title: Objective prediction of pharyngeal swallow dysfunction in dysphagia through artificial neural network modeling.
abstract: BACKGROUND
  Pharyngeal pressure-flow analysis (PFA) of high resolution impedance-manometry (HRIM) with calculation of the swallow risk index (SRI) can quantify swallow dysfunction predisposing to aspiration. We explored the potential use of artificial neural networks (ANN) to model the relationship between PFA swallow metrics and aspiration and to predict swallow dysfunction.
  
  
  METHODS
  Two hundred consecutive dysphagia patients referred for videofluoroscopy and HRIM were assessed. Presence of aspiration was scored and PFA software derived 13 metrics and the SRI. An ANN was created and optimized over training cycles to achieve optimal classification accuracy for matching inputs (PFA metrics) to output (presence of aspiration on videofluoroscopy). Application of the ANN returned a value between 0.00 and 1.00 reflecting the degree of swallow dysfunction.
  
  
  RESULTS
  Twenty one patients were excluded due to insufficient number of swallows (<4). Of 179, 58 aspirated and 27 had aspiration pneumonia history. The SRI was higher in aspirators (aspiration 24 [9, 41] vs no aspiration 7 [2, 18], p < 0.001) and patients with pneumonia (pneumonia 27 [5, 42] vs no pneumonia 8 [3, 24], p < 0.05). The ANN Predicted Risk was higher in aspirators (aspiration 0.57 [0.38, 0.82] vs no aspiration 0.13 [0.4, 0.25], p < 0.001) and in patients with pneumonia (pneumonia 0.46 [0.18, 0.60] vs no pneumonia 0.18 [0.6, 0.49], p < 0.01). Prognostic value of the ANN was superior to the SRI.
  
  
  CONCLUSIONS
  In a heterogeneous cohort of dysphagia patients, PFA with ANN modeling offers enhanced detection of clinically significant swallowing dysfunction, probably more accurately reflecting the complex interplay of swallow characteristics that causes aspiration.
authors.affiliation: Gastroenterology Unit, Women's & Children's Health Network, Adelaide, SA, Australia.|Neurosciences, ExpORL, KU Leuven, Leuven, Belgium.|Translational Research Center for Gastrointestinal Diseases (TARGID), KU Leuven, Leuven, Belgium.
authors.forename: S
authors.initials: S
authors.lastname: Kritas
authors.affiliation: Gerontology and Geriatrics, University Hospitals Leuven, Leuven, Belgium.|Multidisciplinary Clinic for Swallowing Disorders, University Hospitals Leuven, Leuven, Belgium.
authors.forename: E
authors.initials: E
authors.lastname: Dejaeger
authors.affiliation: Translational Research Center for Gastrointestinal Diseases (TARGID), KU Leuven, Leuven, Belgium.
authors.forename: J
authors.initials: J
authors.lastname: Tack
authors.affiliation: Gastroenterology Unit, Women's & Children's Health Network, Adelaide, SA, Australia.|Department of Human Physiology, School of Medicine, Flinders University, Adelaide, SA, Australia.
authors.forename: T
authors.initials: T
authors.lastname: Omari
authors.affiliation: Neurosciences, ExpORL, KU Leuven, Leuven, Belgium.|Translational Research Center for Gastrointestinal Diseases (TARGID), KU Leuven, Leuven, Belgium.
authors.forename: N
authors.initials: N
authors.lastname: Rommel
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003198:Computer Simulation; D003430:Cross-Sectional Studies; D003680:Deglutition Disorders / Q000175:diagnosis / Q000503:physiopathology; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D010614:Pharynx / Q000503:physiopathology; D055815:Young Adult
keywords: dysphagia; high resolution manometry; impedance measurement; swallowing