The Mini Balance Evaluation System Test (Mini-BESTest) for Predicting Recurrent Fall in Active Older Adults from 1-Year Prospective Study

Abstract

Objective: To determine the accuracy of the Mini Balance Evaluation System Test (Mini-BESTest) for predicting recurrent fall in the active elderly using the data from 12-month follow up, as compared to the Berg Balance Scale (BBS) and Timed Up and Go Test (TUG). Method: Two hundred healthy older adults participated and were classified into 2 groups based on of their previous 12-month fall history; with and without history of fall groups. Participants received balance assessments using the Mini-BESTest, BBS, and TUG at the initial visit. Fall incidence was monitored every month for 12 months. An analysis of the receiver operating characteristic curves was performed to calculate the area under the curve (AUC), sensitivity, specificity, cut-off score, likelihood ratio (LR) and posttest accuracy of each scale. In addition, those parameters were calculated and compared based on data from previous 12 months, 6-month and 12-month follow up. Results: Using the prospective 12-month data, The Mini-BESTest demonstrated the highest AUC (0.71) for fall prediction, as compared to that of the BBS (0.59) and TUG (0.41). This is supported by the highest posttest accuracy of the Mini-BESTest (94.5%), whereas the BBS (74.2%) and TUG (27%) showed lower accuracy. The cut-off score of the Mini-BESTest was 18 out of 28, with the sensitivity of 0.91 and specificity of 0.71, and LR+ of 2.4 and LR- of 0.09. These values yielded better accuracy than the values calculated from retrospective 12-months and better clinical relevance than the values calculated from prospective 6-month data. Conclusion: The Mini-BESTest is more accurate to predicting recurrent falls in active elderly persons than the BBS and TUG. The suggested cut-off score based on 12-month follow up is 18 out of 28. Keywords: recurrent fall, active older adults, Mini-BESTest