Evidence map›Paper›PMID 26720041›Full record

ArticlePloS one2015

miRNA-197 and miRNA-223 Predict Cardiovascular Death in a Cohort of Patients with Symptomatic Coronary Artery Disease.

Christian Schulte, Simon Molz, Sebastian Appelbaum, Mahir Karakas, Francisco Ojeda, Denise M Lau, Tim Hartmann, Karl J Lackner, Dirk Westermann, Renate B Schnabel and 2 more

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 100 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
100citing papers in PubMed, 3 pooled it
–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

100 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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40 more citing papers are in PubMed but not listed here.

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

12 authors.

Christian SchulteDepartment of General and Interventional Cardiology, University Heart Center Hamburg Eppendorf, Hamburg, Germany.
Simon MolzDepartment of General and Interventional Cardiology, University Heart Center Hamburg Eppendorf, Hamburg, Germany.
Sebastian AppelbaumDepartment of General and Interventional Cardiology, University Heart Center Hamburg Eppendorf, Hamburg, Germany.
Mahir KarakasDepartment of General and Interventional Cardiology, University Heart Center Hamburg Eppendorf, Hamburg, Germany.
Francisco OjedaDepartment of General and Interventional Cardiology, University Heart Center Hamburg Eppendorf, Hamburg, Germany.
Denise M LauDepartment of General and Interventional Cardiology, University Heart Center Hamburg Eppendorf, Hamburg, Germany.
Tim HartmannDepartment of General and Interventional Cardiology, University Heart Center Hamburg Eppendorf, Hamburg, Germany.
Karl J LacknerInstitute of Clinical Chemistry and Laboratory Medicine, University Medical Center Mainz, Mainz, Germany.
Dirk WestermannDepartment of General and Interventional Cardiology, University Heart Center Hamburg Eppendorf, Hamburg, Germany.
Renate B SchnabelDepartment of General and Interventional Cardiology, University Heart Center Hamburg Eppendorf, Hamburg, Germany.
Stefan BlankenbergDepartment of General and Interventional Cardiology, University Heart Center Hamburg Eppendorf, Hamburg, Germany.
Tanja ZellerDepartment of General and Interventional Cardiology, University Heart Center Hamburg Eppendorf, Hamburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCirculating microRNAs (miRNAs) have been described as potential diagnostic biomarkers in cardiovascular disease and in particular, coronary artery disease (CAD). Few studies were undertaken to perform analyses with regard to risk stratification of future cardiovascular events. miR-126, miR-197 and miR-223 are involved in endovascular inflammation and platelet activation and have been described as biomarkers in the diagnosis of CAD. They were identified in a prospective study in relation to future myocardial infarction.

objectivesThe aim of our study was to further evaluate the prognostic value of these miRNAs in a large prospective cohort of patients with documented CAD.

methodsLevels of miR-126, miR-197 and miR-223 were evaluated in serum samples of 873 CAD patients with respect to the endpoint cardiovascular death. miRNA quantification was performed using real time polymerase chain reaction (RT-qPCR).

resultsThe median follow-up period was 4 years (IQR 2.78-5.04). The median age of all patients was 64 years (IQR 57-69) with 80.2% males. 38.9% of the patients presented with acute coronary syndrome (ACS), 61.1% were diagnosed with stable angina pectoris (SAP). Elevated levels of miRNA-197 and miRNA-223 reliably predicted future cardiovascular death in the overall group (miRNA-197: hazard ratio (HR) 1.77 per one standard deviation (SD) increase (95% confidence interval (CI) 1.20; 2.60), p = 0.004, C-index 0.78; miRNA-223: HR 2.23 per one SD increase (1.20; 4.14), p = 0.011, C-index 0.80). In ACS patients the prognostic power of both miRNAs was even higher (miRNA-197: HR 2.24 per one SD increase (1.25; 4.01), p = 0.006, C-index 0.89); miRA-223: HR 4.94 per one SD increase (1.42; 17.20), p = 0.012, C-index 0.89).

conclusionSerum-derived circulating miRNA-197 and miRNA-223 were identified as predictors for cardiovascular death in a large patient cohort with CAD. These results reinforce the assumption that circulating miRNAs are promising biomarkers with prognostic value with respect to future cardiovascular events.

Indexed as

AgedBiomarkersCoronary Artery DiseaseFemaleFollow-Up StudiesHumansKaplan-Meier EstimateMaleMicroRNAsMiddle AgedPatient Outcome AssessmentPrognosisProportional Hazards ModelsProspective StudiesRisk FactorsBiomarkersMicroRNAsMIR223, humanMIRN197 microRNA, human

Identifiers

PMID26720041
PMCPMC4699820

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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.