ArticleBMC infectious diseases2017
A retrospective cohort study to predict severe dengue in Honduran patients.
Article in BMC infectious diseases, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.
- Prognostic Models in Patients with Dengue: A Systematic Review.The American journal of tropical medicine and hygiene · 2025Pooled it
- Early hematological parameters as predictors for outcomes in children with dengue in northern India: A retrospective analysis.Revista da Sociedade Brasileira de Medicina Tropical · 2021Article
- Dengue epidemic in a non-endemic zone of Bangladesh: Clinical and laboratory profiles of patients.PLoS neglected tropical diseases · 2020Article
- Characterization of clinical patterns of dengue patients using an unsupervised machine learning approach.BMC infectious diseases · 2019Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAn 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.
methodsWe 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.
resultsThirty-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
conclusionWe 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.
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