Evidence map›Paper›PMID 31820004›Full record

ArticleSingapore medical journal2021

Magnetic resonance imaging of dilated cardiomyopathy: prognostic benefit of identifying late gadolinium enhancement in Asian patients.

Anna Nogue Infante, Christopher Chieh Yang Koo, Alfred Yip, Ying Ha Lim, Wee Tiong Yeo, Swee Tian Quek, Toon Wei Lim, Swee Chong Seow, Ping Chai, Ching Ching Ong and 3 more

Abstract read
In one paragraph

Article in Singapore medical journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 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

5 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Prediction of ventricular arrhythmias and sudden cardiac death by quantification and location of late gadolinium enhancement on cardiac magnetic resonance: a systematic review and meta-analysis.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2025
    Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. 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

13 authors.

Anna Nogue InfanteDepartment of Biomedical Engineering, Universitat Pompeu Fabra, Barcelona, Spain.
Christopher Chieh Yang KooDepartment of Cardiology, National University Heart Centre Singapore, Singapore.
Alfred YipDepartment of Cardiology, National University Heart Centre Singapore, Singapore.
Ying Ha LimDepartment of Cardiology, National University Heart Centre Singapore, Singapore.
Wee Tiong YeoDepartment of Cardiology, National University Heart Centre Singapore, Singapore.
Swee Tian QuekDepartment of Diagnostic Imaging, National University Hospital, Singapore.
Toon Wei LimDepartment of Cardiology, National University Heart Centre Singapore, Singapore.
Swee Chong SeowDepartment of Cardiology, National University Heart Centre Singapore, Singapore.
Ping ChaiDepartment of Cardiology, National University Heart Centre Singapore, Singapore.
Ching Ching OngDepartment of Diagnostic Imaging, National University Hospital, Singapore.
Lynette TeoDepartment of Diagnostic Imaging, National University Hospital, Singapore.
Devinder SinghDepartment of Cardiology, National University Heart Centre Singapore, Singapore.
Pipin KojodjojoDepartment of Cardiology, National University Heart Centre Singapore, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionRisk stratification in dilated cardiomyopathy (DCM) is imprecise, relying largely on echocardiographic left ventricular ejection fraction (LVEF) and severity of heart failure symptoms. Adverse cardiovascular events are increased by the presence of myocardial scarring. Late gadolinium enhancement (LGE) on cardiovascular magnetic resonance (CMR) imaging is the gold standard for identifying myocardial scars. We examined the association between LGE on CMR imaging and adverse clinical outcomes during long-term follow-up of Asian patients with DCM.

methodsConsecutive patients with DCM undergoing CMR imaging at a single Asian academic medical centre between 2005 and 2015 were recruited. Clinical outcomes were tracked using comprehensive electronic medical records and mortality was determined by cross-linkages with national registries. Presence and distribution of LGE on CMR imaging were determined by investigators blinded to patient outcomes. Primary endpoint was a composite of heart failure hospitalisations, appropriate implantable cardioverter-defibrillator shocks and cardiovascular mortality.

resultsOf 86 patients, 64.0% had LGE (80.2% male; mean LVEF 30.1% ± 12.7%). Mid-wall fibrosis (71.7%) was the most common pattern of LGE distribution. Over a mean follow-up period of 4.9 ± 3.2 years, 19 (34.5%) patients with LGE reached the composite endpoint compared to 4 (12.9%) patients without LGE (p = 0.01). Presence of LGE, but not echocardiographic LVEF, independently predicted the primary endpoint (hazard ratio 4.15 [95% confidence interval 1.28-13.50]; p = 0.02).

conclusionLGE presence independently predicted adverse clinical events in Asian patients with DCM. Routine use of CMR imaging to characterise the myocardial substrate is recommended for enhanced risk stratification and should strongly influence clinical management.

Indexed as

Cardiomyopathy, DilatedGadoliniumContrast MediaFemaleHumansMagnetic Resonance ImagingMagnetic Resonance Imaging, CineMalePredictive Value of TestsPrognosisStroke VolumeVentricular Function, LeftContrast MediaGadoliniumdilated cardiomyopathymagnetic resonance imagingprognosis

Identifiers

PMID31820004
PMCPMC8801841

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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.