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A retrospective cohort study to predict severe dengue in Honduran patients

Overview of attention for article published in BMC Infectious Diseases, October 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (59th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

Mentioned by

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4 tweeters

Citations

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9 Dimensions

Readers on

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48 Mendeley
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Title
A retrospective cohort study to predict severe dengue in Honduran patients
Published in
BMC Infectious Diseases, October 2017
DOI 10.1186/s12879-017-2800-3
Pubmed ID
Authors

Eduardo Fernández, Marek Smieja, Stephen D. Walter, Mark Loeb

Abstract

An important challenge in the identification of dengue is how to predict which patients will go on to experience severe illness, which is typically characterized by fever, thrombocytopenia, haemorrhagic manifestations, and plasma leakage. Accurate prediction could result in the appropriate hospital triage of high risk patients. The objective of this study was to identify clinical factors observed within the first 24 h of hospital admission that could predict subsequent severe dengue. We conducted a retrospective cohort study of 320 patients with febrile illness who had confirmation of dengue within one week of admission, using data from the 2009-2010 Honduras Epidemiological Survey for Dengue. The outcome measure was plasma leakage defined using hemoconcentration ≥15% as determined by serial hematocrit testing. We conducted univariable analysis and multivariable logistic regression analysis to construct a predictive model for severe dengue. Thirty-four (10.6%) of patients in the 320 patient cohort had hemoconcentration ≥15%. In the final multivariable logistic regression model the presence of ascites, OR 7.29, 95% CI 1.85 to 28.7, and a platelet count <50,000 platelets/mm(3) at admission, OR 3.02, 95% CI 1.42 to 6.42, were significantly associated with plasma leakage, while the presence of petechiae, OR 0.24 95% CI 0.080 to 0.73, and headache, OR 0.38, 95% CI 0.15 to 0.95, were negatively associated with leakage. Using an estimated probability of 7% as a threshold for a person being considered a severe case correctly predicted 26 of the 34 severe cases (sensitivity 76.4%) and 201 of the 286 non-severe cases (specificity of 70.3%) for a percentage correctly classified of 70.9%. We identified signs and symptoms that can correctly identify a majority of patients who eventually develop severe dengue in Honduras. It will be important to further refine our models and validate them in other populations.

Twitter Demographics

The data shown below were collected from the profiles of 4 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 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 48 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 15 31%
Researcher 9 19%
Student > Bachelor 6 13%
Professor 3 6%
Student > Doctoral Student 2 4%
Other 7 15%
Unknown 6 13%
Readers by discipline Count As %
Medicine and Dentistry 21 44%
Social Sciences 3 6%
Pharmacology, Toxicology and Pharmaceutical Science 2 4%
Biochemistry, Genetics and Molecular Biology 2 4%
Nursing and Health Professions 2 4%
Other 7 15%
Unknown 11 23%

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 17 October 2017.
All research outputs
#6,302,668
of 12,002,078 outputs
Outputs from BMC Infectious Diseases
#1,549
of 4,443 outputs
Outputs of similar age
#108,479
of 274,060 outputs
Outputs of similar age from BMC Infectious Diseases
#33
of 87 outputs
Altmetric has tracked 12,002,078 research outputs across all sources so far. This one is in the 47th percentile – i.e., 47% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,443 research outputs from this source. They receive a mean Attention Score of 4.3. 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 274,060 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 59% of its contemporaries.
We're also able to compare this research output to 87 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 62% of its contemporaries.