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The Mini-Balance Evaluation System Test Can Predict Falls in Clinically Stable Outpatients With COPD

Authors :
Aline Costa Lopes
Rafael Stelmach
Rafaella F Xavier
Cristino Carneiro Oliveira
Ana Carolina A C Pereira
Celso R. F. Carvalho
Cibele Cristine Berto Marques da Silva
Frederico Leon Arrabal Fernandes
Source :
Journal of Cardiopulmonary Rehabilitation and Prevention. 39:391-396
Publication Year :
2019
Publisher :
Ovid Technologies (Wolters Kluwer Health), 2019.

Abstract

PURPOSE This study evaluated the accuracy of the Mini-Balance Evaluation System Test (Mini-BESTest) for predicting falls in patients with chronic obstructive pulmonary disease (COPD) and investigated whether postural balance is a risk factor for falls. METHODS Postural balance was evaluated by the Mini-BESTest at baseline, and the incidence of falls over a 12-mo period was prospectively measured by a self-reported falls diary and confirmed by telephone calls. A discriminative power analysis was performed using receiver operating characteristic (ROC) curve and logistic regression analysis. RESULTS Sixty-seven outpatients with COPD (mean age ± SD = 67 ± 9.3 yr) were included. Twenty-five patients (37.3%) experienced ≥1 fall, and 28.2% of the falls resulted in injuries. The Mini-BESTest predicted falls in patients with COPD at the 6- and 12-mo follow-ups with a cut-off score of 22.5 (area under the curve = 0.85 and 0.87) with good sensitivity and specificity (85.7% and 66.7%; 84% and 73.8%, respectively). Higher scores on the Mini-BESTest were associated with a lower risk of falls at 12 mo (OR = 0.50; 95% CI, 0.36-0.70; P < .001). CONCLUSIONS Postural balance assessed by the Mini-BESTest is a good predictor of falls in patients with COPD. Our results imply that impaired balance contributes to the risk of falling and that balance training and fall prevention programs may be required for this population.

Details

ISSN :
19327501
Volume :
39
Database :
OpenAIRE
Journal :
Journal of Cardiopulmonary Rehabilitation and Prevention
Accession number :
edsair.doi.dedup.....52242d2d1b5610e61d51ba96e778538b