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.
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.
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.
For speech detection in Parkinson’s patients, we proposed a method based on time-frequency domain gradient statistics to analyze speech disorders of Parkinson’s patients. In this method, speech signal was first converted to time-frequency domain (time-frequency representation). In the process, the speech signal was divided into frames. Through calculation, each frame was Fourier transformed to obtain the energy spectrum, which was mapped to the image space for visualization. Secondly, deviations values of each energy data on time axis and frequency axis was counted. According to deviations values, the gradient statistical features were used to show the abrupt changes of energy value in different time-domains and frequency-domains. Finally, KNN classifier was applied to classify the extracted gradient statistical features. In this paper, experiments on different speech datasets of Parkinson’s patients showed that the gradient statistical features extracted in this paper had stronger clustering in classification. Compared with the classification results based on traditional features and deep learning features, the gradient statistical features extracted in this paper were better in classification accuracy, specificity and sensitivity. The experimental results show that the gradient statistical features proposed in this paper are feasible in speech classification diagnosis of Parkinson’s patients.
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.
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.
Objective To review the progress of perioperative treatments for patients of Parkinson’s disease and hip fractures. Methods The related literature of treatments for patients of Parkinson’s disease and hip fractures were reviewed and analyzed from the aspects such as the perioperative management, selection of operation ways, and prognosis. Results The patients of Parkinson’s disease are more likely to sustain hip fractures because of postural instability and osteoporosis. The perioperative treatments for patients of Parkinson’s disease and hip fractures should be determined by orthopedists, neurologist, anesthesiologist, and physical therapist. There is still controversy about the selection of operation and surgical approach. And the prognosis of patients of Parkinson’s disease and hip fractures are associated with the severity of Parkinson’s disease. Conclusion There are few clinical studies about the patients of Parkinson’s disease and hip fractures. The mid-term and long-term functional outcomes of patients of Parkinson’s disease and hip fractures are unsufficient. And the best treatments of patients of Parkinson’s disease and hip fractures need to be further explored.
ObjectiveThis study aims to analyze the trends in Parkinson’s disease incidence rates among the elderly population in China from 1990 to 2021 and to forecast incidence growth over the next 20 years, providing. MethodsJoinpoint regression and age-period-cohort models were employed to analyze temporal trends in Parkinson’s disease incidence, and the Nordpred model was used to predict case numbers and incidence rates among the elderly in China from 2022 to 2044. ResultsFindings indicated a significant increase in Parkinson’s disease incidence among China’s elderly population from 1990 to 2021, with crude and age-standardized incidence rates rising from 95.37 per 100 000 and 111.05 per 100 000 to 170.52 per 100 000 and 183.91 per 100 000, respectively. Predictions suggested that by 2044, the number of cases will rise to approximately 878 264, with the age-standardized incidence rate reaching 223.4 per 100 000, and men showing significantly higher incidence rates than women. The rapid increase in both cases and incidence rates indicated that Parkinson’s disease will continue to impose a heavy disease burden on China’s elderly population. ConclusionThe burden of Parkinson’s disease in China’s elderly population has grown significantly and is expected to worsen. To address the rising incidence rates effectively, it is recommended to enhance early screening and health education for high-risk groups, improve diagnostic and treatment protocols, and prioritize resource allocation to Parkinson’s disease prevention and care services to reduce future public health burdens.
Parkinson’s disease is a common chronic progressive neurodegenerative disease, and its main pathological change is the degeneration and loss of dopaminergic neurons in substantia nigra striatum. Vitamin D receptors are widely distributed in neurons and glial cells, and the normal function of substantia nigra striatum system depends on the level of vitamin D and the normal expression of vitamin D receptors. In recent years, from basic to clinical research, there are some differences in the conclusion of the correlation of vitamin D and its receptor gene polymorphism with Parkinson’s disease. This paper aims to review the research on the correlation of vitamin D and vitamin D receptor gene polymorphism with Parkinson’s disease, and discuss the future research direction in this field.
At present, the incidence of Parkinson’s disease (PD) is gradually increasing. This seriously affects the quality of life of patients, and the burden of diagnosis and treatment is increasing. However, the disease is difficult to intervene in early stage as early monitoring means are limited. Aiming to find an effective biomarker of PD, this work extracted correlation between each pair of electroencephalogram (EEG) channels for each frequency band using weighted symbolic mutual information and k-means clustering. The results showed that State1 of Beta frequency band (P = 0.034) and State5 of Gamma frequency band (P = 0.010) could be used to differentiate health controls and off-medication Parkinson’s disease patients. These findings indicated that there were significant differences in the resting channel-wise correlation states between PD patients and healthy subjects. However, no significant differences were found between PD-on and PD-off patients, and between PD-on patients and healthy controls. This may provide a clinical diagnosis reference for Parkinson’s disease.