Comparative utility of the BESTest, mini-BESTest, and brief-BESTest for predicting falls in individuals with Parkinson disease: a cohort study

Phys Ther. 2013 Apr;93(4):542-50. doi: 10.2522/ptj.20120302. Epub 2012 Nov 21.

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).

Objectives: 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.

Design: 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).

Limitations: 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.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Accidental Falls / statistics & numerical data*
  • Aged
  • Aged, 80 and over
  • Cohort Studies
  • Female
  • Humans
  • Male
  • Middle Aged
  • Parkinson Disease / complications*
  • Postural Balance*
  • Prospective Studies
  • Sensitivity and Specificity