Objective To understand the frailty status and main influencing factors of elderly Parkinson’s disease (PD) patients. Methods The elderly PD patients who attended the Department of Neurology of Changshu Hospital of Traditional Chinese Medicine between November 2023 and March 2024 were selected. The patients’ frailty conditions were investigated using general information questionnaire, Chinese version of Tilburg Frailty Indicator, Hoehn-Yahr Rating Scale, Mini-Nutritional Assessment Short Form, Movement Disorder Society-Unified PD Rating Scale Part Ⅲ, PD Sleep Scale-2, and Mini-Mental State Examination. Multiple linear regression analysis was used to further determine the influencing factors of the frailty status in elderly PD patients. Results A total of 170 PD patients were included. Among them, 117 cases (68.82%) had frailty, while 53 cases (31.18%) had not frailty. The average score for frailty was (6.48±3.34) points, the average score for nutritional status was (11.89±1.65) points, the average score for motor function was (27.40±13.73) points, the average score for sleep quality was (16.05±7.76) points, and the average score for cognitive status is (26.25±4.51) points. The Pearson correlation analysis results showed that PD patient frailty was positively correlated with motor function and sleep quality (P<0.01), and negatively correlated with nutritional status and cognitive status (P<0.01). The results of multiple linear regression analysis showed that age, education, place of residence, course of disease, Hoehn-Yahr Rating, nutritional status, motor function, cognitive status and sleep quality were the influencing factors of frailty in PD patients (P<0.05). Conclusions Elderly PD patients are prone to frailty. Healthcare professionals should pay attention to early screening for frailty in this population and provide timely and effective interventions to prevent or delay the onset of frailty in patients.
The dysfunction of subthalamic nucleus is the main cause of Parkinson’s disease. Local field potentials in human subthalamic nucleus contain rich physiological information. The present study aimed to quantify the oscillatory and dynamic characteristics of local field potentials of subthalamic nucleus, and their modulation by the medication therapy for Parkinson’s disease. The subthalamic nucleus local field potentials were recorded from patients with Parkinson’s disease at the states of on and off medication. The oscillatory features were characterised with the power spectral analysis. Furthermore, the dynamic features were characterised with time-frequency analysis and the coefficient of variation measure of the time-variant power at each frequency. There was a dominant peak at low beta band with medication off. The medication significantly suppressed the low beta component and increased the theta component. The amplitude fluctuation of neural oscillations was measured by the coefficient of variation. The coefficient of variation in 4-7 Hz and 60-66 Hz was increased by medication. These effects proved that medication had significant modulation to subthalamic nucleus neural oscillatory synchronization and dynamic features. The subthalamic nucleus neural activities tend towards stable state under medication. The findings would provide quantitative biomarkers for studying the mechanisms of Parkinson’s disease and clinical treatments of medication or deep brain stimulation.
Evidence has been retrieved through MEDLINE and Cochrane Libray about the treatment for patients with advanced Parkinson’s disease who suffered from on-off, dyskinesia and depression after chronic use of L-dopa. All of the evidence has been evaluated. Methods of evidence-based treatment were drawn up according to the evidence, clinciams’ experiences and patients’ preferences. All symptoms of the patient have been improved obviously.
Objective To evaluate the effectiveness of repetitive transcranial magnetic stimulation (rTMS) for treating dysfunction in patients with Parkinson’s disease (PD). Methods We searched the Cochrane Library (Issue 1, 2010), MEDLINE, EMbase, CBMdisc, and CNKI from the date of the database establishment to April 2010. Randomized controlled trials (RCTs) of rTMS for patients with PD were collected. The quality of the included RCTs was critically appraised and data were extracted by two reviewers independently. Meta-analyses were conducted for the eligible RCTs. Results Eight RCTs were included. The pooled results of the first 2 RCTs showed that, there was no significant difference compared with control group about treating PD patients with clinical motor dysfunction by high-frequency rTMS 10 days later (WMD= –4.75, 95%CI –13.73 to 4.23). The pooled analysis of another 3 studies showed that, no significant difference were found about improving symptoms with treatment of low-frequency rTMS for 1 month compared with control group (WDM= –8.51, 95%CI –18.48 to 1.46). The pooled analysis of last 3 studies showed that, patient with treatment of low-frequency rTMS for 3 months, had been significantly improved in clinical symptoms such as neurological, behavior and emotional state, clinical motor function, and activities of daily living (WDM= –5.79, 95%CI –8.44 to –1.13). The frontal or motor cortex rTMS manifested as low frequency (≤1Hz), high intensity (≥90% RMT), multi-frequency (≥3 times) and long time (≥3 months) had a positive effect on the clinical symptoms of patients with PD and also had a long-term effect. Conclusions rTMS can improve clinical symptoms and dysfunction of the patients with PD.
Objective To systematically review the efficacy and safety of CoenzymeQ10 for Parkinson’s disease. Methods Databases including PubMed, The Cochrane Library (Issue 1, 2015), EMbase, CBM, CNKI, WanFang Data and VIP were searched from inception to August 2015, to collect randomized controlled trials (RCTs) about CoenzymeQ10 for Parkinson’s disease. Two reviewers independently screened literature, extracted data and assessed the risk of bias of included studies. Then meta-analysis was performed using RevMan 5.3 software. Results A total of 5 RCTs involving 981 patients were included. The results of meta-analysis showed that, a) As for recently effectiveness, CoenzymeQ10 2 400 mg group was superior to the placebo group in total UPDRS score change (MD=1.09, 95%CI 0.94 to 1.24, P < 0.000?01), UPDRS-I score change (MD=0.19, 95%CI 0.17 to 0.21, P < 0.000?01), UPDRS-II score change (MD=0.27, 95%CI 0.21 to 0.32, P < 0.000?01), UPDRS-III score change (MD=0.65, 95%CI 0.54 to 0.76, P < 0.000?01), Hoehn & Yahr score change (MD=0.05, 95%CI 0.04 to 0.06, P < 0.000?01), and Schwab England score change (MD= –0.87, 95%CI –1.02 to –0.72, P < 0.000?01). b) As for long-term effectiveness, there were no differences between two groups, except that the UPDRS-II score change of CoenzymeQ10 1 200 mg group was superior to the placebo group. c) As for adverse reactions, there were no statistical differences between two groups except that the incidence of cholesterol of the CoenzymeQ10 600 mg group and incidence of diarrhea of the CoenzymeQ10 2?400 mg group were lower than that of the placebo group. Conclusion Current evidence shows that, the dosage of 2?400 mg/d CoenzymeQ10 is effective and safe for early Parkinson’s disease. Due to the limited quality and quantity of included studies, more higher quality studies are needed to verify the above conclusion.
At present the parkinsonian rigidity assessment depends on subjective judgment of neurologists according to their experience. This study presents a parkinsonian rigidity quantification system based on the electromechanical driving device and mechanical impedance measurement method. The quantification system applies the electromechanical driving device to perform the rigidity clinical assessment tasks (flexion-extension movements) in Parkinson’s disease (PD) patients, which captures their motion and biomechanical information synchronously. Qualified rigidity features were obtained through statistical analysis method such as least-squares parameter estimation. By comparing the judgments from both the parkinsonian rigidity quantification system and neurologists, correlation analysis was performed to find the optimal quantitative feature. Clinical experiments showed that the mechanical impedance has the best correlation (Pearson correlation coefficient r = 0.872, P < 0.001) with the clinical unified Parkinson’s disease rating scale (UPDRS) rigidity score. Results confirmed that this measurement system is capable of quantifying parkinsonian rigidity with advantages of simple operation and effective assessment. In addition, the mechanical impedance can be adopted to help doctors to diagnose and monitor parkinsonian rigidity objectively and accurately.
1-methyl-6,7-dihydroxy-1,2,3,4-tetrahydroisoquinoline (Sal) is a kind of catechol isoquinoline compound, which mainly exists in mammalian brain and performs a variety of biological functions. Through in vivo metabolism, Sal can be transformed into endogenous neurotoxins and can participate the occurrence of Parkinson’s disease (PD). This has attracted widespread concern of researchers. Recently, many research works have shown that Sal may lead to alcohol addiction and regulate hormone release of the neuroendocrine system, which indicated that it is a potential regulator of dopaminergic neurons. In this paper, we discuss the neural functions of Sal on the above aspects, and wish to provide some theoretical supports for further research on its mechanism.
People with Parkinson’s disease (PD) exhibit multi-system damaged. Medication mainly targets impairments related to dopaminergic lesions. Moreover, in later stages of the disease, medication becomes less effective. Rehabilitation therapy is believed that it can improve multiple functional disorders, including myotonia, bradykinesia, and postural gait abnormalities. It not only reduces the severity of non-motor symptoms and improves the quality of life in PD patients, but also delays the development of PD and improves the activity of daily life of patients. This article summarizes the progress of rehabilitation assessment and the therapy of PD.
ObjectiveTo summarize and evaluate the quality of methodology, report and evidence of the systematic reviews and meta-analyses (SRs/MAs) of acupuncture and moxibustion interventions for Parkinson's disease. MethodsEight databases including CNKI, WanFang Data, VIP, CBM, PubMed, EMbase, Cochrane Library and Web of Science were searched from inception to May 1, 2023. The quality of methodology, report and evidence involved in these studies were evaluated by AMSTAR 2, PRISMA and GRADE tool. ResultsA total of 28 SRs/MAs were included, and the findings of included studies showed that acupuncture and moxibustion had a clinical advantage for Parkinson's disease. The methodological quality of all studies was extremely low. Thirteen reports were relatively complete, 14 reports had certain flaws, and 1 report had relatively serious flaws. And of the 126 reports for seven outcomes, 1 was graded as high, 12 as moderate, 57 as low, and 56 as critically low. ConclusionThe current evidence shows that acupuncture and moxibustion have a certain clinical effect for Parkinson's disease, but the methodological quality and evidence quality of related SRs/MAs are low, and the standardization still needs to be improved. The efficacy of acupuncture and moxibustion in Parkinson's disease still needs to be verified by high-quality clinical studies in the future.
Methods for achieving diagnosis of Parkinson’s disease (PD) based on speech data mining have been proven effective in recent years. However, due to factors such as the degree of disease of the data collection subjects and the collection equipment and environment, there are different categories of sample aliasing in the sample space of the acquired data set. Samples in the aliased area are difficult to be identified effectively, which seriously affects the classification accuracy of the algorithm. In order to solve this problem, a partition bagging ensemble learning is proposed in this article, which measures the aliasing degree of the sample by designing the the ratio of sample centroid distance metrics and divides the training set into multiple subsets. And then the method of transfer training of misclassified samples is used to adjust the results of subset partitioning. Finally, the optimized weights of each sub-classifier are used to integrate the test results. The experimental results show that the classification accuracy of the proposed method is significantly improved on two public datasets and the increasement of mean accuracy is up to 25.44%. This method not only effectively improves the classification accuracy of PD speech dataset, but also increases the sample utilization rate, providing a new idea for the diagnosis of PD.