Destroyed non-dopaminergic pathways in the early stage of Parkinson's disease assessed by posturography

A comprehensive multivariate analysis of the center of pressure during quiet standing in patients with Parkinson's disease

BACKGROUND

We hypothesized that postural instability observed in individuals with Parkinson's disease (PD) can be classified as distinct subtypes based on comprehensive analyses of various evaluated parameters obtained from time-series of center of pressure (CoP) data during quiet standing. The aim of this study was to characterize the postural control patterns in PD patients by performing an exploratory factor analysis and subsequent cluster analysis using CoP time-series data during quiet standing.

METHODS

127 PD patients, 47 aged 65 years or older healthy older adults, and 71 healthy young adults participated in this study. Subjects maintain quiet standing for 30 s on a force platform and 23 variables were calculated from the measured CoP time-series data. Exploratory factor analysis and cluster analysis with a Gaussian mixture model using factors were performed on each variable to classify subgroups based on differences in characteristics of postural instability in PD.

RESULTS

The factor analysis identified five factors (magnitude of sway, medio-lateral frequency, anterio-posterior frequency, component of high frequency, and closed-loop control). Based on the five extracted factors, six distinct subtypes were identified, which can be considered as subtypes of distinct manifestations of postural disorders in PD patients. Factor loading scores for the clinical classifications (younger, older, and PD severity) overlapped, but the cluster classification scores were clearly separated.

CONCLUSIONS

The cluster categorization clearly identifies symptom-dependent differences in the characteristics of the CoP, suggesting that the detected clusters can be regarded as subtypes of distinct manifestations of postural disorders in patients with PD.

Machine Learning and Wearable Sensors for the Early Detection of Balance Disorders in Parkinson's Disease

Dynamic posturography combined with wearable sensors has high sensitivity in recognizing subclinical balance abnormalities in patients with Parkinson's disease (PD). However, this approach is burdened by a high analytical load for motion analysis, potentially limiting a routine application in clinical practice. In this study, we used machine learning to distinguish PD patients from controls, as well as patients under and not under dopaminergic therapy (i.e., ON and OFF states), based on kinematic measures recorded during dynamic posturography through portable sensors. We compared 52 different classifiers derived from Decision Tree, K-Nearest Neighbor, Support Vector Machine and Artificial Neural Network with different kernel functions to automatically analyze reactive postural responses to yaw perturbations recorded through IMUs in 20 PD patients and 15 healthy subjects. To identify the most efficient machine learning algorithm, we applied three threshold-based selection criteria (i.e., accuracy, recall and precision) and one evaluation criterion (i.e., goodness index). Twenty-one out of 52 classifiers passed the three selection criteria based on a threshold of 80%. Among these, only nine classifiers were considered "optimum" in distinguishing PD patients from healthy subjects according to a goodness index ≤ 0.25. The Fine K-Nearest Neighbor was the best-performing algorithm in the automatic classification of PD patients and healthy subjects, irrespective of therapeutic condition. By contrast, none of the classifiers passed the three threshold-based selection criteria in the comparison of patients in ON and OFF states. Overall, machine learning is a suitable solution for the early identification of balance disorders in PD through the automatic analysis of kinematic data from dynamic posturography.

Factors affecting postural instability after more than one-year bilateral subthalamic stimulation in Parkinson's disease: A cross-sectional study

Background

Balance impairment in Parkinson’s disease is multifactorial and its changes due to subthalamic stimulation vary in different studies.

Objective

We aimed to analyze the combination of predictive clinical factors of balance impairment in patients with Parkinson’s disease treated with bilateral subthalamic stimulation for at least one year.

Methods

We recruited 24 patients with Parkinson’s disease treated with bilateral subthalamic stimulation and 24 healthy controls. They wore an Opal monitor (APDM Inc.) consisting of three-dimensional gyroscopes and accelerometers in the lumbar region. We investigated four stimulation conditions (bilateral stimulation OFF, bilateral stimulation ON, and unilateral right- and left-sided stimulation ON) with four tests: stance on a plain ground with eyes open and closed, stance on a foam platform with eyes open and closed. Age, disease duration, the time elapsed after implantation, levodopa, and stimulation responsiveness were analyzed. The distance of stimulation location from the subthalamic motor center was calculated individually in each plane of the three dimensions. We analyzed the sway values in the four stimulation conditions in the patient group and compared them with the control values. We explored factor combinations (with age as confounder) in the patient group predictive for imbalance with cluster analysis and a machine‐learning‐based multiple regression method.

Results

Sway combined from the four tasks did not differ in the patients and controls on a group level. The combination of the disease duration, the preoperative levodopa responsiveness, and the stimulation responsiveness predicted individual stimulation-induced static imbalance. The more affected patients had more severe motor symptoms; primarily, the proprioceptive followed by visual sensory feedback loss provoked imbalance in them when switching on the stimulation.

Conclusions

The duration of the disease, the severity of motor symptoms, the levodopa responsiveness, and additional sensory deficits should be carefully considered during preoperative evaluation to predict subthalamic stimulation-induced imbalance in Parkinson’s disease.

Effects of task prioritization on a postural-motor task in early-stage Parkinson's disease: EEG connectivity and clinical implication

Appropriate attentional resource allocation could minimize exaggerated dual-task interference due to basal ganglia dysfunction in Parkinson's disease (PD). Here, we assessed the electroencephalography (EEG) functional connectivity to investigate how task prioritization affected posture-motor dual-tasks in PD. Sixteen early-stage PD patients and 16 healthy controls maintained balance in narrow stance alone (single-posture task) or while separating two interlocking rings (postural dual-task). The participants applied a posture-focus or supraposture-focus strategy in the postural dual-task. Postural sway dynamics, ring-touching time, and scalp EEG were analyzed. Both groups exhibited smaller postural sway size, postural determinism, and ring-touching time with the supraposture-focus versus posture-focus strategy. PD patients exhibited higher mean inter-regional connectivity strength than control subjects in both single and dual-task postural conditions. To cope with dual-task interference, PD patients increased inter-regional connectivity (especially with the posture-focus strategy), while control subjects reduced inter-regional connectivity. The difference in mean connectivity strength between the dual-task condition with supraposture-focus and single-posture condition was negatively correlated to the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III total scores and hand-related sub-scores. Our findings suggest differential task prioritization effects on dual-task performance and cortical reorganization between early-stage PD and healthy individuals. Early-stage PD patients are advocated to use a supraposture-focus strategy during a postural dual-task. In addition, with a supraposture-focus strategy, PD patients with mild motor severity could increase compensatory inter-regional connectivity to cope with dual-task interference.

Early balance impairment in Parkinson's Disease: Evidence from Robot-assisted axial rotations

OBJECTIVE

Early postural instability (PI) is a red flag for the diagnosis of Parkinson's disease (PD). Several patients, however, fall within the first three years of disease, particularly when turning. We investigated whether PD patients, without clinically overt PI, manifest abnormal reactive postural responses to ecological perturbations resembling turning.

METHODS

Fifteen healthy subjects and 20 patients without clinically overt PI, under and not under L-Dopa, underwent dynamic posturography during axial rotations around the longitudinal axis, provided by a robotic mechatronic platform. We measured reactive postural responses, including body displacement and reciprocal movements of the head, trunk, and pelvis, by using a network of three wearable inertial sensors.

RESULTS

Patients showed higher body displacement of the head, trunk and pelvis, and lower joint movements at the lumbo-sacral junction than controls. Conversely, movements at the cranio-cervical junction were normal in PD. L-Dopa left reactive postural responses unchanged.

CONCLUSIONS

Patients with PD without clinically overt PI manifest abnormal reactive postural responses to axial rotations, unresponsive to L-Dopa. The biomechanical model resulting from our experimental approach supports novel pathophysiological hypotheses of abnormal axial rotations in PD.

SIGNIFICANCE

PD patients without clinically overt PI present subclinical balance impairment during axial rotations, unresponsive to L-Dopa.

Association of Postural Instability with Autonomic Dysfunction in Early Parkinson’s Disease

Background: There have been several pathologic data that support an association between postural instability (PI) and autonomic dysfunction in Parkinson’s disease (PD). The purpose of this study was to investigate the correlation of PI and autonomic deficits in early PD. Methods: We collected 17 patients with a diagnosis of early PD. PI was assessed by computerized dynamic posturography (CDP). Standardized autonomic function test (AFT) and time and frequency domain spectral analysis of heart rate variability (HRV) were performed. CDP data obtained from the 21 patients were compared to that from age- and sex-matched healthy controls. We collected HRV data from 18 other age- and sex-matched controls. All patients were evaluated in the “OFF” state. We used Mann–Whitney U-test to compare parameters of CDP between the early PD and control groups. Spearman correlation was used for correlation analysis between parameters of CDP and autonomic function test in PD patients. Results: Most patients (76.5%) showed mild or moderate autonomic dysfunction in the standardized AFT. In CDP, sensory ratios of equilibrium score (e.g., visual and vestibular) and composite scores were significantly lower in PD patients than in controls. In HRV, the low-frequency/high-frequency ratio during the tilt and the gap of low- frequency/high-frequency ratio from supine to tilt were significantly different in both groups. The parameters of time and frequency domains of HRV reflecting parasympathetic function were correlated with equilibrium scores for somatosensory organization test in CDP. Discussion: PI was associated with parasympathetic autonomic dysfunction in early PD. This result was in accordance with a previous assumption that PI in PD is related to parasympathetic cholinergic neuron loss in the brainstem.

Postural instability years after stroke

BACKGROUND

Following a stroke, balance disturbances often persist despite full recovery of the paretic side.

AIMS

The aims were to determine how long postural instability could be detected after stroke and the differences in post-stroke patients under and above 65 years of age.

METHODS

Static and dynamic posturography (passing weights from hand to hand around the body) measurements were performed on 29 patients with stroke after 3 ± 2.4 years (≤65 years) and 4.7 ± 3.3 years. (> 65 years) compared with 38 controls.

RESULTS

Only the pathway and the velocity assessed by dynamic posturography were significantly higher (p < 0.05) in the younger group of patients compared with the controls. The older group of patients had significantly elevated parameters measured by both static (p < 0.01) and dynamic posturography (p < 0.05).

CONCLUSIONS

we conclude, using a sensitive and reproducible method to assess both static and dynamic adjustments to maintain balance, that postural instability is significantly greater in post-stroke patients than control subjects. This difference is demonstrable up to 4 years after stroke, despite full recovery of the affected side.