title: Non-linear associations between laryngo-pharyngeal symptoms of gastro-oesophageal reflux disease: clues from artificial intelligence analysis.
abstract: The relationship between the different symptoms of gastro-oesophageal reflux disease remain markedly obscure due to the high underlying non-linearity and the lack of studies focusing on the problem. Aim of this study was to evaluate the hidden relationships between the triad of symptoms related to gastro-oesophageal reflux disease using advanced mathematical techniques, borrowed from the artificial intelligence field, in a cohort of patients with oesophagitis. A total of 388 patients (from 60 centres) with endoscopic evidence of oesophagitis were recruited. The severity of oesophagitis was scored by means of the Savary-Miller classification. PST algorithm was employed. This study shows that laryngo-pharyngeal symptoms related to gastro-oesophageal reflux disease are correlated even if in a non-linear way.
authors.affiliation: Medical Department, Bracco SpA, Milano, Italy. enzo.grossi@bracco.com
authors.forename: E
authors.initials: E
authors.lastname: Grossi
mesh_terms: D000328:Adult; D001185:Artificial Intelligence; D005260:Female; D005764:Gastroesophageal Reflux / Q000503:physiopathology*; D006801:Humans; D007830:Larynx / Q000503:physiopathology*; D008297:Male; D008954:Models, Biological; D010614:Pharynx / Q000503:physiopathology*