A sensitive data analysis approach for detecting changes in dynamic postural stability

Effects of osteopathic manipulative treatment vs. osteopathic cranial manipulative medicine on Parkinsonian gait

CONTEXT

Sixty thousand people are diagnosed with Parkinson's disease (PD) each year, making it the second most common neurodegenerative disorder. PD results in a variety of gait disturbances, including muscular rigidity and decreased range of motion (ROM), that increase the fall risk of those afflicted. Osteopathic manipulative treatment (OMT) emphasizes the central role of the musculoskeletal system, which could be ideal for addressing the somatic dysfunction associated with neurodegeneration in PD. The close anatomical relationship of structures implicated in PD within the skull and the increased frequency of strain patterns raise the question of whether osteopathic cranial manipulative medicine (OCMM) can improve gait performance by improving circulation to the affected nervous tissue. However, there have been few studies in recent years that explore the effects of a standardized OMT protocol on Parkinsonian gait characteristics, and there have been few studies that include OCMM techniques.

OBJECTIVES

This study aims to determine whether a single session of OMT or OMT + OCMM can improve the gait of individuals with PD by addressing joint restrictions in the sagittal plane and by increasing ROM in the lower limb.

METHODS

The following study is a two-group, randomized controlled trial in which individuals with PD (n=45) and age-matched healthy control participants (n=45) were recruited from the community. PD participants were included if they were otherwise healthy, able to stand and walk independently, had not received OMT or physical therapy (PT) within 30 days of data collection, and had idiopathic PD in Hoehn and Yahr stages 1.0-3.0. PD participants were randomly assigned to one of three experimental treatment protocols: a 'whole-body' OMT protocol (OMT-WB), which included OMT and OCMM techniques; a 'neck-down' OMT protocol (OMT-ND), including only OMT techniques; and a sham treatment protocol. Control participants were age-matched to a PD participant and were provided the same OMT experimental protocol. An 18-camera motion analysis system was utilized to capture 3-dimensional (3D) position data in a treadmill walking trial before and after the assigned treatment protocol. Pretreatment and posttreatment hip, knee, and ankle ROM were compared with paired t-tests, and joint angle waveforms during the gait cycle were analyzed with statistical parametric mapping (SPM), which is a type of waveform analysis.

RESULTS

Individuals with PD had significantly reduced hip and knee extension in the stance phase compared to controls (32.9-71.2% and 32.4-56.0% of the gait cycle, respectively). Individuals with PD experienced a significant increase in total sagittal hip ROM (p=0.038) following a single session of the standardized OMT-WB treatment protocol. However, waveform analysis found no significant differences in sagittal hip, knee, or ankle angles at individual points of the gait cycle following OMT-WB, OMT-ND, or sham treatment protocols.

CONCLUSIONS

The increase in hip ROM observed following a single session of OMT-WB suggests that OCMM in conjunction with OMT may be useful for improving gait kinematics in individuals with PD. Longitudinal studies over multiple visits are needed to determine the long-term effect of regular OMT and OMT+OCMM treatments on Parkinsonian gait characteristics.

Sample size estimation in locomotion kinematics and electromyography for statistical parametric mapping

In biomechanics, kinematic and electromyographic data can be represented as one-dimensional (1D) waveforms and compared by using 1D hypothesis tests. These statistical techniques are increasingly applied in the study of locomotion. However, although widely agreed as a key step to obtain reliable and replicable findings, no a priori sample size estimation is usually conducted. This can also be done in 1D tests by calculating the statistical power - i.e., the probability of rejecting the null hypothesis when it is false - by using statistical parametric mapping. With the present study we characterised the parameters needed to estimate sample size in locomotion, and how they impact on statistical power in 1D tests. First, noise and signal in kinematics and electromyography were defined using experimental data on locomotion in physiological and pathological participants. Then, 1D power analysis was performed in representative conditions, and a dataset of tabulated sample sizes was generated. Kinematic and electromyographic data showed a smooth Gaussian noise, with amplitude and full-width-at-half-maximum depending on the physiological or pathological condition, and the considered joint or muscle. Given a certain noise, statistical power increased i) with greater signal amplitude and signal full-width-at-half-maximum, ii) when setting a region of interest and iii) when using a paired (vs. unpaired) study design. The present work provides initial benchmarks for appropriate sampling in 1D hypothesis testing, meant to evaluate statistical power in 1D tests and assists sample size estimation in studies on locomotion.