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Diagnosis of Kawasaki Disease Using a Minimal Whole-Blood Gene Expression Signature

Overview of attention for article published in JAMA Pediatrics, October 2018
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

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15 news outlets
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113 X users
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1 patent
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5 Facebook pages
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1 Google+ user

Citations

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91 Dimensions

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102 Mendeley
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Title
Diagnosis of Kawasaki Disease Using a Minimal Whole-Blood Gene Expression Signature
Published in
JAMA Pediatrics, October 2018
DOI 10.1001/jamapediatrics.2018.2293
Pubmed ID
Authors

Victoria J. Wright, Jethro A. Herberg, Myrsini Kaforou, Chisato Shimizu, Hariklia Eleftherohorinou, Hannah Shailes, Anouk M. Barendregt, Stephanie Menikou, Stuart Gormley, Maurice Berk, Long Truong Hoang, Adriana H. Tremoulet, John T. Kanegaye, Lachlan J. M. Coin, Mary P. Glodé, Martin Hibberd, Taco W. Kuijpers, Clive J. Hoggart, Jane C. Burns, Michael Levin

Abstract

To date, there is no diagnostic test for Kawasaki disease (KD). Diagnosis is based on clinical features shared with other febrile conditions, frequently resulting in delayed or missed treatment and an increased risk of coronary artery aneurysms. To identify a whole-blood gene expression signature that distinguishes children with KD in the first week of illness from other febrile conditions. The case-control study comprised a discovery group that included a training and test set and a validation group of children with KD or comparator febrile illness. The setting was pediatric centers in the United Kingdom, Spain, the Netherlands, and the United States. The training and test discovery group comprised 404 children with infectious and inflammatory conditions (78 KD, 84 other inflammatory diseases, and 242 bacterial or viral infections) and 55 healthy controls. The independent validation group comprised 102 patients with KD, including 72 in the first 7 days of illness, and 130 febrile controls. The study dates were March 1, 2009, to November 14, 2013, and data analysis took place from January 1, 2015, to December 31, 2017. Whole-blood gene expression was evaluated using microarrays, and minimal transcript sets distinguishing KD were identified using a novel variable selection method (parallel regularized regression model search). The ability of transcript signatures (implemented as disease risk scores) to discriminate KD cases from controls was assessed by area under the curve (AUC), sensitivity, and specificity at the optimal cut point according to the Youden index. Among 404 patients in the discovery set, there were 78 with KD (median age, 27 months; 55.1% male) and 326 febrile controls (median age, 37 months; 56.4% male). Among 202 patients in the validation set, there were 72 with KD (median age, 34 months; 62.5% male) and 130 febrile controls (median age, 17 months; 56.9% male). A 13-transcript signature identified in the discovery training set distinguished KD from other infectious and inflammatory conditions in the discovery test set, with AUC of 96.2% (95% CI, 92.5%-99.9%), sensitivity of 81.7% (95% CI, 60.0%-94.8%), and specificity of 92.1% (95% CI, 84.0%-97.0%). In the validation set, the signature distinguished KD from febrile controls, with AUC of 94.6% (95% CI, 91.3%-98.0%), sensitivity of 85.9% (95% CI, 76.8%-92.6%), and specificity of 89.1% (95% CI, 83.0%-93.7%). The signature was applied to clinically defined categories of definite, highly probable, and possible KD, resulting in AUCs of 98.1% (95% CI, 94.5%-100%), 96.3% (95% CI, 93.3%-99.4%), and 70.0% (95% CI, 53.4%-86.6%), respectively, mirroring certainty of clinical diagnosis. In this study, a 13-transcript blood gene expression signature distinguished KD from other febrile conditions. Diagnostic accuracy increased with certainty of clinical diagnosis. A test incorporating the 13-transcript disease risk score may enable earlier diagnosis and treatment of KD and reduce inappropriate treatment in those with other diagnoses.

X Demographics

X Demographics

The data shown below were collected from the profiles of 113 X users 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 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 102 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 15%
Student > Ph. D. Student 11 11%
Student > Doctoral Student 8 8%
Student > Postgraduate 7 7%
Student > Master 7 7%
Other 22 22%
Unknown 32 31%
Readers by discipline Count As %
Medicine and Dentistry 44 43%
Biochemistry, Genetics and Molecular Biology 11 11%
Agricultural and Biological Sciences 5 5%
Nursing and Health Professions 1 <1%
Computer Science 1 <1%
Other 3 3%
Unknown 37 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 179. 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 10 September 2020.
All research outputs
#227,297
of 25,727,480 outputs
Outputs from JAMA Pediatrics
#653
of 6,755 outputs
Outputs of similar age
#4,571
of 356,413 outputs
Outputs of similar age from JAMA Pediatrics
#16
of 89 outputs
Altmetric has tracked 25,727,480 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,755 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 79.4. This one has done particularly well, scoring higher than 90% of its peers.
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 356,413 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 89 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.