↓ Skip to main content

Feasibility of Ultra-Rapid Exome Sequencing in Critically Ill Infants and Children With Suspected Monogenic Conditions in the Australian Public Health Care System

Overview of attention for article published in JAMA: Journal of the American Medical Association, June 2020
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (56th percentile)

Mentioned by

news
4 news outlets
twitter
144 tweeters

Citations

dimensions_citation
9 Dimensions

Readers on

mendeley
43 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Feasibility of Ultra-Rapid Exome Sequencing in Critically Ill Infants and Children With Suspected Monogenic Conditions in the Australian Public Health Care System
Published in
JAMA: Journal of the American Medical Association, June 2020
DOI 10.1001/jama.2020.7671
Pubmed ID
Authors

Sebastian Lunke, Stefanie Eggers, Meredith Wilson, Chirag Patel, Christopher P. Barnett, Jason Pinner, Sarah A. Sandaradura, Michael F. Buckley, Emma I. Krzesinski, Michelle G. de Silva, Gemma R. Brett, Kirsten Boggs, David Mowat, Edwin P. Kirk, Lesley C. Adès, Lauren S. Akesson, David J. Amor, Samantha Ayres, Anne Baxendale, Sarah Borrie, Alessandra Bray, Natasha J. Brown, Cheng Yee Chan, Belinda Chong, Corrina Cliffe, Martin B. Delatycki, Matthew Edwards, George Elakis, Michael C. Fahey, Andrew Fennell, Lindsay Fowles, Lyndon Gallacher, Megan Higgins, Katherine B. Howell, Lauren Hunt, Matthew F. Hunter, Kristi J. Jones, Sarah King, Smitha Kumble, Sarah Lang, Maelle Le Moing, Alan Ma, Dean Phelan, Michael C. J. Quinn, Anna Richards, Christopher M. Richmond, Jessica Riseley, Jonathan Rodgers, Rani Sachdev, Simon Sadedin, Luregn J. Schlapbach, Janine Smith, Amanda Springer, Natalie B. Tan, Tiong Y. Tan, Suzanna L. Temple, Christiane Theda, Anand Vasudevan, Susan M. White, Alison Yeung, Ying Zhu, Melissa Martyn, Stephanie Best, Tony Roscioli, John Christodoulou, Zornitza Stark

Twitter Demographics

The data shown below were collected from the profiles of 144 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 43 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 21%
Other 8 19%
Researcher 7 16%
Student > Master 3 7%
Student > Doctoral Student 3 7%
Other 6 14%
Unknown 7 16%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 13 30%
Medicine and Dentistry 11 26%
Neuroscience 2 5%
Computer Science 2 5%
Nursing and Health Professions 2 5%
Other 6 14%
Unknown 7 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 113. 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 02 December 2020.
All research outputs
#201,035
of 16,641,846 outputs
Outputs from JAMA: Journal of the American Medical Association
#3,200
of 28,834 outputs
Outputs of similar age
#7,803
of 293,728 outputs
Outputs of similar age from JAMA: Journal of the American Medical Association
#186
of 422 outputs
Altmetric has tracked 16,641,846 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 28,834 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 62.7. This one has done well, scoring higher than 88% 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 293,728 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 97% of its contemporaries.
We're also able to compare this research output to 422 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 56% of its contemporaries.