Evidence map›Paper›PMID 26175568›Full record

ReviewKorean journal of radiology

Cardiac Magnetic Resonance Scar Imaging for Sudden Cardiac Death Risk Stratification in Patients with Non-Ischemic Cardiomyopathy.

Eun Kyoung Kim, Pairoj Chattranukulchai, Igor Klem

Open access · hybridAbstract readReview
In one paragraph

Review in Korean journal of radiology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.7field-weighted citation impact, top 10% 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

13 citing papers in PubMed, 22 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

3 authors at 3 institutions in 3 countries.

Eun Kyoung KimDivision of Cardiology, Department of Medicine, Heart Vascular Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 135-710, Korea.
Pairoj ChattranukulchaiDivision of Cardiology, Department of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Bangkok 10330, Thailand. ; Duke Cardiovascular Magnetic Resonance Center, Duke University Medical Center, Durham, NC 27710, USA.
Igor KlemDuke Cardiovascular Magnetic Resonance Center, Duke University Medical Center, Durham, NC 27710, USA. ; Division of Cardiology, Duke University Medical Center, Durham, NC 27710, USA.
Duke Medical Center · USDuke University Hospital · USSungkyunkwan University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In patients with non-ischemic cardiomyopathy (NICM), risk stratification for sudden cardiac death (SCD) and selection of patients who would benefit from prophylactic implantable cardioverter-defibrillators remains challenging. We aim to discuss the evidence of cardiac magnetic resonance (CMR)-derived myocardial scar for the prediction of adverse cardiovascular outcomes in NICM. From the 15 studies analyzed, with a total of 2747 patients, the average prevalence of myocardial scar was 41%. In patients with myocardial scar, the risk for adverse cardiac events was more than 3-fold higher, and risk for arrhythmic events 5-fold higher, as compared to patients without scar. Based on the available observational, single center studies, CMR scar assessment may be a promising new tool for SCD risk stratification, which merits further investigation.

Indexed as

Arrhythmias, CardiacCardiomyopathiesCicatrixDeath, Sudden, CardiacDefibrillators, ImplantableFemaleHumansMagnetic Resonance Imaging, CineMyocardiumRisk AssessmentRisk FactorsCardiac magnetic resonanceNon-ischemic cardiomyopathySudden cardiac death

Identifiers

PMID26175568
PMCPMC4499533
OpenAlexW2169665644

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.