Parkinson's Disease最新文献

Background: There are many pharmacological treatment options beyond levodopa for Parkinson's disease (PD), with a variety of drug classes and formulations available. To achieve patient-centered care, clinicians must consider patients' backgrounds and preferences when selecting medications. Objectives: To investigate medication preferences regarding efficacy, safety, dosage/formulation, and cost in Japanese PD patients. Methods: Adults (18-90 years) from the Japan Parkinson's Disease Association receiving PD medication were eligible. An online survey was conducted, involving a discrete choice experiment, which set five medication characteristics including improvement of bothersome symptoms, risk of dyskinesia, risk of side effects other than dyskinesia, dosage/formulation, and monthly out-of-pocket cost. A questionnaire about the value of efficacy and safety of PD medications was also included. Results: In the full analysis set (N = 207), the mean age was 65.2 years, 53.1% were female, and 62.8% had wearing-off. The most impotrant characteristics of PD medications for patients were the risk of dyskinesia, improvement of bothersome symptoms, and risk of side effects other than dyskinesia. Latent class analysis identified three groups with different preferences who have varied backgrounds, such as disease severity. The three most important symptoms patients wanted to improve were moving difficulty/slow movement (79.7%), body stiffness (43.5%), and pain (42.0%). The three most important side effects patients wanted to avoid were dyskinesia (54.6%), hallucinations/visual hallucinations (19.3%), and constipation (11.6%). Conclusion: PD patients placed the highest importance on the risk of dyskinesia for PD medications and also efficacy. To achieve patient-centered care, clinicians should consider patients' backgrounds and preferences when selecting medications.

Background: It is unclear whether the two device-aided therapies (DATs: deep brain stimulation [DBS] and levodopa-carbidopa intestinal gel [LCIG]) affect personality in patients with Parkinson's disease (PD). Objective: This retrospective study aims to explore if patients with PD and their close relatives experience any changes in the patient's personality following the start of DAT. Methods: In total, 32 patients with DAT (17 DBS and 15 levodopa pump-based therapy) and their close relatives (n = 32) were asked to retrospectively assess potential personality changes in the patients using the Big Five Inventory (BFI) following DAT. They also answered questions regarding perceived quality of life and perceived impact on motor symptoms. Results: There was a diverse perceived change in the patients' five personality traits when divided into the type of therapy. DBS patients reported decreased extraversion (70.6%, n = 12), while their close relatives reported an increase in the trait neuroticism (82.4%, n = 14). A significant difference was found in perceived changes in agreeableness, with 8 DBS patients reporting an increase and 4 close relatives reporting a decrease (p=0.008). Most of the pump patients (LCIG) reported a decreased conscientiousness (66.7% n = 10), a perception confirmed by 73.3% (n = 11) of their close relatives, who in addition reported an increase in neuroticism (73.3%, n = 11). Conclusions: This study suggests perceived personality changes following DAT (DBS or LCIG), which vary by therapy and respondent role. Larger studies are needed, but the findings signal the importance of considering both patients' and their relatives' perspectives when assessing personality changes.

Background: Patients affected by idiopathic Parkinson's disease (IPD) are known to have difficulties in sensorial integration. The ratio of the postural sway in the standing position with closed eyes to open eyes (Romberg Quotient) is a simple way to investigate the role of the visual channel in postural control in this category of patients. Objective: We aim to share our observation about the incidence in patients with IPD of postural blindness, namely the reduction of the postural sway by closing the eyes. Methods: Patients had to stay quiet on a force plate for 30 s in four conditions: eyes open and closed both on a firm and a compliant surface. Results: 30% of the 22 patients analyzed reduced their postural sway by closing their eyes on both firm and compliant surfaces. Conclusion: The role of vision for postural control in patients with IPD should be further investigated.

Objective: Subthalamotomy using magnetic resonance-guided high-intensity focused ultrasound (MRg-FUS) is a noninvasive therapy that improves the cardinal symptoms of Parkinson's disease. However, clinical outcomes show high variability even when all inclusion criteria for this treatment are met. In this work, we aim to study the relationship between brain volumetry and clinical response in patients undergoing this treatment. Methods: Twenty patients who underwent MRg-FUS subthalamotomy were included and evaluated at baseline and 3 months post-treatment. Brain volumes were obtained from pretreatment MRI scans processed with the open-source package FreeSurfer. The treatment response was assessed using the movement disorder society unified Parkinson's disease rating scale (MDS-UPDRS). Principal component analysis (PCA) and clustering methods were used to identify groups of patients with similar clinical outcome. Results: PCA identified 2 clusters of patients, and a sensitivity and a specificity of 80% classified patients who will have a response to treatment with an improvement greater than 40% of the pretreatment UPDRS III scale. A positive association was found with the response to treatment with the variables: brain volume, cortical thickness and volume of total gray matter, and subcortical gray matter and white matter. On the other hand, a negative association was found with the response to treatment with the variables: ventricular volume. Conclusion: Our findings suggest that brain atrophy, reduced global cortical thickness, and increased ventricular volume are significantly associated with the predicting treatment response in Parkinson's disease patients undergoing MRg-FUS subthalamotomy.

Background: People with Parkinson's disease (PD) may use cannabis-based products for symptom management. In France, products containing tetrahydrocannabinol (THC) are prohibited, while cannabidiol (CBD)-products are readily available. However, data on cannabinoid use in French people with PD are lacking. Objectives: To identify correlates of the use of cannabis-based products and to document their patterns of use and perceived effects. Methods: A French nationwide online survey was conducted from May to July 2023. Regression analyses helped identify factors associated with current cannabis and CBD use (regardless of their form). Patterns of use and self-reported effects were also documented. Results: The study sample comprised 1136 participants, with a median age of 68 years. Six percent (5.9%) and 17.9% reported using cannabis and CBD, respectively. Both substances were associated with better knowledge of cannabinoids and a poor self-perceived household economic situation. The most common routes of cannabis administration were oral ingestion (44.8%) and smoking (41.4%); for CBD, they were oral ingestion (82.8%) and smoking (6.4%). Users reported that cannabis and CBD were very effective for sleep disorders, pain, and rigidity/cramps. The satisfaction level for both substances was also high. Conclusion: Cannabis and CBD use among people with PD was associated with better knowledge about cannabinoids and a poor self-perceived household economic situation. Furthermore, users reported high levels of satisfaction for both substances. An enhanced communication with healthcare providers and facilitated access to safe cannabis/CBD products are needed in France to enable people with PD to maximize the benefits of cannabinoids when clinically appropriate.

To evaluate the diagnostic accuracy of machine learning-assisted magnetic resonance imaging (MRI) in detecting cognitive impairment among Parkinson's disease (PD) patients through a systematic review and meta-analysis. We systematically searched for studies that applied machine learning algorithms to MRI data for diagnosing PD with mild cognitive impairment (PD-MCI). Data were extracted and synthesized to calculate pooled sensitivity, specificity, positive likelihood ratio (PLR) and negative diagnostic likelihood ratio (NLR), and diagnostic odds ratios (DOR). A bivariate random-effects model and summary receiver operating characteristic (SROC) curves were employed for statistical analysis. The quality of studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) instrument. The publication bias was investigated through Deeks' funnel plot. All statistical analyses were conducted using Stata 14.0. The pooled sensitivity and specificity for diagnosing PD-MCI using machine learning-assisted MRI were 0.82 (95% CI: 0.75-0.87) and 0.81 (95% CI: 0.73-0.87), respectively. The PLR was 4.28 (95% CI: 2.93-6.27), and the NLR was 0.23 (95% CI: 0.16-0.32), indicating a high diagnostic accuracy. The area under the curve (AUC) for the SROC was 0.85 (95% CI: 0.82-0.88). Quality assessment using the QUADAS-2 tool showed a predominantly low risk of bias among the studies, and the Deeks' funnel plot suggested no significant publication bias (p=0.30). In summary, the MRI combined with machine learning for diagnosing PD-MCI achieved high accuracy with the pooled sensitivity of 82% and specificity of 81%.

Objectives: Levodopa remains the most effective treatment for Parkinson's disease (PD); however, tremor reactions to dopaminergic medications show significant variance among patients with PD. This study aimed to assess the different methodologies employed to determine the dopamine responsiveness of tremors and their association with the clinical characteristics of PD. Methods: Patients with PD and tremors were evaluated using the acute levodopa challenge test (LCT). Tremor levodopa responsiveness (LR) was calculated using the Unified Parkinson's Disease Rating Scale Part III (UPDRS-III) scores during OFF and ON periods. Tremor LR was calculated in two formats: absolute difference in tremor scores (OFF-ON), termed aLR, and percentage change in tremor scores, termed %LR and calculated as ([OFF-ON]/OFF100%). Independent variables were compared between the better tremor response to levodopa and poorer tremor response to levodopa groups based on the tremor change rate median score. Additionally, the effect of the tremor LR calculation method was correlated with clinical measures. Results: This study enrolled 188 patients with PD who displayed tremors, of whom 98 (52%) showed better tremor response to levodopa. We identified a moderately negative correlation between tremor aLR and the rigidity-to-tremor score ratio (r = 0.40) during the OFF period, in addition to positive correlations between tremor aLR and the tremor score (r = 0.75), rest tremor score (r = 0.75), motor score (r = 0.42), postural and kinetic tremor score (r = 0.30), and tremor score-to-disease duration ratio (r = 0.30) of the UPDRS-III during OFF periods. The tremor %LR showed no significant relationship with any of the tested variables. Conclusions: The aLR, rather than the %LR, is a more effective assessment method for evaluating the efficacy of levodopa for treating tremors in PD.

Parkinson's disease (PD) is the second most common neurodegenerative disorder worldwide, and the mainstay of treatment is dopamine replacement therapy; however, its beneficial effects tend to wane over time as the disease progresses. Many patients seek complementary therapies to alleviate motor and nonmotor symptoms associated with PD, and the efficacy of acupuncture as a commonly used complementary and alternative therapy for PD remains controversial. In this review, we systematically examine randomized controlled trials and mechanistic studies on acupuncture for PD over the past 12 years. The findings indicate that acupuncture improves both motor and nonmotor symptoms. We also found that the mechanisms underlying the effects of acupuncture on PD may involve connectomics, modulation of dopamine and glutamate systems, regulation of the gut-brain axis, organelle homeostasis, and molecular and signaling pathway modulation. This review proposes a multitarget neuroprotection hypothesis to provide a theoretical basis for standardized acupuncture research.

Background: Parkinson's disease (PD) is the second most common neurodegenerative disease worldwide. Inflammation, marked by the infiltration of inflammatory mediators and the proliferation of inflammatory cells, is closely linked to PD. This study aims to identify and validate inflammation-related biomarkers in PD and construct a TF-mRNA-miRNA coexpression network through bioinformatics analysis. Methods: The PD-associated dataset GSE7621 and inflammation-related genes were downloaded from the GEO Database and GeneCards platform to obtain inflammation-related differential expression genes (IRDEGs). The key IRDEGs were generated by PPI network analysis. The gene expression levels of the key IRDEGs were validated by blood samples from PD patients using QPCR analysis. We utilized the ENCODE, hTFtarget, CHEA, miRWALK, and miRDB databases to obtain upstream and downstream molecular network models for constructing the TF-mRNA-miRNA interaction network of the key IRDEGs. Finally, based on CIBERSORT algorithm, the associations between IRDEs and immune cell infiltration were investigated. Results: A total of four key IRDEGs (CXCR4, LEP, SLC18A2, and TAC1) were screened and validated. Through biological function analysis, key-related pathways and coexpression networks of PD were identified. These genes may be closely related to the onset of PD. Additionally, we found that increased CD4 T-cell infiltration might be associated with the occurrence of PD. Conclusions: We identified four potential inflammation-related treatment target and constructed a TF-mRNA-miRNA regulatory network. This information provides an initial basis for understanding the complex PD regulatory mechanisms.

Background: This study explores the burden of Parkinson's disease (PD) in Kazakhstan, the largest country in Central Asia, a region where data on neurological disorders are notably sparse. Methods: Utilizing data from Kazakhstan's Unified National Electronic Health System during 2014-2021, the study investigates the epidemiology, disability-adjusted life years (DALYs), and survival outcomes in a cohort of PD patients. The authors employed Cox proportional hazards regression models and Kaplan-Meier analysis, alongside sensitivity analyses, to assess the impact of demographic factors, hypertension, and the Charlson Comorbidity Index (CCI) on survival. Results: The study cohort included 10,125 patients, revealing a tenfold increase in PD prevalence during the study period. Mortality rates varied significantly, with the highest rates observed in the eldest age group (137.05 per 1000 person-years). PD contributed to a loss of 156.12 DALYs per 100,000 population, primarily driven by years of life lost. The analysis identified an increased risk of all-cause mortality among males (adjusted hazard ratio (aHR) 1.6; 1.5-1.8), older individuals (aHR 1.05; 1.04-1.06), those with higher CCIs, and individuals of Kazakh ethnicity. Interestingly, patients with comorbid hypertension had a higher probability of survival (aHR 0.67; 0.60-0.73). Conclusion: This study is the first of its kind in Central Asia to examine the burden of PD using a large-scale outpatient registry. The findings underscore the need for targeted interventions to address the growing burden of PD, particularly among males and ethnic Kazakhs. Additionally, further research is needed to explore the inverse association between hypertension and survival in the PD cohort.