title: Can falls be predicted with gait analytical and posturographic measurement systems? A prospective follow-up study in a nursing home population.
abstract: OBJECTIVE
  To validate previously proposed findings and to develop an objective, feasible and efficient bifactorial (risk factors: gait impairment and balance disorders) fall risk assessment.
  
  
  METHODS
  Prospective follow-up study Setting: Nursing homes (Halle/Saale, Germany).
  
  
  METHODS
  One hundred and forty-six nursing home residents (aged 62-101 years) were recruited.
  
  
  METHODS
  Gait data were collected using a mobile inertial sensor-based system (RehaWatch). Postural regulation data were measured with the Interactive Balance System. Falls were recorded in standardized protocols over a follow-up period of 12 months.
  
  
  METHODS
  Gait parameters (e.g. spatial-temporal parameters), posturographic parameters (e.g. postural subsystems), number of falls.
  
  
  RESULTS
  Seventeen (12%) of the participants had more than two falls per year. The predictive validity of the previously selected posturographic parameters was inadequate (sensitivity: 47%). The new measurement tool defined 67 participants showing an increased risk of falls. In reality, only 8 participants actually fell more than twice during the follow-up period (positive predictive value (PPV): 12%). The negative predictive value (NPV) was 88%. The posturographic frequency range F2-4 (peripheral-vestibular system), stride time and standard deviation of landing phase were the most powerful parameters for fall prediction. Gait and postural variability were larger in the high-risk group (e.g. gait speed; confidence interval (CI)(high): 0.57-0.79 vs. CI(low): 0.72-0.81 m/s).
  
  
  CONCLUSIONS
  RehaWatch and the Interactive Balance System are able to measure two of the most important fall risk factors, but their current predictive ability is not satisfactory yet. The correlation with physiological mechanisms is only shown by the Interactive Balance System.
authors: Department of Sport-Science, Martin-Luther-Universität Halle-Wittenberg, Halle (Saale), Germany. rene.schwesig@sport.uni-halle.de
authors: René
authors: R
authors: Schwesig
authors: David
authors: D
authors: Fischer
authors: Andreas
authors: A
authors: Lauenroth
authors: Stephan
authors: S
authors: Becker
authors: Siegfried
authors: S
authors: Leuchte
mesh_terms: D000058:Accidental Falls; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D005500:Follow-Up Studies; D005684:Gait / Q000502:physiology*; D015577:Geriatric Assessment; D006801:Humans; D008297:Male; D008875:Middle Aged; D009735:Nursing Homes; D004856:Postural Balance / Q000502:physiology*; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012372:ROC Curve; D018570:Risk Assessment