↓ Skip to main content

Identifying Non-invasive Tools to Distinguish Acute Myocarditis from Dilated Cardiomyopathy in Children

Overview of attention for article published in Pediatric Cardiology, April 2018
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
41 Mendeley
Title
Identifying Non-invasive Tools to Distinguish Acute Myocarditis from Dilated Cardiomyopathy in Children
Published in
Pediatric Cardiology, April 2018
DOI 10.1007/s00246-018-1867-y
Pubmed ID
Authors

Divya Suthar, Debra A. Dodd, Justin Godown

Abstract

There is often a diagnostic dilemma in pediatric patients presenting with depressed ventricular function, as myocarditis and dilated cardiomyopathy (DCM) of other etiologies can appear very similar. Accurate identification is critical to guide treatment and to provide families with the most accurate expectation of long-term outcomes. The objective of this study was to identify patterns of clinical presentation and to assess non-invasive measures to differentiate patients with acute myocarditis from other forms of DCM. We identified all children (< 18 years) from our institution with a diagnosis of idiopathic DCM or myocarditis based on endomyocardial biopsy or explant pathology (1996-2015). Characteristics at the time of presentation were compared between patients with a definite diagnosis of myocarditis and those with idiopathic DCM. Data collected included clinical and laboratory data, radiography, echocardiography, and cardiac catheterization data. A total of 58 patients were included in the study; 46 (79%) with idiopathic DCM and 12 (21%) with acute myocarditis. Findings favoring a diagnosis of myocarditis included a history of fever (58 vs. 15%, p = 0.002), arrhythmia (17 vs. 0%, p = 0.003), higher degree of cardiac enzyme elevation, absence of left ventricular dilation (42 vs. 7%, p = 0.002), segmental wall motion abnormalities (58 vs. 13%, p = 0.001), lower left ventricular dimension z-score (3.7 vs. 5.2, p = 0.031), and less severe depression of left ventricular systolic function. There are notable differences between patients with myocarditis and other forms of DCM that can be detected non-invasively at the time of presentation without the need for endomyocardial biopsy. These data suggest that it may be possible to develop a predictive model to differentiate myocarditis from other forms of DCM using non-invasive measures.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 41 100%

Demographic breakdown

Readers by professional status Count As %
Other 5 12%
Student > Postgraduate 5 12%
Researcher 4 10%
Professor > Associate Professor 4 10%
Student > Bachelor 3 7%
Other 9 22%
Unknown 11 27%
Readers by discipline Count As %
Medicine and Dentistry 19 46%
Materials Science 2 5%
Psychology 2 5%
Neuroscience 2 5%
Unspecified 1 2%
Other 1 2%
Unknown 14 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 April 2018.
All research outputs
#18,601,965
of 23,041,514 outputs
Outputs from Pediatric Cardiology
#864
of 1,414 outputs
Outputs of similar age
#255,548
of 329,221 outputs
Outputs of similar age from Pediatric Cardiology
#19
of 44 outputs
Altmetric has tracked 23,041,514 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,414 research outputs from this source. They receive a mean Attention Score of 2.7. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 329,221 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 44 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.