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Comparison of risk prediction scoring systems for ward patients: a retrospective nested case control study

Overview of attention for article published in Critical Care, June 2014
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (52nd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
5 tweeters

Citations

dimensions_citation
49 Dimensions

Readers on

mendeley
128 Mendeley
Summary Twitter Dimensions citations
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Title
Comparison of risk prediction scoring systems for ward patients: a retrospective nested case control study
Published in
Critical Care, June 2014
DOI 10.1186/cc13947
Pubmed ID
24970344
Authors

Shun Yu, Sharon Leung, Moonseong Heo, Graciela J Soto, Ronak T Shah, Sampath Gunda, Michelle Ng Gong

Abstract

The rising prevalence of rapid response teams has led to a demand for risk-stratification tools that can estimate a ward patient's risk of clinical deterioration and subsequent need for intensive care unit (ICU) admission. Finding such a risk-stratification tool is crucial for maximizing the utility of rapid response teams. This study compares the ability of nine risk prediction scores in detecting clinical deterioration among non-ICU ward patients. We also measured each score serially to characterize how these scores changed with time.

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Twitter Demographics

The data shown below were collected from the profiles of 5 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 128 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Brazil 1 <1%
Unknown 126 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 22 17%
Researcher 17 13%
Student > Ph. D. Student 16 13%
Student > Bachelor 11 9%
Student > Postgraduate 11 9%
Other 31 24%
Unknown 20 16%
Readers by discipline Count As %
Medicine and Dentistry 66 52%
Nursing and Health Professions 12 9%
Engineering 9 7%
Computer Science 6 5%
Business, Management and Accounting 2 2%
Other 6 5%
Unknown 27 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 2016.
All research outputs
#12,900,273
of 22,757,541 outputs
Outputs from Critical Care
#4,351
of 6,045 outputs
Outputs of similar age
#105,593
of 227,908 outputs
Outputs of similar age from Critical Care
#44
of 89 outputs
Altmetric has tracked 22,757,541 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,045 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 19.1. This one is in the 26th percentile – i.e., 26% 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 227,908 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 52% 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 is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.

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