Six-Minute Walk as a Measure of Walking Capacity and Endurance in Patients With Pediatric-Onset Multiple Sclerosis

Range of motion abnormalities in the lower limb joints during gait in youth with multiple sclerosis

BACKGROUND

The major objective of this study was to examine whether differences occur in the joint angles of the major lower limb joints while walking in youth with multiple sclerosis (YwMS) compared to age-gender-matched healthy youngsters.

METHODS

Gait analysis was collected using a six-camera Cartesian Optoelectronic Dynamic Anthropometer (CODA) 3D motion analysis system. To determine the gait normality in the YwMS group, we compared our results to reference gait data from normal youngsters. Gait data was divided according to gender and age subgroups (8-14, 15-18 years old).

RESULTS

The total sample included 26 YwMS (12 girls, 14 boys), 11 in the 8-14 age subgroup, and 15 in the 15-18 age subgroup. The mean expanded disability status scale score was 1.3 (S.D=1.0), indicating minimal disability. The total range of hip motion was significantly less in the YwMS group aged 15-18 (both genders) compared with the normative values. Additionally, the maximum flexion in the knee joint during gait was significantly less in boys in the 15 to 18 age subgroup (p<0.001). No differences were found in the hip and knee joint angles in the 8-14 age subgroup.

CONCLUSIONS

YwMS experience modifications in their gait pattern compared with age-gender-matched healthy youngsters. The MS teenagers demonstrated less range of movement in the hip joints and walked slower at a decreased pace than the healthy teenagers. By tracking gait patterns, healthcare providers can identify subtle changes that might facilitate timely interventions to prevent further mobility impairment in this young population.

Progression risk stratification with six-minute walk gait speed trajectory in multiple sclerosis

Background

Multiple Sclerosis (MS) disease progression has notable heterogeneity among patients and over time. There is no available single method to predict the risk of progression, which represents a significant and unmet need in MS.

Methods

MS and healthy control (HC) participants were recruited for a 2-year observational study. A latent-variable growth mixture model (GMM) was applied to cluster baseline 6-min walk gait speed trajectories (6MWGST). MS patients within different 6 MWGST clusters were identified and stratified. The group membership of these MS patients was compared against 2-year confirmed-disease progression (CDP). Clinical and patient-reported outcome (PRO) measures were compared between HC and MS subgroups over 2 years.

Results

62 MS and 41 HC participants completed the 2-year study. Within the MS cohort, 90% were relapsing MS. Two distinct patterns of baseline 6 MWGST emerged, with one cluster displaying a faster gait speed and a typical "U" shape, and the other showing a slower gait speed and a "flattened" 6 MWGST curve. We stratified MS participants in each cluster as low- and high-risk progressors (LRP and HRP, respectively). When compared against 2-year CDP, our 6 MWGST approach had 71% accuracy and 60% positive predictive value. Compared to the LRP group, those MS participants stratified as HRP (15 out of 62 MS participants), were on average 3.8 years older, had longer MS disease duration and poorer baseline performance on clinical outcomes and PROs scores. Over the subsequent 2 years, only the HRP subgroup showed a significant worsened performance on 6 MW, clinical measures and PROs from baseline.

Conclusion

Baseline 6 MWGST was useful for stratifying MS participants with high or low risks for progression over the subsequent 2 years. Findings represent the first reported single measure to predict MS disease progression with important potential applications in both clinical trials and care in MS.

Wearable Sensor Technologies to Assess Motor Functions in People With Multiple Sclerosis: Systematic Scoping Review and Perspective

BACKGROUND

Wearable sensor technologies have the potential to improve monitoring in people with multiple sclerosis (MS) and inform timely disease management decisions. Evidence of the utility of wearable sensor technologies in people with MS is accumulating but is generally limited to specific subgroups of patients, clinical or laboratory settings, and functional domains.

OBJECTIVE

This review aims to provide a comprehensive overview of all studies that have used wearable sensors to assess, monitor, and quantify motor function in people with MS during daily activities or in a controlled laboratory setting and to shed light on the technological advances over the past decades.

METHODS

We systematically reviewed studies on wearable sensors to assess the motor performance of people with MS. We scanned PubMed, Scopus, Embase, and Web of Science databases until December 31, 2022, considering search terms "multiple sclerosis" and those associated with wearable technologies and included all studies assessing motor functions. The types of results from relevant studies were systematically mapped into 9 predefined categories (association with clinical scores or other measures; test-retest reliability; group differences, 3 types; responsiveness to change or intervention; and acceptability to study participants), and the reporting quality was determined through 9 questions. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) reporting guidelines.

RESULTS

Of the 1251 identified publications, 308 were included: 176 (57.1%) in a real-world context, 107 (34.7%) in a laboratory context, and 25 (8.1%) in a mixed context. Most publications studied physical activity (196/308, 63.6%), followed by gait (81/308, 26.3%), dexterity or tremor (38/308, 12.3%), and balance (34/308, 11%). In the laboratory setting, outcome measures included (in addition to clinical severity scores) 2- and 6-minute walking tests, timed 25-foot walking test, timed up and go, stair climbing, balance tests, and finger-to-nose test, among others. The most popular anatomical landmarks for wearable placement were the waist, wrist, and lower back. Triaxial accelerometers were most commonly used (229/308, 74.4%). A surge in the number of sensors embedded in smartphones and smartwatches has been observed. Overall, the reporting quality was good.

CONCLUSIONS

Continuous monitoring with wearable sensors could optimize the management of people with MS, but some hurdles still exist to full clinical adoption of digital monitoring. Despite a possible publication bias and vast heterogeneity in the outcomes reported, our review provides an overview of the current literature on wearable sensor technologies used for people with MS and highlights shortcomings, such as the lack of harmonization, transparency in reporting methods and results, and limited data availability for the research community. These limitations need to be addressed for the growing implementation of wearable sensor technologies in clinical routine and clinical trials, which is of utmost importance for further progress in clinical research and daily management of people with MS.

TRIAL REGISTRATION

PROSPERO CRD42021243249; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=243249.