title: Advanced Treatment Monitoring for Olympic-Level Athletes Using Unsupervised Modeling Techniques.
abstract: BACKGROUND
  Analysis of injury and illness data collected at large international competitions provides the US Olympic Committee and the national governing bodies for each sport with information to best prepare for future competitions. Research in which authors have evaluated medical contacts to provide the expected level of medical care and sports medicine services at international competitions is limited.
  
  
  OBJECTIVE
  To analyze the medical-contact data for athletes, staff, and coaches who participated in the 2011 Pan American Games in Guadalajara, Mexico, using unsupervised modeling techniques to identify underlying treatment patterns.
  
  
  METHODS
  Descriptive epidemiology study.
  
  
  METHODS
  Pan American Games.
  
  
  METHODS
  A total of 618 U.S. athletes (337 males, 281 females) participated in the 2011 Pan American Games.
  
  
  METHODS
  Medical data were recorded from the injury-evaluation and injury-treatment forms used by clinicians assigned to the central US Olympic Committee Sport Medicine Clinic and satellite locations during the operational 17-day period of the 2011 Pan American Games. We used principal components analysis and agglomerative clustering algorithms to identify and define grouped modalities. Lift statistics were calculated for within-cluster subgroups.
  
  
  RESULTS
  Principal component analyses identified 3 components, accounting for 72.3% of the variability in datasets. Plots of the principal components showed that individual contacts focused on 4 treatment clusters: massage, paired manipulation and mobilization, soft tissue therapy, and general medical.
  
  
  CONCLUSIONS
  Unsupervised modeling techniques were useful for visualizing complex treatment data and provided insights for improved treatment modeling in athletes. Given its ability to detect clinically relevant treatment pairings in large datasets, unsupervised modeling should be considered a feasible option for future analyses of medical-contact data from international competitions.
authors.affiliation: Department of Health, Sport, and Exercise Sciences, University of Kansas, Lawrence;
authors.forename: Jacob A
authors.initials: JA
authors.lastname: Siedlik
authors.affiliation: Albany College of Pharmacy and Health Sciences, NY;
authors.forename: Charles
authors.initials: C
authors.lastname: Bergeron
authors.affiliation: Department of Health, Sport, and Exercise Sciences, University of Kansas, Lawrence;
authors.forename: Michael
authors.initials: M
authors.lastname: Cooper
authors.affiliation: Department of Health, Sport, and Exercise Sciences, University of Kansas, Lawrence;
authors.forename: Russell
authors.initials: R
authors.lastname: Emmons
authors.affiliation: US Olympic Committee, Colorado Springs;
authors.forename: William
authors.initials: W
authors.lastname: Moreau
authors.affiliation: US Olympic Committee, Colorado Springs;
authors.forename: Dustin
authors.initials: D
authors.lastname: Nabhan
authors.affiliation: Department of Health, Sport, and Exercise Sciences, University of Kansas, Lawrence;
authors.forename: Philip
authors.initials: P
authors.lastname: Gallagher
authors.affiliation: Department of Health, Sport, and Exercise Sciences, University of Kansas, Lawrence;|Department of Human Nutrition, Kansas State University, Manhattan.
authors.forename: John P
authors.initials: JP
authors.lastname: Vardiman
mesh_terms: D056352:Athletes / Q000706:statistics & numerical data; D001265:Athletic Injuries / Q000453:epidemiology / Q000208:ethnology / Q000628:therapy*; D005260:Female; D005544:Forecasting; D006801:Humans; D008297:Male; D008800:Mexico / Q000453:epidemiology; D010342:Patient Acceptance of Health Care / Q000706:statistics & numerical data; D026741:Physical Therapy Modalities / Q000706:statistics & numerical data; D013177:Sports / Q000502:physiology*; D013178:Sports Medicine / Q000706:statistics & numerical data; D014481:United States / Q000208:ethnology
keywords: clinician care decisions; epidemiology; statistical methods; treatment patterns