↓ Skip to main content

Prospective validation of pediatric disease severity scores to predict mortality in Ugandan children presenting with malaria and non-malaria febrile illness

Overview of attention for article published in Critical Care, December 2015
Altmetric Badge

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 (88th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (59th percentile)

Mentioned by

news
1 news outlet
twitter
8 X users

Citations

dimensions_citation
38 Dimensions

Readers on

mendeley
81 Mendeley
citeulike
1 CiteULike
Title
Prospective validation of pediatric disease severity scores to predict mortality in Ugandan children presenting with malaria and non-malaria febrile illness
Published in
Critical Care, December 2015
DOI 10.1186/s13054-015-0773-4
Pubmed ID
Authors

Andrea L Conroy, Michael Hawkes, Kyla Hayford, Sophie Namasopo, Robert O Opoka, Chandy C John, W Conrad Liles, Kevin C Kain

Abstract

The development of simple clinical tools to identify children at risk of death would enable rapid and rational implementation of lifesaving measures to reduce childhood mortality globally. We evaluated the ability of three clinical scoring systems to predict in-hospital mortality in a prospective observational study of Ugandan children with fever. We computed the Lambaréné Organ Dysfunction Score (LODS), Signs of Inflammation in Children that Kill (SICK), and the Pediatric Early Death Index for Africa (PEDIA). Model discrimination was evaluated by comparing areas under receiver operating characteristic curves (AUCs) and calibration was assessed using the Hosmer-Lemeshow goodness-of-fit test. Sub-analyses were performed in malaria versus non-malaria febrile illness (NMFI), and in early (≤48 hours) versus late (>48 hours) deaths. In total, 2089 children with known outcomes were included in the study (99 deaths, 4.7% mortality). All three scoring systems yielded good discrimination (AUCs, 95% confidence interval (CI): LODS, 0.90, 0.88 to 0.91; SICK, 0.85, 0.83 to 0.86; PEDIA, 0.90, 0.88 to 0.91). Using the Youden index to identify the best cut-offs, LODS had the highest positive likelihood ratio (+LR, 95% CI: LODS, 6.5, 5.6 to 7.6; SICK, 4.4, 3.9 to 5.0; PEDIA, 4.4, 3.9 to 5.0), whereas PEDIA had the lowest negative likelihood ratio (-LR, 95% CI: LODS, 0.21, 0.1 to 0.3; SICK, 0.22, 0.1 to 0.3; PEDIA, 0.16, 0.1 to 0.3), LODS and PEDIA were well calibrated (P = 0.79 and P = 0.21 respectively), and had higher AUCs than SICK in discriminating between survivors and non-survivors in malaria (AUCs, 95% CI: LODS, 0.92, 0.90 to 0.93; SICK, 0.86, 0.84 to 0.87; PEDIA, 0.92, 0.90 to 0.93), but comparable AUCs in NMFI (AUCs, 95% CI: LODS, 0.86, 0.83 to 0.89; SICK, 0.82, 0.79 to 0.86; PEDIA, 0.87, 0.83 to 0.893). The majority of deaths in the study occurred early (n = 85, 85.9%) where LODS and PEDIA had good discrimination. All three scoring systems predicted outcome, but LODS holds the most promise as a clinical prognostic score based on its simplicity to compute, requirement for no equipment, and good discrimination.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 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 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Ethiopia 1 1%
Brazil 1 1%
Unknown 79 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 22%
Student > Master 13 16%
Researcher 8 10%
Student > Postgraduate 7 9%
Other 4 5%
Other 9 11%
Unknown 22 27%
Readers by discipline Count As %
Medicine and Dentistry 37 46%
Agricultural and Biological Sciences 5 6%
Social Sciences 3 4%
Nursing and Health Professions 1 1%
Mathematics 1 1%
Other 5 6%
Unknown 29 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 25 November 2021.
All research outputs
#2,721,745
of 25,374,917 outputs
Outputs from Critical Care
#2,359
of 6,554 outputs
Outputs of similar age
#43,503
of 395,418 outputs
Outputs of similar age from Critical Care
#190
of 466 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,554 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.8. This one has gotten more attention than average, scoring higher than 64% 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 395,418 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 466 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 59% of its contemporaries.