Levodopa ONOFF-state freezing of gait: Defining the gait and non-motor phenotype

Comparison of sleep characteristics between Parkinson's disease with and without freezing of gait: A systematic review

Parkinson's disease (PD) is a neurodegenerative disorder characterized by a range of motor and non-motor symptoms. Among the motor complaints, freezing of gait (FOG) is a common and disabling phenomenon that episodically hinders patients' ability to produce efficient steps. Concurrently, sleep disorders are prevalent in PD and significantly impact the quality of life of affected individuals. Numerous studies have suggested a bidirectional relationship between FOG and sleep disorders. Therefore, our objective was to systematically review the literature and compare sleep outcomes in PD patients with FOG (PD + FOG) and those without FOG (PD-FOG). By conducting a comprehensive search of the PubMed and Web of Science databases, we identified 20 eligible studies for inclusion in our analysis. Our review revealed that compared to PD-FOG, PD + FOG patients exhibited more severe symptoms of rapid eye movement sleep behavior disorder in nine studies, increased daytime sleepiness in eight studies, decreased sleep quality in four studies, and more frequent and severe sleep disturbances in four studies. These findings indicate that PD + FOG patients generally experience worse sleep quality, higher levels of daytime sleepiness, and more disruptive sleep disturbances compared to those without FOG (PD-FOG). The association between sleep disturbances and FOG highlights the importance of evaluating and monitoring these symptoms in PD patients and open the possibility for future studies to assess the impact of managing sleep disturbances on the severity and occurrence of FOG, and vice versa.

Levodopa responsive gait dynamics in OFF- and ONOFF-state freezing of gait in Parkinson's disease

Background

In people with Parkinson's disease (PwPD), Freezing of Gait (FOG) episodes can be levodopa responsive (OFF-FOG) or levodopa unresponsive (ONOFF-FOG). Steady-state gait abnormalities, outside of the freezing episodes themselves also exist and the response to levodopa in these different groups has not been previously documented.

Objectives

To define the levodopa responsiveness in steady-state gait in OFF-FOG and ONOFF-FOG individuals.

Methods

Steady-state gait was collected in both the effective levodopa OFF-state (doses withheld > 8 h) and ON-state (1 h after levodopa dosing) in 32 PwPD; 10 with OFF-FOG and 22 with ONOFF-FOG. Levodopa response was compared between the two groups in the mean and variability (CV) of 8 spatiotemporal gait parameters.

Results

Both OFF-FOG and ONOFF-FOG participants showed improvement in mean stride-length and stride-velocity with levodopa. Improvement was seen in the OFF-FOG but not the ONOFF-FOG groups in mean stride-width and CV Integrated pressure with levodopa.

Discussion

In this study we show that steady-state gait deficits improve with levodopa in PwPD with OFF-FOG and ONOFF-FOG, even though episodes of FOG did not resolve in the ONOFF-FOG group. Lowering levodopa in people with ONOFF-FOG, or levodopa-unresponsive freezing of gait, should be undertake with caution and objective gait titration at different levodopa doses may be beneficial. Further work is needed to elucidate the pathophysiologic mechanisms of these differences.

Gait Declines Differentially in, and Improves Prediction of, People with Parkinson's Disease Converting to a Freezing of Gait Phenotype

BACKGROUND

Freezing of gait (FOG) is a debilitating, variably expressed motor symptom in people with Parkinson's disease (PwPD) with limited treatments.

OBJECTIVE

To determine if the rate of progression in spatiotemporal gait parameters in people converting from a noFOG to a FOG phenotype (FOGConv) was faster than non-convertors, and determine if gait parameters can help predict this conversion.

METHODS

PwPD were objectively monitored longitudinally, approximately every 6 months. Non-motor assessments were performed at the initial visit. Steady-state gait in the levodopa ON-state was collected using a gait mat (Protokinetics) at each visit. The rate of progression in 8 spatiotemporal gait parameters was calculated. FOG convertors (FOGConv) were classified if they did not have FOG at initial visit and developed FOG at a subsequent visit.

RESULTS

Thirty freezers (FOG) and 30 non-freezers were monitored an average of 3.5 years, with 10 non-freezers developing FOG (FOGConv). FOGConv and FOG had faster decline in mean stride-length, swing-phase-percent, and increase in mean total-double-support percent, coefficient of variability (CV) foot-strike-length and CV swing-phase-percent than the remaining non-freezers (noFOG). On univariate modeling, progression rates of mean stride-length, stride-velocity, swing-phase-percent, total-double-support-percent and of CV swing-phase-percent had high discriminative power (AUC > 0.83) for classification of the FOGConv and noFOG groups.

CONCLUSION

FOGConv had a faster temporal decline in objectively quantified gait than noFOG, and progression rates of spatiotemporal gait parameters were more predictive of FOG phenotype conversion than initial (static) parameters Objectively monitoring gait in disease prediction models may help define FOG prone groups for testing putative treatments.