Contributions
Abstract: P353
Type: Poster
Abstract Category: Clinical aspects of MS - Clinical assessment tools
Background: Falls are extremely prevalent occurrences among multiple sclerosis (MS) patients. Approximately 40-60% of MS patients will report a fall in any given year and at least half of those falls will result in an injury. It is important, therefore, to identify measures that can better assess patients" risk for falling and provide timely appropriate preventive therapies.
Objective: Our objective was to determine whether the Expanded Timed Up-and-Go (ETUG) and/or its individual components can be used to predict whether individuals are at risk for falling.
Methods: Participants for our study are part of a larger, ongoing Cardiovascular, Environmental and Genetic (CEG) study that aims to enroll 350 patients with MS or clinically isolated syndrome (CIS) and 150 healthy controls (HC). Our present analyses include 66 participants; 49 MS/CIS patients and 17 HC subjects. Participants were evaluated with Kurtzke Expanded Disability Status Scale (EDSS), the Timed 25-Foot walk (T25FW) and the ETUG. Subjects who reported falls during the past year were compared to subjects who did not with regards to demographic information, mobility and disability measures. Receiver operating characteristic (ROC) analyses were carried out to establish cutoff scores maximising sensitivity and specificity that were later used to determine whether ETUG and/or its timed components were of value in predicting which participants had reported falls.
Results: The average age for MS/CIS patients was 55.9 years (SD=12.0) and 51.0 (SD=17.5) years for HC. Both groups were predominantly female (81.6% in the MS/CIS group and 70.6% in the HC). For MS/CIS patients who took longer than 17.89 seconds to complete the ETUG, they were 13.87 times as likely to fall compared to those who took less time (p-value=0.001). Each of the 6 component mobility measures of the ETUG was able to significantly differentiate fallers from non-fallers in MS/CIS patients (all p-values ≤0.005). Four HC reported falls (23.5%), however the only component of the ETUG that was able to distinguish fallers from non-fallers in HCs at almost significant levels was the second walk (p=0.057).
Conclusion: The ETUG and its subsidiary components are sensitive measures for predicting which patients reported a fall in the past year. Though additional studies are needed to confirm our findings, the ETUG is an easy-to-administer, objective measure that may be able to predict falls in at-risk MS patients.
Disclosure:
Caila Vaughn: Nothing to disclose.
Katelyn Kavak: Nothing to disclose.
Sirin Gandhi: Nothing to disclose.
Ahmed Sanai: Nothing to disclose.
Dejan Jakimovski: Nothing to disclose.
Susan Bennett has participated in speakers´ bureaus and on advisory boards for Acorda Therapeutics.
Murali Ramanathan has received research funding from the National Multiple Sclerosis Society and the National Science Foundation. He receives royalty income from a self-published textbook.
Ralph Benedict received research support from Biogen, Novartis, Genzyme, Acorda and Mallinckrodt and provides consultation for Biogen, Genetech, Teva, Novartis, and Sanofi, and conducts CME for EMD Serono.
Robert Zivadinov has received personal compensation from Teva Pharmaceuticals, Biogen Idec, EMD Serono, Genzyme-Sanofi, Claret Medical, IMS Health and Novartis for speaking and consultant fees and has received financial support for research activities from Teva Pharmaceuticals, Genzyme-Sanofi, Novartis, Claret Medical, Intekrin and IMS Health.
Bianca Weinstock-Guttman has received personal compensation for consulting, speaking and serving on a scientific advisory board for Biogen Idec, Teva Neuroscience, EMD Serono, Novartis, Questcor and Genzyme& Sanofi and has received financial support for research activities from NMSS, NIH (not for the present study), ITN, Teva Neuroscience, Biogen Idec, EMD Serono, Aspreva, Novartis, Genzyme.
Abstract: P353
Type: Poster
Abstract Category: Clinical aspects of MS - Clinical assessment tools
Background: Falls are extremely prevalent occurrences among multiple sclerosis (MS) patients. Approximately 40-60% of MS patients will report a fall in any given year and at least half of those falls will result in an injury. It is important, therefore, to identify measures that can better assess patients" risk for falling and provide timely appropriate preventive therapies.
Objective: Our objective was to determine whether the Expanded Timed Up-and-Go (ETUG) and/or its individual components can be used to predict whether individuals are at risk for falling.
Methods: Participants for our study are part of a larger, ongoing Cardiovascular, Environmental and Genetic (CEG) study that aims to enroll 350 patients with MS or clinically isolated syndrome (CIS) and 150 healthy controls (HC). Our present analyses include 66 participants; 49 MS/CIS patients and 17 HC subjects. Participants were evaluated with Kurtzke Expanded Disability Status Scale (EDSS), the Timed 25-Foot walk (T25FW) and the ETUG. Subjects who reported falls during the past year were compared to subjects who did not with regards to demographic information, mobility and disability measures. Receiver operating characteristic (ROC) analyses were carried out to establish cutoff scores maximising sensitivity and specificity that were later used to determine whether ETUG and/or its timed components were of value in predicting which participants had reported falls.
Results: The average age for MS/CIS patients was 55.9 years (SD=12.0) and 51.0 (SD=17.5) years for HC. Both groups were predominantly female (81.6% in the MS/CIS group and 70.6% in the HC). For MS/CIS patients who took longer than 17.89 seconds to complete the ETUG, they were 13.87 times as likely to fall compared to those who took less time (p-value=0.001). Each of the 6 component mobility measures of the ETUG was able to significantly differentiate fallers from non-fallers in MS/CIS patients (all p-values ≤0.005). Four HC reported falls (23.5%), however the only component of the ETUG that was able to distinguish fallers from non-fallers in HCs at almost significant levels was the second walk (p=0.057).
Conclusion: The ETUG and its subsidiary components are sensitive measures for predicting which patients reported a fall in the past year. Though additional studies are needed to confirm our findings, the ETUG is an easy-to-administer, objective measure that may be able to predict falls in at-risk MS patients.
Disclosure:
Caila Vaughn: Nothing to disclose.
Katelyn Kavak: Nothing to disclose.
Sirin Gandhi: Nothing to disclose.
Ahmed Sanai: Nothing to disclose.
Dejan Jakimovski: Nothing to disclose.
Susan Bennett has participated in speakers´ bureaus and on advisory boards for Acorda Therapeutics.
Murali Ramanathan has received research funding from the National Multiple Sclerosis Society and the National Science Foundation. He receives royalty income from a self-published textbook.
Ralph Benedict received research support from Biogen, Novartis, Genzyme, Acorda and Mallinckrodt and provides consultation for Biogen, Genetech, Teva, Novartis, and Sanofi, and conducts CME for EMD Serono.
Robert Zivadinov has received personal compensation from Teva Pharmaceuticals, Biogen Idec, EMD Serono, Genzyme-Sanofi, Claret Medical, IMS Health and Novartis for speaking and consultant fees and has received financial support for research activities from Teva Pharmaceuticals, Genzyme-Sanofi, Novartis, Claret Medical, Intekrin and IMS Health.
Bianca Weinstock-Guttman has received personal compensation for consulting, speaking and serving on a scientific advisory board for Biogen Idec, Teva Neuroscience, EMD Serono, Novartis, Questcor and Genzyme& Sanofi and has received financial support for research activities from NMSS, NIH (not for the present study), ITN, Teva Neuroscience, Biogen Idec, EMD Serono, Aspreva, Novartis, Genzyme.