Disinhibited Blink Reflex Recovery Is Related to Lateral Trunk Flexion in Parkinson Disease:

Predictors and Pathophysiology of Axial Postural Abnormalities in Parkinsonism: A Scoping Review

Background

Postural abnormalities involving the trunk are referred to as axial postural abnormalities and can be observed in over 20% of patients with Parkinson's disease (PD) and in atypical parkinsonism. These symptoms are highly disabling and frequently associated with back pain and a worse quality of life in PD. Despite their frequency, little is known about the pathophysiology of these symptoms and scant data are reported about their clinical predictors, making it difficult to prompt prevention strategies.

Objectives

We conducted a scoping literature review of clinical predictors and pathophysiology of axial postural abnormalities in patients with parkinsonism to identify key concepts, theories and evidence on this topic.

Methods

We applied a systematic approach to identify studies, appraise quality of evidence, summarize main findings, and highlight knowledge gaps.

Results

Ninety-two articles were reviewed: 25% reported on clinical predictors and 75% on pathophysiology. Most studies identified advanced disease stage and greater motor symptoms severity as independent clinical predictors in both PD and multiple system atrophy. Discrepant pathophysiology data suggested different potential central and peripheral pathogenic mechanisms.

Conclusions

The recognition of clinical predictors and pathophysiology of axial postural abnormalities in parkinsonism is far from being elucidated due to literature bias, encompassing different inclusion criteria and measurement tools and heterogeneity of patient samples. Most studies identified advanced disease stage and higher burden of motor symptoms as possible clinical predictors. Pathophysiology data point toward many different (possibly non-mutually exclusive) mechanisms, including dystonia, rigidity, proprioceptive and vestibular impairment, and higher cognitive deficits.

Postural deformities in Parkinson's disease: A bibliometric analysis based on web of science

Objective

Postural deformities are common debilitating conditions during the progression of Parkinson's disease (PD). However, the underlying pathophysiology and optimal treatment strategy are unclear. In this study, we aimed to identify primary research fields, important achievements and emerging trends in postural deformities in PD.

Methods

Web of Science Core Collection database was searched to retrieve all literature related to postural deformities in PD over the past 20 years. Data such as annual numbers of publications, countries of origin, publication journals, cooperation between countries, citation index and keywords were retrieved from the selected publications. Bibliometrix Package in R software were used for bibliometric analysis and visualization.

Results

In total, 211 publications that met the criteria were collected. Analyses had shown that the annual numbers of publications increased gradually with fluctuations. Japan was the most prolific country (n = 59). Italy participated in international cooperation the most frequently. Parkinsonism & related disorders (n = 25) took a prominent lead among all journals, and the most productive institution in this area was University of Verona (n = 27). The most local cited author was Tinazzi Michele. According to the thematic map, "scoliosis", "fusion", and "balance" have rapidly become research hot spots in related fields.

Conclusions

Articles pertaining to postural deformities in PD are still being published, in which the etiology is a combination of peripheral plus central involvement. Treatment approaches include rehabilitative exercises, oral medication, botulinum toxin injection, deep brain stimulation and spine surgery, which is getting current attention and would be a hot topic of future research.

How can neurophysiological studies help with movement disorders characterization in clinical practice? A review

BACKGROUND

Neurophysiological studies are ancillary tools to better understand the features and nature of movement disorders. Electromyography (EMG), together with electroencephalography (EEG) and accelerometer, can be used to evaluate a hypo and hyperkinetic spectrum of movements. Specific techniques can be applied to better characterize the phenomenology, help distinguish functional from organic origin and assess the most probable site of the movement generator in the nervous system.

OBJECTIVE

We intend to provide an update for clinicians on helpful neurophysiological tools to assess movement disorders in clinical practice.

METHODS

Non-systematic review of the literature published up to June 2019.

RESULTS

A diversity of protocols was found and described. These include EMG analyses to define dystonia, myoclonus, myokymia, myorhythmia, and painful legs moving toes pattern; EMG in combination with accelerometer to study tremor; and EEG-EMG to study myoclonus. Also, indirect measures of cortical and brainstem excitability help to describe and diagnose abnormal physiology in Parkinson's disease, atypical parkinsonism, dystonia, and myoclonus.

CONCLUSION

These studies can be helpful for the diagnosis and are usually underutilized in neurological practice.

Comparison of the Use of Blink Rate and Blink Rate Variability for Mental State Recognition

Recent research has unearthed that blink rate variability (BRV) can be employed as a psychophysiological measure. However, its efficiency for mental state recognition (MSR) has not been investigated yet. Because BRV can indicate dynamics inherent in eye blinks, we conjectured that BRV might exhibit stronger abilities for the MSR if compared with blink rate (BR), known as the leading indicator derived from eye blinks for MSR. Therefore, in this paper, we attempted to differentiate between high and low cognitive loads of an individual through the analyses of BR and BRV, respectively, which could be viewed as a preliminary study for comparing their MSR abilities. First, an n -back experiment was performed to collect data. Then, in order to characterize the phenomenon of BRV, the features were extracted from its time and frequency domains, respectively. Finally, the area under the curve (AUC) values of BRV and BR for MSR were estimated by the ten commonly used classifiers, respectively. The results indicated that BRV achieves significantly higher AUC values than BR, which suggests its strong potentiality for MSR. In sum, the BRV may prove to be a promising method for the MSR, which should be considered in the future.