ALTERING THE INTESTINAL MICROBIOME IN CYSTIC FIBROSIS

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 compr...

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Bibliographische Detailangaben
Hauptverfasser:	Valls, Rebecca A, Hampton, Thomas, O'Toole, George A, Madan, Juliette C
Format:	Patent
Sprache:	eng
Schlagworte:	BEER BIOCHEMISTRY CHEMISTRY COMPOSITIONS OR TEST PAPERS THEREFOR CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL ORENZYMOLOGICAL PROCESSES ENZYMOLOGY HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEICACIDS OR MICROORGANISMS METALLURGY MICROBIOLOGY MUTATION OR GENETIC ENGINEERING PHYSICS PROCESSES OF PREPARING SUCH COMPOSITIONS SPIRITS VINEGAR WINE
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Beschreibung
Zusammenfassung:	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.