Novel approaches to the prediction of influenza complications

Novel approaches to the prediction of influenza complications

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Influenza is a common condition, affecting millions of Americans every year. While it is usually a self-limited illness, some patients experience complications such as pneumonia or hospitalization. It would be helpful to be able to identify patients at high risk for complications, who could be followed more closely. The goal of our research is to develop one or more practical, validated, accurate tools to predict the likelihood of complications among patients with influenza-like illness and the subset who have proven influenza A or B virus infection.

Aim 1: Use logistic regression to develop and validate a point score that predicts complications requiring an antibiotic or hospitalization in patients with flu or flu-like illness.
Aim 2: Use classification and regression tree analysis to develop and validate a decision tree that predicts complications requiring an antibiotic or hospitalization in patients with flu or flu-like illness.

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