Association of sleep disturbance and freezing of gait in Parkinson disease: prevention/delay implications

Tang, Xiaohui; Yu, Lijia; Yang, Jingyun; Guo, Wenjing; Liu, Ying; Xu, Yaling; Wang, Xijin

doi:10.5664/jcsm.9022

Cited by 14 publications

(7 citation statements)

References 52 publications

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“…Consistent with other studies, our study showed that sleep disorder represented as a higher Epworth Sleepiness Scale score ( P = 0.012*) was predictive of FoG occurrence 16,22 . The pedunculopontine nucleus (PPN), a target for deep brain stimulation (DBS) for the treatment of parkinsonian gait disorders, may be involved in the association, as the same cells of large cholinergic neurons in PPN were involved in both arousal and motor control, confirmed in vitro, in vivo, and across species 22 . DBS in this region caused sleepiness or rapid transition into sleep, besides improving motor abilities in the FoG patients, further proving the association of sleep disorder with FoG around this region 23 .…”

Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 85%

“…Freezers had significantly sleep disturbances compared with the non-freezers 22 . Consistent with other studies, our study showed that sleep disorder represented as a higher Epworth Sleepiness Scale score ( P = 0.012*) was predictive of FoG occurrence 16,22 . The pedunculopontine nucleus (PPN), a target for deep brain stimulation (DBS) for the treatment of parkinsonian gait disorders, may be involved in the association, as the same cells of large cholinergic neurons in PPN were involved in both arousal and motor control, confirmed in vitro, in vivo, and across species 22 .…”

Section: Discussionmentioning

confidence: 85%

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Predicting the onset of freezing of gait in de novo Parkinson’s disease

Wang

Pan

Zhang

et al. 2021

Preprint

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Freezing of gait (FoG) is a debilitating symptom of Parkinson's disease (PD) related to higher risks of falls and poor quality of life. In this study, we predicted the onset of FoG in PD patients using a battery of risk factors from patients enrolled in the Parkinson's Progression Markers Initiative (PPMI) cohort. The endpoint was the presence of FoG, which was assessed every year during the five-year follow-up visit. Overall, 212 PD patients were included in analysis. Seventy patients (33.0%) developed FoG during the visit (pre-FoG group). Age, bradykinesia, TD/PIGD classification, fatigue, cognitive impairment, impaired autonomic functions and sleep disorder were found to be significantly different in patients from pre-FoG and non-FoG groups at baseline. The logistic regression model showed that motor factors such as TD/PIGD classification (OR = 2.67, 95% CI = 1.41-5.09), MDS-UPDRS part III score (OR = 1.05, 95% CI = 1.01-1.09) were associated with FoG occurrence. Several indicators representing non-motor symptoms such as SDMT total score (OR = 0.95, 95% CI = 0.91-0.98), HVLT immediate/Total recall (OR = 0.91, 95% CI = 0.86-0.97), MOCA (OR = 0.87, 95% CI = 0.76-0.99), Epworth Sleepiness Scale (OR = 1.13, 95% CI = 1.03-1.24), fatigue(OR = 1.98, 95% CI = 1.32-3.06), SCOPA-AUT gastrointestinal score (OR = 1.27, 95% CI = 1.09-1.49) and SCOPA-AUT urinary score (OR = 1.18, 95% CI = 1.06-1.32) were found to have the predictive value. PD patients that developed FoG showed a significant reduction of DAT uptake in the striatum. However, no difference at baseline was observed in genetic characteristics and CSF biomarkers between the two patient sets. Our model indicated that TD/PIGD classification, MDS-UPDRS total score, and Symbol Digit Modalities score were independent risk factors for the onset of FoG in PD patients. In conclusion, the combination of motor and non-motor features including the akinetic subtype and poor cognitive functions should be considered in identifying PD patients with high risks of FoG onset.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 85%

Section: Discussionmentioning

confidence: 85%

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Predicting the onset of freezing of gait in de novo Parkinson’s disease

Wang

Pan

Zhang

et al. 2021

Preprint

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“…The prevailing belief is that pathology of PD and various PD‐related motor or nonmotor symptoms trigger sleep disturbances in patients with PD. Recent research has demonstrated that poor sleep is related to a higher risk of PD and can exacerbate PD progression 3,7,13,25–28 . However, in most of these studies, sleep assessments relied on subjective measures, lacking objective results.…”

Section: Discussionmentioning

confidence: 99%

Correlation of slow‐wave sleep with motor and nonmotor progression in Parkinson's disease

Chen,

Zhao,

Chen

et al. 2023

Ann Clin Transl Neurol

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ObjectiveThis study aimed to explore the association between slow‐wave sleep and the progression of motor and nonmotor symptoms in patients with PD.MethodsData were collected from the Parkinson's Progression Markers Initiative study. Slow‐wave sleep, also known as deep non‐rapid eye movement (DNREM) sleep, was objectively assessed using the Verily Study Watch. Motor function was assessed using the Movement Disorder Society‐Unified Parkinson's Disease Rating Scale Part III score, Hoehn and Yahr stage, freezing of gait, motor fluctuations, and dyskinesia severity. Comprehensive assessments were conducted on nonmotor symptoms, including depression, anxiety, global cognitive function, and autonomic dysfunction. Statistical analyses involved repeated‐measures analysis of variance and linear regression.ResultsA total of 102 patients with PD were included in the study, with a median follow‐up duration of 3.4 years. In the long DNREM sleep duration group (n = 55), better motor function (DNREM × time interaction: F(1,100) = 4.866, p = 0.030), less severe sexual dysfunction (p = 0.026), and improved activities of daily living (p = 0.033) were observed at the last follow‐up visit compared with the short DNREM sleep duration group (n = 47). Reduced DNREM sleep duration is a risk factor for motor progression (β = −0.251, p = 0.021; 95% confidence interval = −0.465 to −0.038).InterpretationThe findings suggest an association between longer DNREM sleep duration and slower motor and nonmotor progression in patients with PD.

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“…Yet studies exploring the impact of poor sleep quality in PwPD are limited. Previous studies in PwPD correlated poor sleep quality with increased freezing of gait [25], gait deficits [26], impaired cognition, and mobility limitations [27]. However, the relationship of sleep quality with FOF and falls in PwPD has not been established.…”

Section: Introductionmentioning

confidence: 99%

Cognitive status and sleep quality can explain the fear of falling and fall history in people with Parkinson’s disease

Alissa,

Rehan,

Al-Sharman

et al. 2023

International Journal of Rehabilitation Research

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Fear of falling (FOF) is highly prevalent in people with Parkinson’s disease (PwPD) and contributes to high fall risk. Studies reporting on the relationship between falls, FOF, and non-motor factors such as cognitive function and sleep quality in Parkinson’s disease are limited. This study aimed to investigate (1) the relationship of cognitive function and sleep quality with FOF, and history of falls in PwPD; (2) differences in cognitive function and sleep quality between Parkinson’s disease fallers and non-fallers; and (3) a cut-off score for cognitive function and sleep quality to discriminate Parkinson’s disease fallers from non-fallers. Fifty PwPD were assessed for FOF [Falls Efficacy Scale-International (FES-I)], cognition [Montréal Cognitive Assessment (MOCA)], sleep quality [Pittsburgh Sleep Quality Index (PSQI)], and falls history. The MOCA is significantly associated with FES-I scores (R 2 = 0.429, P < 0.0001). Both MOCA (P = 0.012) and PSQI (P = 0.027) were associated with falls history even after adjusting for confounding factors (age, sex, L-dopa use, Parkinson’s disease severity). Both MOCA and PSQI scores were able to distinguish fallers from non-fallers with cut-off scores of 15.5 and 7.5, respectively. Although our findings revealed that both cognitive function and sleep quality are important factors influencing falls and FOF in PwPD, it remains to be determined if addressing cognitive impairments and poor sleep quality may favorably impact balance before integrating such screenings into fall prevention programs.

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Association of sleep disturbance and freezing of gait in Parkinson disease: prevention/delay implications

Cited by 14 publications

References 52 publications

Predicting the onset of freezing of gait in de novo Parkinson’s disease

Predicting the onset of freezing of gait in de novo Parkinson’s disease

Correlation of slow‐wave sleep with motor and nonmotor progression in Parkinson's disease

Cognitive status and sleep quality can explain the fear of falling and fall history in people with Parkinson’s disease

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