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Effect of a sepsis prediction algorithm on patient mortality, length of stay and readmission: a prospective multicentre clinical outcomes evaluation of real-world patient data from US hospitals

Overview of attention for article published in BMJ Health & Care Informatics, April 2020
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#15 of 512)
  • High Attention Score compared to outputs of the same age (95th percentile)

Mentioned by

news
8 news outlets
policy
2 policy sources
twitter
9 X users

Readers on

mendeley
102 Mendeley
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Title
Effect of a sepsis prediction algorithm on patient mortality, length of stay and readmission: a prospective multicentre clinical outcomes evaluation of real-world patient data from US hospitals
Published in
BMJ Health & Care Informatics, April 2020
DOI 10.1136/bmjhci-2019-100109
Pubmed ID
Authors

Hoyt Burdick, Eduardo Pino, Denise Gabel-Comeau, Andrea McCoy, Carol Gu, Jonathan Roberts, Sidney Le, Joseph Slote, Emily Pellegrini, Abigail Green-Saxena, Jana Hoffman, Ritankar Das

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
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 %
Student > Ph. D. Student 12 12%
Researcher 9 9%
Student > Master 8 8%
Other 7 7%
Student > Bachelor 6 6%
Other 18 18%
Unknown 42 41%
Readers by discipline Count As %
Medicine and Dentistry 22 22%
Computer Science 13 13%
Nursing and Health Professions 5 5%
Engineering 5 5%
Biochemistry, Genetics and Molecular Biology 3 3%
Other 11 11%
Unknown 43 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 67. 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 01 August 2023.
All research outputs
#673,244
of 26,397,269 outputs
Outputs from BMJ Health & Care Informatics
#15
of 512 outputs
Outputs of similar age
#19,787
of 412,428 outputs
Outputs of similar age from BMJ Health & Care Informatics
#1
of 4 outputs
Altmetric has tracked 26,397,269 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 512 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.0. This one has done particularly well, scoring higher than 97% 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 412,428 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 95% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them