Bibliographic reference
Frederico Pieruccini‐Faria, Sandra E. Black, Mario Masellis, Eric E. Smith, Quincy J. Almeida, Karen Z. H. Li, Louis Bherer, Richard Camicioli, Manuel Montero‐Odasso. Gait variability across neurodegenerative and cognitive disorders: Results from the Canadian Consortium of Neurodegeneration in Aging (CCNA) and the Gait and Brain Study. Alzheimer’s & Dementia, 2021 DOI: 10.1002/alz.12298
Abstract
The framework and evolution of neurodegenerative diseases have yet to be fully understood. Recent studies suggest that a patient’s cognitive performance is strongly linked to their ability to maintain a continuous and steady gait.
This study confirms the association between diminished cognitive performance and gait impairment, independent of disease subtype. More specifically, the study identifies gait variability, defined as stride-to-stride fluctuations, as both a sign of neurodegenerative damage and a marker able to predict disease progression. Moreover, gait analysis seems to have the distinct potential of quickly identifying patients with Alzheimer’s disease. These patients in particular, compared to the others, presented significant variability in stride time, stride length, and double support time during gait analysis.
Background
As some previous studies affirm, there is a strong connection between gait impairments and cognitive decline. These gait alterations are fairly common in the clinical presentation of neurodegenerative diseases. By analyzing every single stride, it is possible to identify certain features (such as the length and duration of various phases of movement) that distinguish each step from the previous one.
In earlier literature, however, there’s a lack of systematic analysis of the various aspects of gait impairments as they relate to the most common neurodegenerative diseases.
Study parameters
This study is based on 500 participants divided into 9 groups: the control group; subjects with a diagnosis of Parkinson’s disease (PD); people with subjective cognitive impairment (also evaluated as a whole group of subjects without dementia); people with a diagnosed mild cognitive impairment (MCI); subjects with both PD and MCI (also evaluated as a whole group characterized by low level of cognitive degeneration); patients with Alzheimer’s disease (AD); subjects with a clinical case of dementia due to Parkinson’s disease (PDD); people with frontotemporal dementia; and people with Lewy body dementia (also evaluated as a whole group characterized by severe cognitive impairment).
During the gait analysis, 11 parameters were evaluated, divided into 4 categories:
- Rhythm
- Pace
- Variability
- Postural control
The information obtained was then analyzed both as unadjusted data and data adjusted for the participants’ main differences (age, sex, years of education, number of comorbidities).
The results
From all the gathered data, the study demonstrated that:
- The PD group had higher gait variability and lower postural control than that of the control group
- The AD group also had higher gait variability and lower postural control than that of the control group
- The PDD group had higher gait variability than that of the control group
In the end, only gait variability was demonstrated to be a significant factor in identifying patients with Parkinson’s Disease, dementia related to Parkinson’s Disease, and Alzheimer’s Disease. Specifically, the data shows that all 3 parameters considered in gait variability (stride time variability, stride length variability, and double support time variability) are statistically significant in identifying patients with PD, PDD and AD.
Furthermore, these 3 characteristics of gait variability are significantly associated with participants’ cognitive performance (evaluated with a MoCA score), independent of disease subtype. In particular, gait variability showed a high potential for identifying Alzheimer’s disease dementia, with a sensibility of 75-80% and specificity of 54-70%.
Taking into consideration the whole spectrum of Parkinson’s disease, gait variability explained the MoCA scores significantly better than the UPDRS-III system used to recruit the study subjects.
Study limitations
Considering the frontotemporal dementia group and the Lewy body dementia group, there are not enough participants to collect significant data about the correlation between gait impairments and cognitive performance. Moreover, the participants associated with these two groups are significantly younger than the subjects of the other groups. Even with a greater number of participants, data about frontotemporal dementia and Lewy body dementia may still not be relevant.
Focusing instead on the data related to the PD spectrum, the correlation between gait impairments and cognitive performance, although still significant, is attenuated by 33.6% when the severity of parkinsonism is included in the model as a covariate.
Finally, regarding the MCI group, the data differed from the control group in the direction expected but lacked statistical relevance, probably due to the many degrees of freedom in the analysis.
What’s new
Gait analysis, as it relates to neurodegenerative disorders, may be used as a factor to evaluate the cognitive progression of the disease, particularly in patients with Alzheimer’s disease (typically considered the archetypal cognitive disorder). Moreover, recognizing gait variability (both as a set of 3 characteristics, and by looking at each characteristic separately) can lead to the development of a highly specific and precise gait analysis protocol.
Future outlook
Future cohort studies would be necessary to confirm the data collected for each cognitive disorder evaluated, starting with Alzheimer’s disease. If these studies demonstrate the connection revealed in this experiment, it would be possible to identify neurodegenerative disorders at an early stage and evaluate their progression in a more comprehensive and relevant way.
Edited by Alessio Baricich
