Assessing the Relationship between the Enhanced Gait Variability Index and Falls in Individuals with Parkinson's Disease

Neural correlates of dual-task walking in people with central neurological disorders: a systematic review

BACKGROUND

People with central neurological disorders experience difficulties with dual-task walking due to disease-related impairments. The objective of this review was to provide a comprehensive examination of the neural correlates (structural/functional brain changes) of dual-task walking in people with Parkinson's disease (PD), multiple sclerosis (MS), stroke, and Alzheimer's disease (AD).

METHODS

A systematic review of the literature was conducted, following PRISMA guidelines, on Medline, Embase, and Scopus. Included studies examined the relationship between structural and functional brain imaging and dual-task walking performance in people with PD, MS, stroke, and AD. Articles that met the inclusion criteria had baseline characteristics, study design, and behavioral and brain outcomes extracted. Twenty-three studies were included in this review.

RESULTS

Most structural imaging studies (75%) found an association between decreased brain integrity and poor dual-task performance. Specific brain regions that showed this association include the striatum regions and hippocampus in PD and supplementary motor area in MS. Functional imaging studies reported an association between increased prefrontal activity and maintained (compensatory recruitment) or decreased dual-task walking performance in PD and stroke. A subset (n = 2) of the stroke papers found no significant correlations. Increased supplementary motor area activity was associated with decreased performance in MS and stroke. No studies on AD were identified.

CONCLUSION

In people with PD, MS, and stroke, several neural correlates of dual-task walking have been identified, however, the direction of the association between neural and performance outcomes varied across the studies. The type of cognitive task used and presentation modality (e.g., visual) may have contributed to these mixed findings.

Assessment of Risk Factors for Falls among Patients with Parkinson's Disease

Introduction

The aim of this study was to assess the risk factors for falls in patients with Parkinson's disease.

Materials and Methods

The study comprised 53 participants (52.8% women and 47.2% men). The Hoehn and Yahr 5-point disability scale was used to assess the severity of Parkinson's disease. The Tinetti Balance and Gait Scale were used to evaluate the risk of falls. The Katz scale was used to test the independence of people with PD. The Falls Efficacy Scale-International Short Form (FES-I) was implemented to assess fear of falling.

Results

The majority of participants was at a high risk of falls, being at the same level for women and men. A significant relationship was noted between the risk of falls and subjective assessment of mobility (χ² = 31.86, p < 0.001), number of falls (χ² = 37.92, p < 0.001), independence of the subjects (χ² = 19.28, p < 0.001), type of injury suffered during the fall (χ² = 36.93, p < 0.001), external factors (χ² = 33.36, p < 0.001), and the level of fear of falling (χ² = 8.88, p < 0.001). A significant relationship also occurred between the number of falls and the fear of falling (χ² = 33.49, p < 0.001) and between the number of falls and disease severity (χ² = 45.34, p < 0.001). The applied physiotherapy did not reduce the risk of falls (χ² = 3.18, p = 0.17).

Conclusions

Individuals who rated their mobility as good or excellent were at a low risk of falls. People who fell more times were at a high risk of falling. People more independent were at a low risk of falls. Previous injuries were the most associated with being at risk of falling. Uneven surfaces and obstacles on one's path are the external factors most associated with the risk of falling. People with low levels of fall anxiety were at a low risk of falls. Most people with low fall anxiety have never fallen. Additionally, the majority of patients with stage 1 of the disease have not fallen at all. The reason for the ineffectiveness of physiotherapy may be due to the exercise programs used and the lack of systematic implementation of them. PD is different for each patient; thus, it is important to select individually customized physiotherapy depending on motor and nonmotor symptoms, as well as general health of a patient.

Gait variability is sensitive to detect Parkinson's disease patients at high fall risk

BACKGROUND

Gait disturbance is an important risk factor for falls in Parkinson's disease (PD). Using wearable sensors, we can obtain the spatiotemporal parameters of gait and calculate the gait variability. This prospective study aims to objectively evaluate the gait characteristics of PD fallers, and further explore the relationship between spatiotemporal parameters of gait, gait variability and falls in PD patients followed for six months.

METHODS

Fifty-one PD patients were enrolled in this study. A seven-meter timed up and go test was performed. Gait characteristics were determined by a gait analysis system. Patients were followed monthly by telephone until the occurrence of falls or till the end of six months. The patients were categorized into fallers and non-fallers based on whether fell during the follow-up period. Gait parameters were compared between two groups, and binary logistic regression was used to establish the falls prediction model. In the receiver-operating characteristic curve, area under the curve (AUC) was utilized to evaluate the prediction accuracy of each indicator.

RESULTS

All subjects completed the follow-up, and 14 (27.5%) patients reported falls. PD fallers had greater gait variability. The range of motion of the trunk in sagittal plane variability was an independent risk factor for falls and achieved moderate prediction accuracy (AUC = 0.751), and the logistic regression model achieved a good accuracy of falls prediction (AUC = 0.838).

CONCLUSIONS

Increased gait variability is a significant feature of PD fallers and is more sensitive to detect PD patients at high risk of falls than spatiotemporal parameters.