Association of fall risk factors and non-motor symptoms in patients with early Parkinson's disease

Risk factors for falls in Parkinson's disease: a cross-sectional observational and Mendelian randomization study

Background

Patients with Parkinson's disease (PD) exhibit a heightened risk of falls and related fractures compared to the general population. This study aims to assess the clinical characteristics associated with falls in the patient with PD and to gain further insight into these factors through Mendelian randomization analysis.

Methods

From January 2013 to December 2023, we included 591 patients diagnosed with Parkinson's disease at Shenzhen Baoan People's Hospital. Using univariate and multivariate logistic regression analyses, we identified clinical variables associated with falls. We constructed a nomogram based on these variables and evaluated the predictive efficacy of the model. Additionally, we employed summary statistics from genome-wide association studies to conduct two-sample Mendelian randomization (MR) analyses on key variables influencing falls.

Results

Compared to the control group, we identified osteoporosis, motor dysfunction, higher Hoehn and Yahr scale as significant risk factors for falls in PD patients. Conversely, treatment with levodopa and a higher level of education exhibited a protective effect against the risk of falling. MR analysis further confirmed a causal relationship between osteoporosis, education level and falls in PD patients.

Conclusion

Osteoporosis and educational attainment are correlated with falls in Parkinson's disease.

Association between autonomic dysfunction with motor and non-motor symptoms in patients with Parkinson's disease

To investigate the association between autonomic dysfunction (AutD) and motor as well as non-motor symptoms (NMS) in patients with Parkinson's disease (PD). Fifty-three PD patients were divided into two groups based on the number of domains affected by AutD: a multi-domain AutD group (AutD-M) and a single-domain AutD group (AutD-S), as evaluated using the Scale for Outcomes in Parkinson's disease-Autonomic (SCOPA-AUT), which assesses autonomic symptoms, one of the NMS. A comprehensive comparison was conducted between the two groups, including clinical measures such as clinical scales, quantitative evaluations of motor function and exercise capacity. Spearman correlation analysis was employed to investigate the relationship between AutD severity and PD symptoms. Additionally, we performed multiple linear regression model analysis to determine whether associations between SCOPA-AUT scores and clinical assessments remained significant after adjusting for Hoehn and Yahr stage, sex, and age. PD patients in the AutD-M group exhibited significantly more severe NMS and motor symptoms compared to those in the AutD-S group. In correlation analysis, SCOPA-AUT scores showed significant correlations with multiple clinical symptoms, such as most of the NMS, 10-MWT and CPET parameters. Furthermore, regression analysis also revealed that more pronounced fatigue, anxiety, depressive symptoms, worse walking speed and impaired exercise capacity were associated with higher SCOPA-AUT scores. The presence of AutD is correlated with emotional disturbances, decreased exercise endurance, and impaired gait function in patients with PD. Early management of AutD may prove beneficial in alleviating some NMS and motor symptoms in PD.

Prognostic factors for falls in Parkinson's disease: a systematic review

BACKGROUND

Falls represent a critical concern in Parkinson's disease (PD), contributing to increased morbidity and reduced quality of life.

PURPOSE

We conducted a systematic review to assess the prognostic factors associated with falls in PD, aiming to provide a comprehensive overview of relevant demographic and clinical parameters, and aid neurologists in identifying subsets of PD patients most susceptible to falls and associated injuries.

METHODS

PubMed and Web of Science databases were searched for prospective studies assessing factors associated with falls in ambulatory PD patients across different settings, from inception to August 2023. Data extraction was conducted using CHARMS-PF checklist and risk of bias was assessed with QUIPS tool. PRISMA guidelines were followed.

RESULTS

The initial search yielded 155 references. Thirty-four studies, involving a total of 3454 PD patients, were included in the final analysis. The mean pooled age was 67.6 years, and 45.1% were women. PD patients presented mild motor impairment (UPDRS III score 27.8) with mean pooled disease duration of 5.7 years. Gait and balance disorders and history of prior falls emerged as the most consistent predictors of falls across studies. Disease duration, disease severity, dysautonomic symptoms, freezing of gait, frontal cognitive functions, and PD medication dosages yielded inconsistent findings. Conversely, dyskinesias, age, sex, and depression were unrelated to future falls in PD. Logistic regression models were most commonly employed to identify factors significantly associated with falls in PD. Substantial heterogeneity prevailed in the inclusion of confounding factors.

CONCLUSION

The evidence suggests that previous history of falls, gait disorders, and poor balance are robust prognostic markers for falls in PD.

Telemedicine-Based Risk Program to Prevent Falls Among Older Adults: Protocol for a Randomized Quality Improvement Trial

BACKGROUND

The Center for Disease Control and Prevention's Stopping Elderly Accidents, Deaths, and Injuries (STEADI) initiative offers health care providers tools and resources to assist with fall risk screening and multifactorial fall risk assessment and interventions. Its effectiveness has never been evaluated in a randomized trial.

OBJECTIVE

This study aims to describe the protocol for the STEADI Options Randomized Quality Improvement Trial (RQIT), which was designed to evaluate the impact on falls and all-cause health expenditures of a telemedicine-based form of STEADI implemented among older adults aged 65 years and older, within a primary care setting.

METHODS

STEADI Options was a pragmatic RQIT implemented within a health system comparing a telemedicine version of the STEADI fall risk assessment to the standard of care (SOC). Before screening, we randomized all eligible patients in participating clinics into the STEADI arm or SOC arm based on their scheduled provider. All received the Stay Independent screener (SIS) to determine fall risk. Patients were considered at risk for falls if they scored 4 or more on the SIS or answered affirmatively to any 1 of the 3 key questions within the SIS. Patients screened at risk for falls and randomized to the STEADI arm were offered a registered nurse (RN)-led STEADI assessment through telemedicine; the RN provided assessment results and recommendations to the providers, who were advised to discuss fall-prevention strategies with their patients. Patients screened at risk for falls and randomized to the SOC arm were asked to participate in study data collection only. Data on recruitment, STEADI assessments, use of recommended prevention services, medications, and fall occurrences were collected using electronic health records and patient surveys. Using staff time diaries and administrative records, the study prospectively collected data on STEADI implementation costs and all-cause outpatient and inpatient charges incurred over the year following enrollment.

RESULTS

The study enrolled 720 patients (n=307, 42.6% STEADI arm; n=353, 49% SOC arm; and n=60, 8.3% discontinued arm) from September 2020 to December 2021. Follow-up data collection was completed in January 2023. As of February 2024, data analysis is complete, and results are expected to be published by the end of 2025.

CONCLUSIONS

The STEADI RQIT evaluates the impact of a telemedicine-based, STEADI-based fall risk assessment on falls and all-cause health expenditures and can provide information on the intervention's effectiveness and cost-effectiveness.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05390736, http://clinicaltrials.gov/ct2/show/NCT05390736.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR1-10.2196/54395.

Association between falls and nonmotor symptoms in patients with Parkinson's disease

INTRODUCTION

Parkinson's disease (PD) is a chronic neurodegenerative disorder. Falls are common in patients with PD and can lead to disability, bedridden status, and death. The mechanisms of falls induced by symptoms of PD have not been fully clarified. We investigated the association between falls and nonmotor symptoms in PD patients.

METHODS

A total of 361 patients with Parkinson's disease were included. Whether the patients had fallen in the past half a year was recorded. Nonmotor symptoms were assessed by 30 items from the nonmotor symptom questionnaire (NMS Quest), Parkinson's Disease Sleep Scale (PDSS), Hamilton Depression Scale (HAMD), Hamilton Anxiety Scale (HAMA), and Montreal Cognitive Assessment Scale (MOCA).

RESULTS

A total of 63 patients experienced falls in the past six months, with an incidence of 17.5%. The patients with falls were elderly, had severe motor symptoms and disease severity, and the proportion of diabetic patients who experienced falls was higher. Adjusted for the above factors, the results showed that patients with falls had higher PD-NMS, HAMD and HAMA scores, but there was no significant difference in the total score and subscores of the MoCA scale between the two groups. The risk factors related to falling included age, history of diabetes, depression (HAMD), HAMD cognitive impairment, NMS urinary tract and NMS postural hypotension.

CONCLUSIONS

Falls were a common symptom in patients with PD and were not only related to motor symptoms but also closely related to nonmotor symptoms. urinary tract symptoms, postural hypotension, depression and HAMD cognitive impairment were risk factors related to falling in patients with PD.

Regional homogeneity and functional connectivity of freezing of gait conversion in Parkinson's disease

Background

Freezing of gait (FOG) is common in the late stage of Parkinson's disease (PD), which can lead to disability and impacts the quality of life. Therefore, early recognition is crucial for therapeutic intervention. We aimed to explore the abnormal regional homogeneity (ReHo) and functional connectivity (FC) in FOG converters and evaluate their diagnostic values.

Methods

The data downloaded from the Parkinson's Disease Progression Markers Project (PPMI) cohort was subdivided into PD-FOG converters (n = 16) and non-converters (n = 17) based on whether FOG appeared during the 3-year follow-up; 16 healthy controls were well-matched. ReHo and FC analyses were used to explore the variations in spontaneous activity and interactions between significant regions among three groups of baseline data. Correlations between clinical variables and the altered ReHo values were assessed in FOG converter group. Last, logistic regression and receiver operating characteristic curve (ROC) were used to predict diagnostic value.

Results

Compared with the non-converters, FOG converters had reduced ReHo in the bilateral medial superior frontal gyrus (SFGmed), which was negatively correlated with the postural instability and gait difficulty (PIGD) score. ReHo within left amygdala/olfactory cortex/putamen (AMYG/OLF/PUT) was decreased, which was correlated with anxiety and autonomic dysfunction. Also, increased ReHo in the left supplementary motor area/paracentral lobule was positively correlated with the rapid eye movement sleep behavior disorder screening questionnaire. FOG converters exhibited diminished FC in the basal ganglia, limbic area, and cognitive control cortex, as compared with non-converters. The prediction model combined ReHo of basal ganglia and limbic area, with PIGD score was the best predictor of FOG conversion.

Conclusion

The current results suggested that abnormal ReHo and FC in the basal ganglia, limbic area, and cognitive control cortex may occur in the early stage of FOG. Basal ganglia and limbic area dysfunction combined with higher PIGD score are useful for the early recognition of FOG conversion.

Predicting the fatigue in Parkinson's disease using inertial sensor gait data and clinical characteristics

Objectives

The study aimed to analyze the clinical features and gait characteristics of patients with Parkinson's disease (PD) who also suffer from fatigue and to develop a model that can help identify fatigue states in the early stages of PD.

Methodology

A total of 81 PD patients have been enrolled for the Parkinson's Fatigue Scale (PFS-16) assessment and divided into two groups: patients with or without fatigue. Neuropsychological assessments of the two groups, including motor and non-motor symptoms, were collected. The patient's gait characteristics were collected using a wearable inertial sensor device.

Results

PD patients who experienced fatigue had a more significant impairment of motor symptoms than those who did not, and the experience of fatigue became more pronounced as the disease progressed. Patients with fatigue had more significant mood disorders and sleep disturbances, which can lead to a poorer quality of life. PD patients with fatigue had shorter step lengths, lower velocity, and stride length and increased stride length variability. As for kinematic parameters, PD patients with fatigue had lower shank-forward swing max, trunk-max sagittal angular velocity, and lumbar-max coronal angular velocity than PD patients without fatigue. The binary logistic analysis found that Movement Disorder Society-Unified Parkinson's Disease Rating Scale-I (MDS-UPDRS-I) scores, Hamilton Depression Scale (HAMD) scores, and stride length variability independently predicted fatigue in PD patients. The area under the curve (AUC) of these selected factors in the receiver operating characteristic (ROC) analysis was 0.900. Moreover, HAMD might completely mediate the association between Hamilton Anxiety Scale (HAMA) scores and fatigue (indirect effect: β = 0.032, 95% confidence interval: 0.001-0.062), with a percentage of mediation of 55.46%.

Conclusion

Combining clinical characteristics and gait cycle parameters, including MDS-UPDRS-I scores, HAMD scores, and stride length variability, can identify PD patients with a high fatigue risk.

Abnormal dynamic functional connectivity changes correlated with non-motor symptoms of Parkinson’s disease

Background

Non-motor symptoms are common in Parkinson’s disease (PD) patients, decreasing quality of life and having no specific treatments. This research investigates dynamic functional connectivity (FC) changes during PD duration and its correlations with non-motor symptoms.

Methods

Twenty PD patients and 19 healthy controls (HC) from PPMI dataset were collected and used in this study. Independent component analysis (ICA) was performed to select significant components from the entire brain. Components were grouped into seven resting-state intrinsic networks. Static and dynamic FC changes during resting-state functional magnetic resonance imaging (fMRI) were calculated based on selected components and resting state networks (RSN).

Results

Static FC analysis results showed that there was no difference between PD-baseline (PD-BL) and HC group. Network averaged connection between frontoparietal network and sensorimotor network (SMN) of PD-follow up (PD-FU) was lower than PD-BL. Dynamic FC analysis results suggested four distinct states, and each state’s temporal characteristics, such as fractional windows and mean dwell time, were calculated. The state 2 of our study showed positive coupling within and between SMN and visual network, while the state 3 showed hypo-coupling through all RSN. The fractional windows and mean dwell time of PD-FU state 2 (positive coupling state) were statistically lower than PD-BL. Fractional windows and mean dwell time of PD-FU state 3 (hypo-coupling state) were statistically higher than PD-BL. Outcome scales in Parkinson’s disease–autonomic dysfunction scores of PD-FU positively correlated with mean dwell time of state 3 of PD-FU.

Conclusion

Overall, our finding indicated that PD-FU patients spent more time in hypo-coupling state than PD-BL. The increase of hypo-coupling state and decrease of positive coupling state might correlate with the worsening of non-motor symptoms in PD patients. Dynamic FC analysis of resting-state fMRI can be used as monitoring tool for PD progression.

Association of Depression With Early Occurrence of Postural Instability in Parkinson's Disease

OBJECTIVE

Depression in Parkinson's disease (PD) affects the quality of life of patients. Postural instability and gait disturbance are associated with the severity and prognosis of PD. We investigated the association of depression with axial involvement in early-stage PD patients.

METHODS

This study involved 95 PD patients unexposed to antiparkinsonian drugs. After a baseline assessment for depression, the subjects were divided into a depressed PD group and a nondepressed PD group. Analyses were conducted to identify an association of depression at baseline with the following outcome variables: the progression to Hoehn and Yahr scale (H-Y) stage 3, the occurrence of freezing of gait (FOG), levodopa-induced dyskinesia, and wearing-off. The follow-up period was 53.40 ± 16.79 months from baseline.

RESULTS

Kaplan-Meier survival curves for H-Y stage 3 and FOG showed more prominent progression to H-Y stage 3 and occurrences of FOG in the depressed PD group than in the nondepressed PD group (log-rank p = 0.025 and 0.003, respectively). Depression in drug-naïve, early-stage PD patients showed a significant association with the progression to H-Y stage 3 (hazard ratio = 2.55; 95% confidence interval = 1.32-4.93; p = 0.005), as analyzed by Cox regression analyses. In contrast, the occurrence of levodopa-induced dyskinesia and wearing-off did not differ between the two groups (log-rank p = 0.903 and 0.351, respectively).

CONCLUSION

Depression in drug-naïve, early-stage PD patients is associated with an earlier occurrence of postural instability. This suggests shared nondopaminergic pathogenic mechanisms and potentially enables the prediction of early development of postural instability.

Association Between Gait and Dysautonomia in Patients With De Novo Parkinson's Disease: Forward Gait Versus Backward Gait

OBJECTIVE

Studies on gait and autonomic dysfunction have been insufficient so far, particularly de novo Parkinson's disease (PD). The aim of this study was to identify the association between gait dynamics and autonomic dysfunction in patients with de novo PD.

METHODS

A total 38 patients with de novo PD were retrospectively included in this study. Details of patients' dysautonomia were assessed using the Scales for Outcomes in Parkinson's Disease-Autonomic Dysfunction (SCOPA-AUT). For assessment of gait, a computerized gait analysis was performed using the GAITRite system for forward gait and backward gait. High SCOPA-AUT score (PD-HSAS) group and low SCOPA-AUT score (PD-LSAS) group were identified according to their SCOPA-AUT scores.

RESULTS

Nineteen (50%) patients with high SCOPA-AUT scores above median value (12.5) were assigned into the PD-HSAS group and others were assigned to the PD-LSAS group. Compared with the PD-LSAS group, the PD-HSAS group exhibited slower gait, shorter stride, decreased cadence, increased double support phase, decreased swing phase, and increased variability in swing time. Total SCOPA-AUT score showed significantly positive correlations with gait variability and instability but a negative correlation with gait hypokinesia. In subdomain analysis, urinary dysautonomia was highly associated with impairment of gait dynamics. All significant results were found to be more remarkable in backward gait than in forward gait.

CONCLUSION

Our findings suggest that alteration in gait dynamics, especially backward gait, is highly associated with autonomic dysfunction in patients with de novo PD.

Silibinin ameliorates depression/anxiety-like behaviors of Parkinson's disease mouse model and is associated with attenuated STING-IRF3-IFN-β pathway activation and neuroinflammation

Depression and anxiety are common neuropsychiatric symptom of Parkinson's disease (PD), reflecting reduced quality of life in patients with PD. Silibinin (silybin), a flavonoid extracted and isolated from the fruit of Silybum marianum (L.) Gaertn, is widely used for the treatment of hepatic diseases. We report here that silibinin shows anti-depressant and anti-anxiety effects on 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced model mice with PD. All the results of open field test, elevated plus maze test, tail suspension test and forced swimming test demonstrated that silibinin administration significantly attenuated MPTP-induced depression/anxiety. Hematoxylin-eosin (HE) staining and Nissl staining results showed that MPTP injection caused the damage of hippocampal neurons, but this was ameliorated by oral administration of silibinin. Silibinin significantly restored hippocampal levels of 5-hydroxyptramine (5-HT) and noradrenaline (NA), two important neurotransmitters for regulating mood, which decreased in MPTP-injected mice. Neuroinflammation, as reflected by the increased expressions of IL-1β, TNFα and IFN-β, was marked in the hippocampus of MPTP-treated mice, accompanying increased stimulator of interferon genes (STING) and interferon regulatory factor-3 (IRF3). Silibinin administration, however, down-regulated the levels of IL-1β, TNFα and IFN-β, as well as STING and IRF3, protecting MPTP-induced PD model mice. These findings indicate that silibinin has a potential of being further developed as a therapeutic for depression and anxiety in PD.