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 .
Predicting falls among patients with multiple sclerosis: Comparison of patient-reported outcomes and performance-based measures of lower extremity functions.
BACKGROUND Accurate fall screening tools are needed to identify those multiple sclerosis ( MS ) patients at high risk of falling . The present study aim ed at determining the validity of a series of performance-based measures ( PBMs ) of lower extremity functions and patient-reported outcomes ( PROs ) in predicting falls in a sample of MS patients ( n = 84 ) , who were ambulatory independent . METHODS Patients were assessed using the following PBMs : timed up and go ( TUG ) , timed 25-foot walk ( T25FW ) , cognitive T25FW , 2-min walk ( 2MW ) , and cognitive 2MW . Moreover , a series of valid and reliable PROs were filled in by participants including the activities-specific balance confidence ( ABC ) , 12-item multiple sclerosis walking scale ( MSWS-12 ) , fall efficacy scale international ( FES-I ) , and modified fatigue impact scale ( MFIS ) . The dual task cost ( DTC ) of 2MW and T25FW tests were calculated as a percentage of change in parameters from single to dual task conditions . Participants were classified as none-fallers and fallers ( ⩾1 ) based on their prospect i ve fall occurrence . RESULTS In the present study , 41(49 % ) participants recorded ≥ 1 fall and were classified as fallers . The results of logistic regression analysis revealed that each individual test , except DTC of 2MW and T25FW , significantly predicted future falls . However , considering the area under the curves ( AUCs ) , PROs were more accurate compared to PBMs . In addition , the results of multiple logistic regression with the first two factors extracted from principal component analysis revealed that both factor 1 ( PROs ) and factor 2 ( PBMs ) significantly predicted falls with a greater odds ratio ( OR ) for factor 1 ( factor 1 : P = < 0.0001 , OR = 63.41 ( 6.72 - 597.90 ) ) than factor 2 ( P < 0.05 , OR = 5.03 ( 1.33 - 18.99 ) ) . CONCLUSIONS The results of this study can be used by clinicians to identify and monitor potential fallers in MS patients
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 .