Predicting falls among patients with multiple sclerosis: Comparison of patient-reported outcomes and performance-based measures of lower extremity functions

Shirin Tajali; Mohammad-Jafar Shaterzadeh-Yazdi; Hossein Negahban; Jaap H van Dieën; Mohammad Mehravar; Nastaran Majdinasab; Amal Saki-Malehi; Razie Mofateh

doi:10.1016/j.msard.2017.06.014

Predicting falls among patients with multiple sclerosis: Comparison of patient-reported outcomes and performance-based measures of lower extremity functions

Mult Scler Relat Disord. 2017 Oct:17:69-74. doi: 10.1016/j.msard.2017.06.014. Epub 2017 Jun 27.

Authors

Shirin Tajali¹, Mohammad-Jafar Shaterzadeh-Yazdi², Hossein Negahban³, Jaap H van Dieën⁴, Mohammad Mehravar¹, Nastaran Majdinasab⁵, Amal Saki-Malehi⁶, Razie Mofateh¹

Affiliations

¹ Musculoskeletal Rehabilitation Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
² Musculoskeletal Rehabilitation Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran. Electronic address: Shaterzadeh.pt@gmail.com.
³ Department of Physical Therapy, School of Paramedical Sciences, Mashhad University of Medical Sciences, Mashhad, Iran; Orthopedic Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
⁴ Department of Human Movement Sciences, Research Institute MOVE, VU University, Amsterdam, The Netherlands.
⁵ Musculoskeletal Rehabilitation Research Center, Department of Neurology, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
⁶ Department of Biostatistics and Epidemiology, Health faculty, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.

PMID: 29055478
DOI: 10.1016/j.msard.2017.06.014

Abstract

Background: Accurate fall screening tools are needed to identify those multiple sclerosis (MS) patients at high risk of falling. The present study aimed 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 prospective 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.

Keywords: Falling; Multiple sclerosis; Patient-reported outcomes; Performance-based measures; Risk factor.

MeSH terms

Accidental Falls / prevention & control*
Adult
Fatigue
Female
Humans
Lower Extremity / physiopathology*
Male
Multiple Sclerosis / complications
Multiple Sclerosis / diagnosis*
Multiple Sclerosis / physiopathology
Patient Reported Outcome Measures
Postural Balance
Prospective Studies