Evidence map›Paper›PMID 28207922›Full record

ReviewMolecular bioSystems2017

Mass spectrometry for the discovery of biomarkers of sepsis.

Katelyn R Ludwig, Amanda B Hummon

Abstract readReview
In one paragraph

Review in Molecular bioSystems, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed
3.7field-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

51 citing papers in PubMed, 92 citations in OpenAlex.

  1. Metabolic footprint of sepsis and septic shock: A narrative review.World journal of critical care medicine · 2026
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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

2 authors at 1 institution in 2 countries.

Katelyn R LudwigDepartment of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN, USA. ahummon@nd.edu.
Amanda B HummonDepartment of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN, USA. ahummon@nd.edu.ORCID http://orcid.org/0000-0002-1969-9013
University of Notre Dame · US

Funding

Spatial SILAC: Examining the Proteome in 3D Cell CulturesR01GM110406 · NIGMS · UNIVERSITY OF NOTRE DAME · PI HUMMON, AMANDA B. · 2014 to 2022
$3.0M
NIGMS NIH HHS R01 GM110406
6 · The paper itself

Abstract

Sepsis is a serious medical condition that occurs in 30% of patients in intensive care units (ICUs). Early detection of sepsis is key to prevent its progression to severe sepsis and septic shock, which can cause organ failure and death. Diagnostic criteria for sepsis are nonspecific and hinder a timely diagnosis in patients. Therefore, there is currently a large effort to detect biomarkers that can aid physicians in the diagnosis and prognosis of sepsis. Mass spectrometry is often the method of choice to detect metabolomic and proteomic changes that occur during sepsis progression. These "omics" strategies allow for untargeted profiling of thousands of metabolites and proteins from human biological samples obtained from septic patients. Differential expression of or modifications to these metabolites and proteins can provide a more reliable source of diagnostic biomarkers for sepsis. Here, we focus on the current knowledge of biomarkers of sepsis and discuss the various mass spectrometric technologies used in their detection. We consider studies of the metabolome and proteome and summarize information regarding potential biomarkers in both general and neonatal sepsis.

Indexed as

Mass SpectrometryMetabolomeMetabolomicsProteomeProteomicsAge FactorsAnimalsBiomarkersDisease ProgressionHumansSepsisBiomarkersProteome

Identifiers

PMID28207922
PMCPMC5373965
OpenAlexW2586078640

What OpenQuestion holds

Textmetadata
LicenceTDM
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.