Predictive tools for severe dengue conforming to World Health Organization 2009 criteria.

Autor: Carrasco LR; Department of Biological Sciences, National University of Singapore, Singapore., Leo YS; Communicable Disease Centre, Tan Tock Seng Hospital, Singapore; Saw Swee Hock School of Public Health, National University of Singapore, Singapore., Cook AR; Saw Swee Hock School of Public Health, National University of Singapore, Singapore; Program in Health Services and Systems Research, Duke-NUS Graduate Medical School, Singapore; Biodefence Centre, Ministry of Defence, Singapore, Singapore., Lee VJ; Saw Swee Hock School of Public Health, National University of Singapore, Singapore; Biodefence Centre, Ministry of Defence, Singapore, Singapore; Centre for Health Services Research, National University of Singapore, Singapore., Thein TL; Communicable Disease Centre, Tan Tock Seng Hospital, Singapore., Go CJ; Communicable Disease Centre, Tan Tock Seng Hospital, Singapore., Lye DC; Communicable Disease Centre, Tan Tock Seng Hospital, Singapore; Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
Jazyk: angličtina
Zdroj: PLoS neglected tropical diseases [PLoS Negl Trop Dis] 2014 Jul 10; Vol. 8 (7), pp. e2972. Date of Electronic Publication: 2014 Jul 10 (Print Publication: 2014).
DOI: 10.1371/journal.pntd.0002972
Abstrakt: Background: Dengue causes 50 million infections per year, posing a large disease and economic burden in tropical and subtropical regions. Only a proportion of dengue cases require hospitalization, and predictive tools to triage dengue patients at greater risk of complications may optimize usage of limited healthcare resources. For severe dengue (SD), proposed by the World Health Organization (WHO) 2009 dengue guidelines, predictive tools are lacking.
Methods: We undertook a retrospective study of adult dengue patients in Tan Tock Seng Hospital, Singapore, from 2006 to 2008. Demographic, clinical and laboratory variables at presentation from dengue polymerase chain reaction-positive and serology-positive patients were used to predict the development of SD after hospitalization using generalized linear models (GLMs).
Principal Findings: Predictive tools compatible with well-resourced and resource-limited settings--not requiring laboratory measurements--performed acceptably with optimism-corrected specificities of 29% and 27% respectively for 90% sensitivity. Higher risk of severe dengue (SD) was associated with female gender, lower than normal hematocrit level, abdominal distension, vomiting and fever on admission. Lower risk of SD was associated with more years of age (in a cohort with an interquartile range of 27-47 years of age), leucopenia and fever duration on admission. Among the warning signs proposed by WHO 2009, we found support for abdominal pain or tenderness and vomiting as predictors of combined forms of SD.
Conclusions: The application of these predictive tools in the clinical setting may reduce unnecessary admissions by 19% allowing the allocation of scarce public health resources to patients according to the severity of outcomes.
Databáze: MEDLINE
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