Evidence map›Paper›PMID 28147324›Full record

ArticleOncotarget2017

Identification of novel biomarkers for prediction of neurological prognosis following cardiac arrest.

Jung Woo Eun, Hee Doo Yang, Soo Hyun Kim, Sungyoup Hong, Kyu Nam Park, Suk Woo Nam, Sikyoung Jeong

Open access · diamondAbstract read
In one paragraph

Article in Oncotarget, 2017. 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
1.4field-weighted citation impact, top 20% 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

7 citing papers in PubMed, 9 citations in OpenAlex.

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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

7 authors at 1 institution in 1 country.

Jung Woo EunDepartment of Pathology, Functional RNomics Research Center, Cancer Evolution Research Center, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Hee Doo YangDepartment of Pathology, Functional RNomics Research Center, Cancer Evolution Research Center, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Soo Hyun KimDepartment of Emergency Medicine, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Sungyoup HongDepartment of Emergency Medicine, College of Medicine, The Catholic University of Korea, Daejeon, Republic of Korea.
Kyu Nam ParkDepartment of Emergency Medicine, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Suk Woo NamDepartment of Pathology, Functional RNomics Research Center, Cancer Evolution Research Center, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Sikyoung JeongDepartment of Emergency Medicine, College of Medicine, The Catholic University of Korea, Daejeon, Republic of Korea.
Catholic University of Korea · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEarly prognostication of neurological outcome in comatose patients after cardiac arrest (CA) is important for devising patient treatment strategies. However, there is still a lack of sensitive and specific biomarkers for easy identification of these patients. We evaluated whether molecular signatures from blood of CA patients might help to improve the prediction of neurological outcome.

methodsWe examined 22 comatose patients resuscitated after CA and obtained peripheral blood samples 48 hours after CA. To identify novel blood biomarkers, we aimed to measure neurological outcomes according to the Cerebral Performance Category (CPC) score at 6 months after CA and to determine blood transcriptome-based molecular signature of poor neurological outcome group.

resultsAccording to the CPC score, 10 patients exhibited a CPC score of one and 12 patients, a CPC score four to five. Blood transcriptomics revealed differently expressed profiles between the good outcome group and poor outcome group. A total of 150 genes were down-regulated and 237 genes were up-regulated in the poor neurological outcome group compared with good outcome group. From the blood transcriptome-based signatures, we identified that MAPK3, BCL2 and AKT1 were more specific and sensitive diagnostic biomarkers in poor neurological outcome with an area under the curve of 0.867 (p<0.0001), 0.800 (p=0.003), and 0.767 (p=0.016) respectively.

conclusionsWe identify three biomarkers as potential predictors of neurological outcome following CA. Further assessment of the prognostic value of transcriptomic analysis in larger cohorts of CA patients is needed.

Indexed as

BiomarkersCluster AnalysisComaFemaleGene Expression ProfilingHeart ArrestHumansMaleMiddle AgedMitogen-Activated Protein Kinase 3Outcome Assessment, Health CarePredictive Value of TestsPrognosisProto-Oncogene Proteins c-aktProto-Oncogene Proteins c-bcl-2ResuscitationAKT1 protein, humanBiomarkersMitogen-Activated Protein Kinase 3Proto-Oncogene Proteins c-aktProto-Oncogene Proteins c-bcl-2cardiac arrestcerebral performance categorymolecular signatureneurological prognosisPathology Sectionperipheral blood transcriptome

Identifiers

PMID28147324
PMCPMC5369953
OpenAlexW2581303167

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.