Risk factors for encephalitis and death from West Nile virus infection: An analysis of hospitalized cases in Houston, Texas from 2002--2008

We conducted a nested case-control study to determine the significant risk factors for developing encephalitis from West Nile virus (WNV) infection. The purpose of this research project was to expand the previously published Houston study of 2002–2004 patients to include data on Houston patients from four additional years (2005–2008) to determine if there were any differences in risk factors shown to be associated with developing the more severe outcomes of WNV infection, encephalitis and death, by having this larger sample size. A re-analysis of the risk factors for encephalitis and death was conducted on all of the patients from 2002–2008 and was the focus of this proposed research. This analysis allowed for the determination to be made that there are differences in the outcome in the risk factors for encephalitis and death with an increased sample size. Retrospective medical chart reviews were completed for the 265 confirmed WNV hospitalized patients; 153 patients had encephalitis (WNE), 112 had either viral syndrome with fever (WNF) or meningitis (WNM); a total of 22 patients died. Univariate logistic regression analyses on demographic, comorbidities, and social risk factors was conducted in a similar manner as in the previously conducted study to determine the risk factors for developing encephalitis from WNV. A multivariate model was developed by using model building strategies for the multivariate logistic regression analysis. The hypothesis of this study was that there would be additional risk factors shown to be significant with the increase in sample size of the dataset. This analysis with a greater sample size and increased power supports the hypothesis in that there were additional risk factors shown to be statistically associated with the more severe outcomes of WNV infection (WNE or death). Based on univariate logistic regression results, these data showed that even though age of 20–44 years was statistically significant as a protecting effect for developing WNE in the original study, the expanded sample lacked significance. This study showed a significant WNE risk factor to be chronic alcohol abuse, when it was not significant in the original analysis. Other WNE risk factors identified in this analysis that showed to be significant but were not significant in the original analysis were cancer not in remission > 5 years, history of stroke, and chronic renal disease. When comparing the two analyses with death as an outcome, two risk factors that were shown to be significant in the original analysis but not in the expanded dataset analysis were diabetes mellitus and immunosuppression. Three risk factors shown to be significant in this expanded analysis but were not significant in the original study were illicit drug use, heroin or opiate use, and injection drug use. However, with the multiple logistic regression models, the same independent risk factors for developing encephalitis of age and history of hypertension including drug induced hypertension were consistent in both studies.^

Identfying predictors of St. Louis encephalitis activity in Houston Texas

Generalized linear Poisson and logistic regression models were utilized to examine the relationship between temperature and precipitation and cases of Saint Louis encephalitis virus spread in the Houston metropolitan area. The models were investigated with and without repeated measures, with a first order autoregressive (AR1) correlation structure used for the repeated measures model. The two types of Poisson regression models, with and without correlation structure, showed that a unit increase in temperature measured in degrees Fahrenheit increases the occurrence of the virus 1.7 times and a unit increase in precipitation measured in inches increases the occurrence of the virus 1.5 times. Logistic regression did not show these covariates to be significant as predictors for encephalitis activity in Houston for either correlation structure. This discrepancy for the logistic model could be attributed to the small data set.^ Keywords: Saint Louis Encephalitis; Generalized Linear Model; Poisson; Logistic; First Order Autoregressive; Temperature; Precipitation. ^