Abstract
Background: Human H1N1 Influenza A virus was first reported in 2009 when seasonal outbreaks consistently occurred around the world. H1N1 patients present to the emergency departments (ED) with flu-like symptoms extending up to severe respiratory symptoms that require hospital admission. Developing a prediction model for patient outcomes is important to select patients for hospital admission. To date, there is no available data to guide the hospital admission of H1N1 patients based on their initial presentation.
Objective: The aim of this study was to investigate the predictors of hospital admission of H1N1 patients presenting in the ED.
Methods: We conducted a retrospective review of all laboratory-confirmed H1N1 cases presenting to the ED of a tertiary university hospital in the Eastern region of Saudi Arabia within the period from November 2015 to January 2016. We retrieved data of the initial triage category, vital signs, and presenting symptoms. Multivariate logistic regression analysis was performed to evaluate risk factors for hospital admission among H1N1patients presented to the ED.
Results: We identified 333 patients with laboratory-confirmed H1N1. Patients were classified into two groups: admitted group (n=80; 24%) and non-admitted group (n=253; 76%). Sixty patients (75%) were triaged under category IV. Triage category of level III and less were the most predictive for hospital admission. Multivariate regression analysis showed that of all vital signs, tachypnea was a significant risk factor for hospital admission (OR=1.1; 95% CI 1.02 to 1.13, p<0.01). The association between lower triage category and hospital stay was statistically significant (chi(2) =6.068, p=0.037). Also, patients with dyspnea were 4.5 times more likely to have longer hospital stay (OR=4.5; 95% CI 1.2 to 17.1, p=0.025).
Conclusion: Lower triage category and increased respiratory rate predict the need for hospital admission of H1N1 infected patients; while patients with dyspnea or bronchial asthma are likely to stay longer in the hospital. Further prospective studies are needed to evaluate the accuracy of using the CTAS and other clinical parameters in predicting hospitalization of H1N1 patients during outbreaks.