4M
Leveraging Clinical Trials of Diabetic Kidney Disease to Advance BiomarkersU01DK106962 · NIDDK · YALE UNIVERSITY · PI COCA, STEVEN G, PARIKH, CHIRAG R · 2015 to 2019
$1.3M
AKI Matched Phenotype Linked Evaluation with Tissue (AMPLE-Tissue)UH3DK114866 · NIDDK · JOHNS HOPKINS UNIVERSITY · PI PARIKH, CHIRAG R · 2019 to 2021
$900k
THE FRAMINGHAM HEART STUDY-N01HC25195-268025195-268025195N01HC025195 · HC · TRUSTEES OF BOSTON UNIVERSITY · PI WOLF, PHILIP A · 2002 to 2006
–
NCATS NIH HHS UL1 TR001863NHLBI NIH HHS 75N92019D00031NHLBI NIH HHS HHSN268201500001CNHLBI NIH HHS HHSN268201500001INHLBI NIH HHS N01 HC025195NHLBI NIH HHS R01 HL085757NHLBI NIH HHS R01 HL132320NIA NIH HHS RF1 AG063507NIDDK NIH HHS P30 DK079310NIDDK NIH HHS R01 DK072381NIDDK NIH HHS U01 DK082185NIDDK NIH HHS U01 DK085660NIDDK NIH HHS U01 DK106962NIDDK NIH HHS UH3 DK114866
6 · The paper itself

Abstract

Although immunoassays are the most widely used protein measurement method, aptamer-based methods such as the SomaScan platform can quantify up to 7000 proteins per biosample, creating new opportunities for unbiased discovery. However, there is limited research comparing the consistency of biomarker-disease associations between immunoassay and aptamer-based platforms. In a substudy of the TRIBE-AKI cohort, preoperative and postoperative plasma samples from 294 patients with previous immunoassay measurements were analyzed using the SomaScan platform. Inter-platform Spearman correlations (r

Indexed as

Acute Kidney InjuryAgedAged, 80 and overAptamers, PeptideBiomarkersBlood Chemical AnalysisBlood ProteinsCardiac Surgical ProceduresFemaleHumansImmunoassayMaleMiddle AgedPreoperative PeriodProteomicsAptamers, PeptideBiomarkersBlood Proteins

Identifiers

PMID34343625
PMCPMC8572170
OpenAlexW3187584935

What OpenQuestion holds

Textmetadata
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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.