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Predicting mortality in sick African children: the FEAST Paediatric Emergency Triage (PET) Score

Overview of attention for article published in BMC Medicine, July 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

Mentioned by

blogs
1 blog
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22 X users
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1 Facebook page
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1 Redditor

Citations

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60 Dimensions

Readers on

mendeley
162 Mendeley
Title
Predicting mortality in sick African children: the FEAST Paediatric Emergency Triage (PET) Score
Published in
BMC Medicine, July 2015
DOI 10.1186/s12916-015-0407-3
Pubmed ID
Authors

Elizabeth C. George, A. Sarah Walker, Sarah Kiguli, Peter Olupot-Olupot, Robert O. Opoka, Charles Engoru, Samuel O. Akech, Richard Nyeko, George Mtove, Hugh Reyburn, James A. Berkley, Ayub Mpoya, Michael Levin, Jane Crawley, Diana M. Gibb, Kathryn Maitland, Abdel G. Babiker

Abstract

Mortality in paediatric emergency care units in Africa often occurs within the first 24 h of admission and remains high. Alongside effective triage systems, a practical clinical bedside risk score to identify those at greatest risk could contribute to reducing mortality. Data collected during the Fluid As Expansive Supportive Therapy (FEAST) trial, a multi-centre trial involving 3,170 severely ill African children, were analysed to identify clinical and laboratory prognostic factors for mortality. Multivariable Cox regression was used to build a model in this derivation dataset based on clinical parameters that could be quickly and easily assessed at the bedside. A score developed from the model coefficients was externally validated in two admissions datasets from Kilifi District Hospital, Kenya, and compared to published risk scores using Area Under the Receiver Operating Curve (AUROC) and Hosmer-Lemeshow tests. The Net Reclassification Index (NRI) was used to identify additional laboratory prognostic factors. A risk score using 8 clinical variables (temperature, heart rate, capillary refill time, conscious level, severe pallor, respiratory distress, lung crepitations, and weak pulse volume) was developed. The score ranged from 0-10 and had an AUROC of 0.82 (95 % CI, 0.77-0.87) in the FEAST trial derivation set. In the independent validation datasets, the score had an AUROC of 0.77 (95 % CI, 0.72-0.82) amongst admissions to a paediatric high dependency ward and 0.86 (95 % CI, 0.82-0.89) amongst general paediatric admissions. This discriminative ability was similar to, or better than other risk scores in the validation datasets. NRI identified lactate, blood urea nitrogen, and pH to be important prognostic laboratory variables that could add information to the clinical score. Eight clinical prognostic factors that could be rapidly assessed by healthcare staff for triage were combined to create the FEAST Paediatric Emergency Triage (PET) score and externally validated. The score discriminated those at highest risk of fatal outcome at the point of hospital admission and compared well to other published risk scores. Further laboratory tests were also identified as prognostic factors which could be added if resources were available or as indices of severity for comparison between centres in future research studies.

X Demographics

X Demographics

The data shown below were collected from the profiles of 22 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 162 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Israel 1 <1%
Unknown 160 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 26 16%
Researcher 19 12%
Student > Ph. D. Student 18 11%
Other 13 8%
Student > Postgraduate 13 8%
Other 33 20%
Unknown 40 25%
Readers by discipline Count As %
Medicine and Dentistry 79 49%
Agricultural and Biological Sciences 8 5%
Nursing and Health Professions 5 3%
Social Sciences 4 2%
Biochemistry, Genetics and Molecular Biology 3 2%
Other 21 13%
Unknown 42 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 21. 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 18 June 2019.
All research outputs
#1,585,842
of 23,577,654 outputs
Outputs from BMC Medicine
#1,108
of 3,569 outputs
Outputs of similar age
#21,284
of 264,341 outputs
Outputs of similar age from BMC Medicine
#28
of 73 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,569 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 44.5. This one has gotten more attention than average, scoring higher than 68% 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 264,341 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 91% of its contemporaries.
We're also able to compare this research output to 73 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 61% of its contemporaries.