- •Falls are a common public health concern among persons with multiple sclerosis and can substantially decrease quality of life
- •Forward walking and balance measures exhibit limited sensitivity and predictive accuracy for falls
- •Backward walking has been linked to falls in older adults and may provide additional clues about fall risk in multiple sclerosis
- •Backward walking velocity is the strongest descriptor of retrospective fallers in our sample of 38 individuals with multiple sclerosis
- •Backward walking may be a useful tool to sensitively identify multiple sclerosis fallers along with current clinical methods
Individuals with multiple sclerosis experience deficits in mobility resulting in injurious falls. Fall detection has proved challenging; the majority of clinical measures rely on forward walking and balance measures, yet these measures have poor sensitivity and predictive value for differentiating between fallers and non-fallers. Backward walking better differentiates fallers from non-fallers in the elderly and other neurodegenerative diseases; therefore, the objective of this study was to examine both forward and backward walking to determine the strongest, unique contributor that differentiates fallers from non-fallers in persons with multiple sclerosis.
In a single session, spatiotemporal measures of forward and backward walking and fall history were collected. For the subsequent six months, individuals recorded falls in a fall diary. Discriminant function analysis was used to determine what variables most strongly and uniquely differentiate multiple sclerosis fallers from non-fallers.
Thirty-eight individuals with multiple sclerosis participated. Forward and backward velocity, stride length, and double support time as well as age, disease severity, and symptom duration were included in the models. Together, the variables differentiated between fallers and non-fallers (Wilk's lambda χ2 (8, N = 36) = 0.497, p<0.001) and in rank order, backward walking velocity was the strongest unique predictor. Repeating the analysis with a stepwise approach yielded that backward walking velocity in the first step (χ2 (1, 34) = 0.68, F = 15.96, p<0.001) and symptom duration in the second step (χ2 = 0.59, F (2, 33) = 11.46; p<0.001) most strongly differentiated retrospective fallers and non-fallers. This stepwise model with backward walking velocity and symptom duration accurately classified 76.3% of cases. Addition of forward walking measures did not significantly improve the models, and indeed the accuracy of classification was reduced to 71.1%. Exploratory analysis showed that backward walking velocity was the best predictor of prospectively reported fallers and non-fallers (χ2 (1, 7) = 0.43, F = 9.20, p = 0.02).
Backward walking velocity exhibits the highest effect magnitude and specificity in differentiating fallers from non-fallers in individuals with MS and demonstrates potential as clinically feasible and efficient fall detection tool.
To read this article in full you will need to make a payment
Purchase one-time access:Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
One-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
Subscribe:Subscribe to Multiple Sclerosis and Related Disorders
Already a print subscriber? Claim online access
Already an online subscriber? Sign in
Register: Create an account
Institutional Access: Sign in to ScienceDirect
- et al. Detection of subtle gait disturbance and future fall risk in early multiple sclerosis.J. Neurol. 2020; https://doi.org/10.1212/WNL.000000000000893810.1212/WNL.0000000000008938
- Risk factors for and management of cognitive dysfunction in multiple sclerosis.Nat. Rev. Neurol. 2011; 7 (PMID:21556031): 332-342
- Validity and Reliability of Four Clinical Gait Measures in Patients with Multiple Sclerosis.Int. J. MS Care. 2017; 19: 247-252https://doi.org/10.7224/1537-2073.2015-006
- Predicting falls in people with multiple sclerosis: falls history is as accurate as more complex measures.Mult. Scler. Int. 2013; 2013496325https://doi.org/10.1155/2013/496325
- Sensorimotor factors affecting gait variability in older people–a population-based study.J. Gerontol. A Biol. Sci. Med. Sci. 2010; 65: 386-392
- Validity of six balance disorders scales in persons with multiple sclerosis.Disabil. Rehabil. 2006; 28: 789-795https://doi.org/10.1080/09638280500404289
- Cognitive impairment in multiple sclerosis.Lancet Neurol. 2008; 7: 1139-1151https://doi.org/10.1016/S1474-4422(08)70259-X
- Utility of disease-specific measures and clinical balance tests in prediction of falls in persons with multiple sclerosis.J. Neurol. Phys. Ther. 2013; 37 (PMID:23872680): 99-104
- Executive dysfunction and cognitive impairment in a large community-based sample with multiple sclerosis from New Zealand: a descriptive study.Arch. Clin. Neuropsychol. 2008; 23: 1-19https://doi.org/10.1016/j.acn.2007.09.005
- Cognitive and motor functioning in patients with multiple sclerosis: neuropsychological predictors of walking speed and falls.J. Neurol. Sci. 2012; 316 (PMID:22353853): 42-46https://doi.org/10.1016/j.jns.2012.02.003
- Backward walking measures are sensitive to age-related changes in mobility and balance.Gait Posture. 2013; 37: 593-597https://doi.org/10.1016/j.gaitpost.2012.09.022
- Distinguishing among multiple sclerosis fallers, near-fallers and non-fallers.Mult. Scler. Relat. Disord. 2018; 19: 99-104https://doi.org/10.1016/j.msard.2017.11.019
- A systematic review of factors associated with accidental falls in people with multiple sclerosis: a meta-analytic approach.Clin. Rehabil. 2014; 28: 704-716https://doi.org/10.1177/0269215513517575
- Gait analysis in multiple sclerosis: characterization of temporal–spatial parameters using GAITRite functional ambulation system.Gait Posture. 2009; 29: 138-142https://doi.org/10.1016/j.gaitpost.2008.07.011
- Longitudinal assessment of falls in patients with Parkinson's disease using inertial sensors and the timed up and go test.J. Rehabili. Ass. Technol. Eng. 2018; 5https://doi.org/10.1177/2055668317750811
- Identification of risk factors for falls in multiple sclerosis: a systematic review and meta-analysis.Phys. Ther. 2013; 93: 504-513https://doi.org/10.2522/ptj.20120231
- Backward walking in Parkinson's disease.Mov. Disord. 2009; 24: 218-223https://doi.org/10.1002/mds.22330
- Measuring the impact of MS on walking ability: the 12-Item MS Walking Scale (MSWS-12).J. Neurol. 2003; 60: 31-36https://doi.org/10.1212/WNL.60.1.31
- Underreporting of fall injuries of older adults: implications for wellness visit fall risk screening.J. Am. Geriatr. Soc. 2018; 66: 1195-1200https://doi.org/10.1111/jgs.15360
- Cognitive function and walking velocity in people with dementia: a comparison of backward and forward walking.Gait Posture. 2017; 58: 481-486https://doi.org/10.1016/j.gaitpost.2017.09.009
- The relationship between fear of falling to spatiotemporal gait parameters measured by an instrumented treadmill in people with multiple sclerosis.Gait Posture. 2014; 39: 739-744https://doi.org/10.1016/j.gaitpost.2013.10.012
- Development of a Common Outcome Data Set for Fall Injury Prevention Trials: The Prevention of Falls Network Europe Consensus.J. Am. Geriatr. Soc. 2005; 53: 1618-1622https://doi.org/10.1111/j.1532-5415.2005.53455.x
- Understanding falls in multiple sclerosis: association of mobility status, concerns about falling, and accumulated impairments.Phys. Ther. 2012; 92: 407-415https://doi.org/10.2522/ptj.20100380
- Relationship of backward walking to clinical outcome measures used to predict falls in the older population: A factor analysis.Phys. Ther. Rehabil. 2017; 4: 14https://doi.org/10.7243/2055-2386-4-14
- Validity of the timed 25-foot walk as an ambulatory performance outcome measure for multiple sclerosis.Mult. Scler. 2017; 23: 704-710
- Walking speed: the functional vital sign.J. Aging Phys. Act. 2015; 23: 314-322https://doi.org/10.1123/japa.2013-0236
- Predicting accidental falls in people with multiple sclerosis—a longitudinal study.Clin. Rehabil. 2009; 23 (PMID:19218300): 259-269
- Clinical relevance using timed walk tests and “timed up and go” testing in persons with multiple sclerosis.Physiother. Res. Int. 2007; 12: 105-114https://doi.org/10.1002/pri.358
- Falls in people with MS–an individual data meta-analysis from studies from Australia, Sweden, United Kingdom and the United States.Mult. Scler. 2015; 21: 92-100https://doi.org/10.1177/1352458514538884
- Prognostic value of usual gait speed in well-functioning older people–results from the health, aging and body composition study.J. Am. Geriatr. Soc. 2005; 53 (Pennix backward walking): 1675-1680https://doi.org/10.1111/j.1532-5415.2005.53501.x
- Fear of falling and associated activity curtailment among middle aged and older adults with multiple sclerosis.Mult. Scler. 2007; 13: 1168-1175https://doi.org/10.1177/1352458507079260
- Characterization of compensatory stepping in people with multiple sclerosis.Arch. Phys. Med. Rehabil. 2015; 97: 513-552https://doi.org/10.1016/j.apmr.2015.10.103
- The ability of clinical balance measures to identify falls risk in multiple sclerosis: a systematic review and meta-analysis.Clin. Rehabil. 2018; 32: 571-582https://doi.org/10.1177/0269215517748714
- Spectrum of gait impairments in presymptomatic and symptomatic Huntington's disease.Mov. Disord. 2008; 23: 1100-1107https://doi.org/10.1002/mds.21987
- Cognitive, and Behavioral performance in middle-aged and older adults with multiple sclerosis.Topics in Ger. Rehab. 2019; 35: 199-208https://doi.org/10.1097/TGR.0000000000000235
- Mobility, balance and falls in persons with multiple sclerosis.PLoS One. 2011; 6: e28021https://doi.org/10.1371/journal.pone.0028021
- Walking direction and cognitive challenges on persons with multiple sclerosis.Mult. Scler. Int. 2013; 13: 4-14https://doi.org/10.1155/2013/859323
Published online: July 09, 2020
Accepted: July 9, 2020
Received in revised form: July 2, 2020
Received: March 27, 2020
Preliminary data from this manuscript was presented at the American Physical Therapy Association Combined Sections Meeting in January, 2018.
© 2020 Elsevier B.V. All rights reserved.