Severity Of Illness Models For Respiratory Syncytial Virus–Associated Hospitalization

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Abstract
The objective of this investigation was to examine the feasibility of multivariate severity of illness models for pediatric patients hospitalized with respiratory syncytial virus (RSV) infection. From a pre- existing retrospective cohort study database, all infants and children 2 yr of age or younger with community-acquired RSV infection admitted to the University of Michigan's C. S. Mott Children's Hospital during nine epidemics were examined. The study group consisted of 802 hospitalized pa- tients younger than 2 yr of age with community-acquired RSV infection; 182 (23%) patients had pro- longed hospital length of stay defined as 7 d or greater. Multivariate logistic regression modeling of nine variables measurable during the first hospital day was strongly associated with prolonged hospi- talization (p , 0.0001). Receiver operator characteristic curve analysis resulted in an area under the curve of 0.894, indicating excellent model discrimination. Goodness-of-fit testing indicated excellent model calibration for observed versus predicted outcomes (p 5 0.216). We conclude that severity of illness models for RSV-associated hospitalization with excellent predictive properties in terms of clas- sification, discrimination, and calibration are possible. Further study is required to determine if such models are generalizable across multiple centers and epidemics. Moler FW, Ohmit SE. Severity of illness models for respiratory syncytial virus-associated hospitalization.