Predicting faller status in persons with multiple sclerosis using the Multiple Sclerosis Walking Scale-12

Abstract

Background

Persons with multiple sclerosis (PwMS) are at an increased risk for falling, making it necessary to identify useful screening tools. The aims of this study were to 1) determine a cut-off score for the 12-item Multiple Sclerosis Walking Scale (MSWS-12) for identifying PwMS as fallers and 2) evaluate its predictive ability of faller status after controlling for other potential contributing factors.

Methods

Participant characteristics, MSWS-12, and falls in the last six months were collected on PwMS (n = 171) during a single session. Fallers (53.8 %; n = 92) were individuals reporting ≥ 1 fall in the past six months. A receiver-operating-characteristic (ROC) curve was performed to estimate the classification accuracy (area under the curve; AUC) of the MSWS-12 at detecting fallers. Optimal cut-off scores were calculated using the Youden Index and Index of Union methods. The dichotomized MSWS-12 cut-off score was then entered into a logistic regression, with faller status as the outcome, and age, gender, body mass index, disease duration, and fatigue as covariates.

Results

The MSWS-12 had a fair classification accuracy for identifying fallers (AUC = 0.74), with the cut-off score of ≥ 46 % having 76.1 % sensitivity and 64.6 % specificity. The MSWS-12 cut-off score remained a significant predictor of faller status in the adjusted model (adjusted odds ratio [aOR]: 3.77, 95 % CI: 1.75, 8.15, P = .001), along with higher fatigue (aOR: 1.11, 95 % CI: 1.02, 1.20, P = .015).

Conclusion

PwMS with MSWS-12 scores ≥ 46 % were more likely to be fallers than those with lower scores. When used in conjunction with a clinician's judgement and other assessments, the MSWS-12 may be a useful screening tool for identifying PwMS who are fallers.