Altering the intestinal microbiome in cystic fibrosis

Abstract

The present disclosure relates to computer-implemented systems for identifying a patient with cystic fibrosis as having a high risk for upper respiratory infections or systemic inflammation, based on the patient's stool microbiota. The systems use machine learning models trained with data comprising (a) risk classifications for subjects with cystic fibrosis and (b) stool microbiota information for each of the subjects. The present disclosure also relates to methods of reducing frequency and/or number of upper respiratory infections in a patient with cystic fibrosis. The present disclosure also relates to methods of identifying a patient with cystic fibrosis (CF) as having a high risk for frequent upper respiratory infections or high systemic inflammation based on the patient's stool microbiota.

Dependencies are inferred from the claim text.