Predictors of prolonged hospital stay among patients with dengue infection in Hospital Canselor Tuanku Muhriz

Abstract

Dengue infection is considered as one of the most important vector-borne diseases with high morbidity and mortality. High incidence of dengue resulted in increased hospital admission. Prolonged hospital stay may affect the patients and families in terms of economic loss and psychological impact. There have been limited published literature on the factors that may predict prolonged hospital stay amongst patients with dengue infection, particularly in Malaysia. The objective of this study is to determine predictors of prolonged hospital stay amongst patients with dengue infection. This was a cross sectional study by using retrospective data of randomly selected patients aged 15 years old and above, who were admitted due to dengue fever in Hospital Canselor Tuanku Muhriz in Kuala Lumpur from 1 January 2014 to 30 November 2017. Data analysis included descriptive analysis, bivariate analysis, and multivariable analysis by using hierarchical logistic regression. A total of 513 dengue patients were included in the study. The median age was 34 years old, and more than half were males. The median length of stay was four days, and more than one-third of patients had prolonged hospital stay. Factors associated with the prolonged hospital stay included fever less than three days (OR 15.00, 95%CI 5.98-37.50), had four or more warning signs (OR 3.75, 95%CI 1.84-7.64), severe dengue (OR 16.60, 95%CI 5.12-53.79), acute kidney injury (OR 4.12, 95%CI 1.15-14.69) and secondary bacterial infection (OR 7.02, 95%CI 1.19- 41.36). Days of fever on admission, WS, dengue severity and complications may predict the length of hospitalisation amongst dengue infected patients. These findings could be very useful for medical practitioners in districts whereby resources are limited, especially in the rural areas. It may also benefit both public health authorities and clinicians in this hyperendemic region to prioritise care that may translate into reduced morbidity and mortality.