title: An electronic walkway can predict short-term fall risk in nursing home residents with dementia.
abstract: OBJECTIVE
  To evaluate the feasibility and validity of gait parameters measured with an electronic walkway system in predicting short-term fall risk in nursing home residents with dementia.
  
  
  METHODS
  57 ambulatory nursing home residents with moderate to severe dementia participated in this prospective cohort study. We used the GAITRite(®) 732 walkway system to assess gait parameters. Measurements were collected every 3 months over a 15 month period, with each measurement being a baseline for the subsequent measurement. Falls were retrieved from incident reports. The predictive validity of the GAITRite(®) parameters was expressed in terms of sensitivity and specificity. Logistic regression analysis was conducted to examine the association between these parameters and falls occurrence within three months.
  
  
  RESULTS
  Reduced velocity (OR=1.22; 95% CI 1.04-1.43) and reduced mean stride length (OR=1.19; 95% CI 1.03-1.40) were the best significant gait predictors of a fall within three months, with a sensitivity of 82% for velocity and 86% for mean stride length, and a specificity of 52% for velocity and for mean stride length. The test procedure took an average of 5 min per participant. Some verbal persuasion or physical cueing was necessary in 142 measurements (80.7%).
  
  
  CONCLUSIONS
  Gait parameters as measured with an electronic walkway system can be used for the prediction of short-term fall risk in nursing home residents with moderate to severe dementia. However some form of persuasion might be needed to perform the task. To refine our findings, large prospective studies on the predictive validity of gait parameters in this type of population are needed.
authors.affiliation: Section of Geriatric Medicine, Department of Internal Medicine, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands.
authors.forename: Carolyn S
authors.initials: CS
authors.lastname: Sterke
authors.forename: Ed F
authors.initials: EF
authors.lastname: van Beeck
authors.forename: Caspar W N
authors.initials: CW
authors.lastname: Looman
authors.forename: Reto W
authors.initials: RW
authors.lastname: Kressig
authors.forename: Tischa J M
authors.initials: TJ
authors.lastname: van der Cammen
mesh_terms: D000058:Accidental Falls / Q000517:prevention & control* / Q000706:statistics & numerical data; D000368:Aged; D000369:Aged, 80 and over; D000704:Analysis of Variance; D015331:Cohort Studies; D003704:Dementia / Q000150:complications* / Q000175:diagnosis; D005080:Exercise Test / Q000295:instrumentation* / Q000379:methods; D005240:Feasibility Studies; D005260:Female; D005684:Gait / Q000502:physiology; D020233:Gait Disorders, Neurologic / Q000145:classification* / Q000453:epidemiology / Q000534:rehabilitation*; D015577:Geriatric Assessment / Q000379:methods*; D006707:Homes for the Aged; D006801:Humans; D015994:Incidence; D008297:Male; D009735:Nursing Homes; D011237:Predictive Value of Tests; D011446:Prospective Studies; D018570:Risk Assessment; D012720:Severity of Illness Index; D016138:Walking / Q000502:physiology