Digital Tool a Better Disability Measure in MS?

A digital tool to measure walking has the potential to improve measurement of disability among patients with multiple sclerosis (MS).

Dr Mark Gudesblatt

“When you measure disability, what you really want to know is how things are changing in the patient’s life and not your perception of how they’re changing,” said Mark Gudesblatt, MD, who presented a study comparing the technique, called quantitative gait analysis, to other measures at a poster session during the annual meeting held by the Americas Committee for Treatment and Research in Multiple Sclerosis (ACTRIMS).

The device, called Protokinetics, has been used in clinical studies for Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, stroke, Friederich’s ataxia, and other conditions. The device is a digitized carpet that senses weight change and pressure as the individual walks.

“We can actually measure performance, and the performance is not just how fast you walk 25 feet. We’re measuring things that underlie how you walk: step length, step length variability, velocity, weight shift, how much time you spend on one leg. So it’s like listening to a symphony. We’re not measuring just the trumpets or the violins, we’re measuring everything,” said Dr. Gudesblatt, who is medical director of the Comprehensive MS Center at South Shore Neurologic Associates, Patchogue, N.Y.

Commonly used measures include the Expanded Disability Status Scale (EDSS), the 25-foot time walk (25’TW), and the Timed Up and Go (TUG).

Those measures are useful but don’t really measure up to clinical need, Dr. Gudesblatt said. “What you want is no evidence of disease activity, whether that’s multiple dimensions of thinking or multiple dimensions of walking, or changes on an MRI that are not the radiologist’s impression. Patients always say: ‘Doc, I’m worse.’ And we say: ‘Well, your exam is unchanged, your MRI has not changed. But they are worse for reasons – either their perception or their performance. So you can measure this very granularly, and you can relate it to their fear of falling, their balance confidence. This ups the game,” said Dr. Gudesblatt.

“And here’s where it gets even more interesting. You can use this for signatures of disease,” he added. The data can, for example, suggest that instead of Parkinson’s disease, a patient may have a Parkinson’s variant. “What we’re doing is showing how the 25-foot timed walk and Timed Up and Go are very traditional, conservative measures. They’re equivalent to the Pony Express. They’re good, but not where you want to be.”

Technology provides more sensitive, but more complex data

Digital tools to measure a variety of functions, including gait, cognition, and upper limb function are becoming increasingly common in MS, according to Catherine Larochelle, MD, PhD, who was asked for comment. “They are easily providing measures that are likely more sensitive and diverse and probably more meaningful about the daily functional status of a person than our usual EDSS,” said Dr. Larochelle, who is an associate professor at Université de Montréal.

The next step is to determine how best to use the complex data that such devices generate. “Lots of research is being done to better understand how to use the rich but complex data obtained with these tools to provide useful information to people with MS and their clinical team, to help guide shared clinical decisions, and likely accelerate and improve outcomes in clinical trials. So this is a very exciting new era in terms of clinical neurological assessment,” said Dr. Larochelle.

Granular gait analysis

Dr. Gudesblatt and colleagues analyzed retrospective data from 105 people with MS (69% female; average age, 53.7 years). Participants underwent all tests on the same day. The digital gait analysis captured velocity, double support, cadence, functional ambulation profile, gait variability index, and walk ratio over three trials conducted at preferred walking speed (PWS) and during dual task walking.

There were statistically significant relationships (P ≤ .01) between TUG and 25’TW (R2 = 0.62). There were also significant relationships between 25’TW and digital parameters measured at PWS: velocity (R2 = 0.63); double support (R2 = 0.74); cadence (R2 = 0.56); and gait variability index (R2 = 0.54). During dual task walking, there were relationships between 25’TW and velocity (R2 = 0.53); double support (R2 = 0.30); cadence (R2 = 0.43); and gait variability index (R2 = 0.46).

TUG values were significantly associated with gait parameters during PWS: velocity (R2 = 0.71); double support (R2 = 0.75); cadence (R2 = 0.43); gait variability index (R2 = 0.45); and walk ratio (R2 = 0.06). During dual task walking, TUG values were significantly associated with velocity (R2 = 0.55), double support (R2 = 0.21), cadence (R2 = 0.45), and gait variability index (R2 = 0.39).

“With the availability multiple effective disease modifying therapies and the future potential of restorative or reparative treatments, more granular, validated standardized outcome measures are urgently needed,” said Dr. Gudesblatt. Analysis of gait cycle can provide clinically useful information not adequately captured by the current, more traditional approaches of measuring outcomes in MS.

Dr. Gudesblatt and Dr. Larochelle have no relevant financial disclosures.

This article originally appeared on, part of the Medscape Professional Network.

Source: Read Full Article