title: Comparative utility of the BESTest, mini-BESTest, and brief-BESTest for predicting falls in individuals with Parkinson disease: a cohort study.
abstract: BACKGROUND
  The newly developed brief-balance evaluation system test (brief-BESTest) may be useful for measuring balance and predicting falls in individuals with Parkinson disease (PD).
  
  
  OBJECTIVE
  The purposes of this study were: (1) to describe the balance performance of those with PD using the brief-BESTest, (2) to determine the relationships among the scores derived from the 3 versions of the BESTest (i.e., full BESTest, mini-BESTest, and brief-BESTest), and (3) to compare the accuracy of the brief-BESTest with that of the mini-BESTest and BESTest in identifying recurrent fallers among people with PD.
  
  
  METHODS
  This was a prospective cohort study.
  
  
  METHODS
  Eighty participants with PD completed a baseline balance assessment. All participants reported a fall history during the previous 6 months. Fall history was again collected 6 months (n=51) and 12 months (n=40) later.
  
  
  RESULTS
  At baseline, participants had varying levels of balance impairment, and brief-BESTest scores were significantly correlated with mini-BESTest (r=.94, P<.001) and BESTest (r=.95, P<.001) scores. Six-month retrospective fall prediction accuracy of the Brief-BESTest was moderately high (area under the curve [AUC]=0.82, sensitivity=0.76, and specificity=0.84). Prospective fall prediction accuracy over 6 months was similarly accurate (AUC=0.88, sensitivity=0.71, and specificity=0.87), but was less sensitive over 12 months (AUC=0.76, sensitivity=0.53, and specificity=0.93).
  
  
  CONCLUSIONS
  The sample included primarily individuals with mild to moderate PD. Also, there was a moderate dropout rate at 6 and 12 months.
  
  
  CONCLUSIONS
  All versions of the BESTest were reasonably accurate in identifying future recurrent fallers, especially during the 6 months following assessment. Clinicians can reasonably rely on the brief-BESTest for predicting falls, particularly when time and equipment constraints are of concern.
authors.affiliation: Program in Physical Therapy, Department of Anatomy & Neurobiology, Washington University School of Medicine, St Louis, Missouri 63108, USA.
authors.forename: Ryan P
authors.initials: RP
authors.lastname: Duncan
authors.forename: Abigail L
authors.initials: AL
authors.lastname: Leddy
authors.forename: James T
authors.initials: JT
authors.lastname: Cavanaugh
authors.forename: Leland E
authors.initials: LE
authors.lastname: Dibble
authors.forename: Terry D
authors.initials: TD
authors.lastname: Ellis
authors.forename: Matthew P
authors.initials: MP
authors.lastname: Ford
authors.forename: K Bo
authors.initials: KB
authors.lastname: Foreman
authors.forename: Gammon M
authors.initials: GM
authors.lastname: Earhart
mesh_terms: D000058:Accidental Falls / Q000706:statistics & numerical data*; D000368:Aged; D000369:Aged, 80 and over; D015331:Cohort Studies; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010300:Parkinson Disease / Q000150:complications*; D004856:Postural Balance; D011446:Prospective Studies; D012680:Sensitivity and Specificity