Meta- analysis demonstrated fallers perform significantly worse than non-fallers on all measures analysed except the Timed Up and Go Cognitive ( p < 0.05 ) , but discriminative ability of the measures is commonly not reported .
Of those reported , the Activities-specific Balance Confidence Scale had the highest area under the receiver operating characteristic curve value ( 0.92 ) , but without reporting corresponding measures of clinical utility .
Conclusion : Clinical measures of balance differ significantly between fallers and non-fallers but have poor predictive ability for falls risk in people with multiple sclerosis
Objective : To determine the ability of clinical measures of balance to distinguish fallers from non-fallers and to determine their predictive validity in identifying those at risk of falls .
Risk factors for falls in multiple sclerosis: an observational study
Background : People with multiple sclerosis ( MS ) experience frequent falls , which are associated with impairments and limitations to activities and participations . Objective : The objective of this paper is to evaluate falls risk factors using robust clinical measures . Methods : A total of 150 individuals ( confirmed MS diagnosis , Exp and ed Disability Status Scale ( EDSS ) 3.5–6.5 ) were recruited , with 148 participants included in the final analysis . Demographic data were collected and performance assessed in eight predictor measures  ( Physiological Profile Assessment ( PPA ) , Brief Ataxia Rating scale , Ashworth scale ( Ashworth ) , Modified Falls Efficacy scale , Symbol Digit Modalities Test , dual-task interference , lying/st and ing blood pressure , static/dynamic visual acuity )  . Participants prospect ively recorded falls over three months using a daily diary . People were classified as “ fallers ” based on reports of ≥ two falls . Results : A total of 104 participants recorded 672 falls ; 78 ( 52.7 % ) reported ≥ two falls . Continence issues , previous falls history and use of prescribed medications were each associated with increased risk of being a “ faller ” . Ashworth and PPA risk score contributed significantly to a logistic regression model predicting faller/non-faller classification . The reduced model ( Ashworth , PPA , EDSS ) showed fair-to-good predictive ability ( ROC c-statistic 0.73 , sensitivity 70 % , specificity 69 % ) . Conclusion : This study confirms the high prevalence of falls in ambulant people with MS . Important potentially modifiable risk factors are identified , suggesting aspects to target in falls interventions
Meta- analysis demonstrated fallers perform significantly worse than non-fallers on all measures analysed except the Timed Up and Go Cognitive ( p < 0.05 ) , but discriminative ability of the measures is commonly not reported .
Of those reported , the Activities-specific Balance Confidence Scale had the highest area under the receiver operating characteristic curve value ( 0.92 ) , but without reporting corresponding measures of clinical utility .
Conclusion : Clinical measures of balance differ significantly between fallers and non-fallers but have poor predictive ability for falls risk in people with multiple sclerosis
Objective : To determine the ability of clinical measures of balance to distinguish fallers from non-fallers and to determine their predictive validity in identifying those at risk of falls .