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- Title
Prediction of mortality in severe dengue cases.
- Authors
Md-Sani, Saiful Safuan; Md-Noor, Julina; Han, Winn-Hui; Gan, Syang-Pyang; Rani, Nor-Salina; Tan, Hui-Loo; Rathakrishnan, Kanimoli; A-Shariffuddin, Mohd Azizuddin; Abd-Rahman, Marzilawati
- Abstract
<bold>Background: </bold>Increasing incidence of dengue cases in Malaysia over the last few years has been paralleled by increased deaths. Mortality prediction models will therefore be useful in clinical management. The aim of this study is to identify factors at diagnosis of severe dengue that predicts mortality and assess predictive models based on these identified factors.<bold>Method: </bold>This is a retrospective cohort study of confirmed severe dengue patients that were admitted in 2014 to Hospital Kuala Lumpur. Data on baseline characteristics, clinical parameters, and laboratory findings at diagnosis of severe dengue were collected. The outcome of interest is death among patients diagnosed with severe dengue.<bold>Results: </bold>There were 199 patients with severe dengue included in the study. Multivariate analysis found lethargy, OR 3.84 (95% CI 1.23-12.03); bleeding, OR 8.88 (95% CI 2.91-27.15); pulse rate, OR 1.04 (95% CI 1.01-1.07); serum bicarbonate, OR 0.79 (95% CI 0.70-0.89) and serum lactate OR 1.27 (95% CI 1.09-1.47), to be statistically significant predictors of death. The regression equation to our model with the highest AUROC, 83.5 (95% CI 72.4-94.6), is: Log odds of death amongst severe dengue cases = - 1.021 - 0.220(Serum bicarbonate) + 0.001(ALT) + 0.067(Age) - 0.190(Gender).<bold>Conclusion: </bold>This study showed that a large proportion of severe dengue occurred early, whilst patients were still febrile. The best prediction model to predict death at recognition of severe dengue is a model that incorporates serum bicarbonate and ALT levels.
- Subjects
MALAYSIA; DENGUE; DIAGNOSIS; DENGUE hemorrhagic fever; DENGUE viruses; MORTALITY; PUBLIC health; BICARBONATE ions; CREATININE; MULTIVARIATE analysis; PHARMACOKINETICS; SURVIVAL; ALANINE aminotransferase; RETROSPECTIVE studies; RECEIVER operating characteristic curves
- Publication
BMC Infectious Diseases, 2018, Vol 18, Issue 1, pN.PAG
- ISSN
1471-2334
- Publication type
journal article
- DOI
10.1186/s12879-018-3141-6