Content » Vol 45, Issue 6

Original report

The mini-BESTest can predict Parkinsonian recurrent fallers: A 6-month prospective study

Margaret K.Y. Mak, Mandy M Auyeung
Department of Rehabilitation Sciences, Hong Kong Polytechnic University, Hung Hom, Hong Kong. E-mail: rsmmak@inet.polyu.edu.hk
DOI: 10.2340/16501977-1144

Abstract

Objectives: To examine whether the Mini-Balance Evaluation Systems Test (Mini-BESTest) independently predicts recurrent falls in people with Parkinson’s disease.
Design: The study used a longitudinal cohort design.
Subjects: A total of 110 patients with Parkinson’s disease completed the study and were included in the final analysis. Most of the patients had moderate disease severity.
Methods: All subjects were measured to establish a baseline. The tests used were Unified Parkinson’s Disease Rating Scale (MDS-UPDRS III), Freezing of Gait Questionnaire, Five-Time-Sit-To-Stand Test, and Mini-BESTest. All patients were followed by telephone interview for 6 months to register the incidence of monthly falls.
Results: Twenty-four patients (21.2%) reported more than one fall and were classified as recurrent fallers. Results of the multivariate logistic regression showed that, after adjusting for fall history and MDS-UPDRS III score, the Mini-BESTest score remained a significant predictor of recurrent falls. We further established that a cut-off Mini-BESTest score of 19 had the best sensitivity (79%) for predicting future falls in patients with Parkinson’s disease.
Conclusion: The results indicate that those with a Mini-BESTest score < 19 at baseline had a significantly higher risk of sustaining recurrent falls in the next 6 months. These findings highlight the importance of evaluating dynamic balance ability during fall risk assessment in patients with Parkinson’s disease.

Lay Abstract

Comments

Do you want to comment on this paper? The comments will show up here and if appropriate the comments will also separately be forwarded to the authors. You need to login/create an account to comment on articles. Click here to login/create an account.
Advertisement