Parkinson's Disease Severity Research Articles

Severity level diagnosis of Parkinson’s disease by ensemble K-nearest neighbor under imbalanced data

The reliable and explainable diagnosis of severity level for Parkinson’s disease (PD) is significant for the therapy. Nonetheless, there are little data for severe PD patients but abundant data for slight PD patients, and this imbalanced distribution reduces the accuracy of diagnosis. Besides, the intrinsic differences for different severity levels are still unclear due to the individual differences and similarity of gait. To figure out the gait differences toward the development of PD severity level, gait features like time and force features as well as their coefficient of variance and asymmetry index have been extracted and compared. To overcome the imbalance influence during the severity level diagnosis, an ensemble K-nearest neighbor (EnKNN) is proposed. The K-nearest neighbor algorithm is applied to construct the base classifiers with extracted features, then the weight of each base classifier is calculated by the G-mean score and the F-measure. Finally, base classifiers are integrated by weight voting. Results show that the proposed EnKNN can achieve an average accuracy of 95.02% (0.44%) for PD severity level diagnosis overwhelming the imbalanced distribution of data. Additionally, some gait features exhibit distinct change with the increase of PD severity level which helps to a reliable and explainable diagnosis.

Relating Global Cognition With Upper-Extremity Motor Skill Retention in Individuals With Mild-to-Moderate Parkinson's Disease.

Background and Purpose: Cognition has been linked to rehabilitation outcomes in stroke populations, but this remains unexplored in individuals with Parkinson's disease (PD). The purpose of this secondary data analysis from a recent clinical trial (NCT02600858) was to determine if global cognition was related to skill performance after motor training in individuals with PD.Methods: Twenty-three participants with idiopathic PD completed 3 days of training on an upper-extremity task. For the purposes of the original clinical trial, participants trained either “on” or “off” their dopamine replacement medication. Baseline, training, and 48-h retention data have been previously published. Global cognition was evaluated using the Montreal Cognitive Assessment (MoCA). Linear regression examined whether MoCA score predicted longer-term retention at nine-day follow-up; baseline motor task performance, age, PD severity, depressive symptoms, and group (medication “on”/“off”) were included as covariates. Baseline and follow-up motor task performance were assessed for all participants while “on” their medication.Results: MoCA score was positively related to follow-up motor task performance, such that individuals with better cognition were faster than those with poorer cognition. Baseline task performance, age, PD severity, depressive symptoms, and medication status were unrelated to follow-up performance.Discussion and Conclusions: Results of this secondary analysis align with previous work that suggest cognitive impairment may interfere with motor learning in PD and support the premise that cognitive training prior to or concurrent with motor training may enhance rehabilitative outcomes for individuals with PD. Findings also suggest that assessing cognition in individuals with PD could provide prognostic information about their responsiveness to motor rehabilitation.

Association of ATG5 gene polymorphism with Parkinson’s disease in a Han Chinese population

PurposeThere is growing evidence that autophagy-related gene 5 (ATG5) is involved in neural development, neuronal differentiation, and neurodegenerative diseases. The purpose of this study was to investigate the association between ATG5 gene single-nucleotide polymorphisms (SNPs) and Parkinson’s disease (PD) in the Han population.MethodsA case–control study was conducted in 120 PD patients and 100 healthy volunteers. MassArray platform was used to analyze polymorphisms in three different regions of ATG5 gene (rs510432, rs573775 and rs17587319). In the included subjects, 50 PD patients and 50 healthy volunteers were selected, and the plasma ATG5 concentration was detected by enzyme-linked immunosorbent assay (ELISA). The allele and genotype frequencies of SNPs were assessed using the SHEsis program.ResultsWe found a significant correlation between rs17587319 and PD, and the subcomponent showed a high correlation between rs17587319 with cognitive impairment and age at onset in PD patients. At the same time, the total plasma ATG5 level of PD patients and the plasma ATG5 expression level of early-onset Parkinson’s disease (EOPD) patients were significantly higher than the control group, while there was no significant difference of ATG5 expression between late-onset Parkinson’s disease (LOPD) patients and the control group.ConclusionThese findings suggest that genetic variations in the ATG5 gene and low levels of the ATG5 protein are associated with susceptibility to PD and with cognitive impairment in PD patients. ATG5 could be a potential biomarker to assess the severity and prognosis of PD.

Diabetes Mellitus and Parkinson's Disease: A Systematic Review and Meta-Analyses.

A link between diabetes mellitus (DM) and Parkinson's disease (PD) have been proposed but evidence are sparse and inconsistent. Perform a systematic review of all evidence that link DM and PD characterising the prevalence of DM in PD patients, the risk of developing PD in DM patients and the influence of DM on PD severity and progression. MEDLINE, Scopus, and Cochrane Library from inception to June 30, 2021 were searched. Studies reporting prevalence, incidence, severity and disease progression of DM and PD were included. Prevalence of DM in PD and incidence of PD in DM patients, and characteristics of PD. A total of 21 studies (n = 11,396) included data on DM prevalence in PD patients, 12 studies (n = 17,797,221) included data on incidence of PD in DM patients, and 10 studies (n = 2,482) included data on DM impact on PD severity and disease progression. The prevalence of DM in PD patients was 10.02 %, (95%C.I. 7.88 -12.16), DM patients showed a higher risk of developing PD (OR: 1.34 95%CI 1.26-1.43 p < 0.0001) compared to non-DM, and PD patients with DM showed a greater severity of motor symptoms, with higher Hoehn and Yahr stage (SMD: 0.36 95%CI 0.12-0.60; p < 0.001) and higher UPDRS (SMD 0.60 95%CI 0.28-0.92; p < 0.001) compared with PD patients without DM. Although the prevalence of DM in PD patients is similar to the general population, patients with DM have a higher risk of developing PD, and the presence of DM is associated with greater PD severity and faster progression, which suggests that DM may be a facilitating factor of neurodegeneration.

Comparison of Mini-Mental State Examination and Montreal Cognitive Assessment Ratings Across Levels of Parkinson's Disease Severity.

Cognitive impairment (CI) is common in Parkinson's disease (PD) and an important cause of disability. Screening facilitates early detection of CI and has implications for management. Preclinical disability is when patients have functional limitations but maintain independence through compensatory measures. The objective of this study was to investigate the relationship between scores on the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) with levels of PD severity and disability. PD patients (n = 2,234) in a large observational study were stratified by disease severity, based on Total Unified Parkinson's Disease Rating Scale (Total UPDRS) and Hoehn and Yahr (HY) stage. Using MMSE (n = 1,184) or MoCA (n = 1,050) and basic (ADL) and instrumental activities of daily living (IADL) scales for disability, linear regression analysis examined associations between cognitive status and disability. Cognition and disability were highly correlated, with the strongest correlation between IADL and MoCA. Only 16.0% of mean MMSE scores were below threshold for CI (28) and only in advanced PD (Total UPDRS 60+, HY≥3). MoCA scores fell below CI threshold (26) in 66.2% of the sample and earlier in disease (Total UPDRS 30+, HY≥2), corresponding with impairments in ADLs. In a large clinical dataset, a small fraction of MMSE scores fell below cutoff for CI, reinforcing that MMSE is an insensitive screening tool in PD. MoCA scores indicated CI earlier in disease and coincided with disability. This study shows that MoCA, but not MMSE is sensitive to the emergence of early cognitive impairment in PD and correlates with the concomitant onset of disability.

Gait based Parkinson’s disease diagnosis and severity rating using multi-class support vector machine

To diagnose Parkinson’s disease (PD) in a clinical setting, generally clinicians utilize several clinical manifestations such as motor impairments and non-motor symptoms and predict the severity level based on unified Parkinson’s disease rating scale (UPDRS). Such a clinical evaluation highly depends on the expertise and experience of the clinicians and results in variation in assessment among clinicians. Hence, to assist the clinicians to diagnose the PD and rate the severity level, we present a gait classification based decision support system using multi-class support vector machine (MCSVM). As the gait alterations are the initial manifestations of PD, we utilize the publicly available vertical ground reaction force (VGRF) dataset and perform the kinematic analysis to extract the spatiotemporal features. To identify the prominent gait biomarkers, this work utilizes a correlation based feature selection approach and employs multi-regression approach to normalize the gait time series data. Moreover, transforming the multi-class classification problem into multiple binary classification problem using one-versus-one (OVO) strategy, the proposed PD severity rating framework tests the performance of four SVM kernel functions for three different walking tests. Experimental results highlight that the quadratic SVM classifier offers an average accuracy of 98.65% and outperforms several other state-of-the-art methods that utilized gait dataset for PD diagnosis.

Effect of bladder dysfunction on development of depression and anxiety in Parkinson's disease.

Parkinson's disease (PD) often presents with movement disorder. However, besides motor complaints, there are many complaints such as anxiety, depression, urinary complaints and constipation. The aim of this study was to investigate whether neurogenic lower urinary dysfunction (NLUD), which is frequently seen in PD, has an effect on the development of anxiety and depression in these patients. The study included 32 males (66.6%) and 16 females (33.3%); in total 48 subjects were registered. For the diagnosis and severity of PD, the UK Parkinson's Disease Society Brain Bank Criteria, Unified Parkinson's Disease Rating Scale (UPDRS) and the Hoehn-Yahr scale were used. Urological evaluation was performed using history, physical examination, laboratory tests and standard forms such as IPSS and OAB-V8. There was no difference between the genders in terms of duration, severity and NLUD (p > 0.05). The incidence of anxiety and depression in PD patients was 62.8% and 72.1%, respectively. The prevalence of NLUD was 67.4% and depression and anxiety was found to increase (1.06 and 1.28 times, respectively) in relation to NLUD. In particular, there was a relationship between storage lower urinary tract symptoms and anxiety and depression development (p < 0.05). As expected, it was found that the incidence of NLUD, anxiety and depression was increased in PD. In addition, NLUD was found to be a risk factor for the development of anxiety and depression. Therefore, it is concluded that NLUD, which can potentially cause important complications, as well as motor complaints, should be closely monitored and treated in PD patients.

Inter-electrode distance influences subthalamic local field potentials recordings in Parkinson's disease

The study of subthalamic (STN) local field potentials (LFPs) led to significant advancement in the understanding of the pathophysiology of Parkinson's disease (PD). PD is associated with pathological spectral power in the β band (11–30 Hz range), and it is also characterized by β phase- high frequency (200-500 Hz) amplitude coupling (PAC). Although both β band spectral power and PAC correlate with PD severity, whether their changes are consistent with different electrodes geometry is still a matter of debate. This study aims to assess the spectral power and PAC of two LFP signals captured from both wide- and close-spaced contact pairs (i.e. 0–3 and 1–2) of the same DBS electrode within the STN, before and after Levodopa administration.

S1913 Antibiotic Combination Therapy Improves Symptoms of Parkinson’s Disease in Individuals With Chronic Constipation

Introduction: Parkinson’s disease (PD) is a neurodegenerative disorder characterized by the loss of dopaminergic neurons with motor symptoms of tremor, rigidity, bradykinesia and postural instability alongside non-motor symptoms such as constipation. Here we explore the effects of a novel antibiotic combination therapy (ACT) comprising Metronidazole, Vancomycin and Rifaximin for the treatment of constipation, which improved symptoms of PD in two cases. Our findings were validated by the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) to rank the burden of disease ranging from normal=0 to most severe=272. Case description/methods: Case 1 A 69 y/o male presented with PD and severe constipation including straining to initiate a bowel movement and inability to defecate for up to 1wk. Before commencing ACT, preliminary MDS-UPDRS was 38 and symptoms included asymmetric tremor, cogwheel rigidity, bradykinesia and shuffling gait despite treatment with Levodopa and Carbidopa. At 1yr review on ACT, constipation had abated with daily bowel motions not requiring Movicol. The MDS-UPDRS fell to 21 indicating a 45% reduction even with an unchanged PD medication regimen. Strikingly, there was a diminished tremor, milder cog-wheeling tone and minimal impairment of gait. After concluding ACT, the patient slowly regressed in line with the natural progression of disease. Case 2 A 62 y/o female presented with PD and a 10yr history of constipation, passing a bowel motion once every 4d with bloating and flatulence. Before ACT with added Colchicine was commenced, baseline MDS-UPDRS was 37 and symptoms included asymmetric tremor, rigidity, postural instability and decreased arm swing despite treatment with Pramipexole and Rasagiline. At 1yr follow-up on ACT, constipation had resolved with complete emptying daily and no bloating or flatulence. The MDS-UPDRS fell to 26 denoting a 30% reduction whilst the dosage of PD medication remained constant. Noticeably, there was a decreased frequency of tremor, absence of rigidity, improved balance and greater arm swing. Upon cessation of ACT, the patient had a sustained response and gained further success with self-initiated thiamine injections. Discussion: ACT successfully treated constipation and improved neurological symptoms of PD in two cases. Our findings suggest that treatments modulating the gut microbiota may play a role in reducing the severity and progression of PD as well as ameliorating non-motor symptoms such as constipation.Table 1.: Two cases with Parkinson’s Disease and Chronic Constipation who were treated with Antibiotic Combination Therapy PD: Parkinson’s Disease, MDS-UPDRS: Movement Disorder Society-Unified Parkinson’s Disease Rating Scale (ranging from normal=0 to most severe=272), w: With, w/o: Without, BNO: Bowels not open, BO: Bowels open, i: One ii: Two, mg: Milligram, qd: Once a day, bd: Twice a day, qid: Four times a day.

Cross-Sectional Study on the Gut Microbiome of Parkinson's Disease Patients in Central China.

Gastrointestinal dysfunction plays an important role in the occurrence and development of Parkinson’s disease (PD). This study investigates the composition of the gut microbiome using shotgun metagenomic sequencing in PD patients in central China. Fecal samples from 39 PD patients (PD group) and the corresponding 39 healthy spouses of the patients (SP) were collected for shotgun metagenomics sequencing. Results showed a significantly altered microbial composition in the PD patients. Bilophila wadsworthia enrichment was found in the gut microbiome of PD patients, which has not been reported in previous studies. The random forest (RF) model, which identifies differences in microbiomes, reliably discriminated patients with PD from controls; the area under the receiver operating characteristic curve was 0.803. Further analysis of the microbiome and clinical symptoms showed that Klebsiella and Parasutterella were positively correlated with the duration and severity of PD, whereas hydrogen-generating Prevotella was negatively correlated with disease severity. The Cluster of Orthologous Groups of protein database, the KEGG Orthology database, and the carbohydrate-active enzymes of gene-category analysis showed that branched-chain amino acid–related proteins were significantly increased, and GH43 was significantly reduced in the PD group. Functional analysis of the metagenome confirmed differences in microbiome metabolism in the PD group related to short-chain fatty acid precursor metabolism.

Plasma acyl-carnitines, bilirubin, tyramine and tetrahydro-21-deoxycortisol in Parkinson's disease and essential tremor. A case control biomarker study

Background and purposeGiven the overlapping clinical manifestations and pathology, the differentiation between essential tremor (ET) and Parkinson's disease (PD) is difficult. Our aims were to examine the plasma metabolomics profiling and their association with motor and non-motor symptoms (NMS) in patients with PD, and to determine differences between de novo PD compared to moderate-advanced PD vs. controls and patients with ET. MethodsPlasma samples were collected from 137 subjects including 35 age matched controls, 29 NOVO-PD, 35 PD and 38 ET patients. PD severity, motor and NMS including cognitive function were assessed using the UPDRS, NMS and PD cognitive rating scales, respectively. Metabolomics analysis was performed by UPLC-ESI-QToF-MS followed by unsupervised multivariate statistics. The area under the curve of the biomarkers according to distribution of their concentrations and the diagnosis of PD (NOVO-PD, advanced PD) vs ET and healthy controls was used as a measurement of diagnostic ability. ResultsSeveral acyl-carnitines, bilirubin, tyramine and tetrahydro-21-deoxycortisol (THS) presented good predictive accuracy (AUC higher than 0.8) for differentiating de novo PD and advanced PD from controls and ET, suggesting an alteration in the lipid oxidation pathway. In multivariate regression analysis, metabolite levels were not significantly associated with motor and NMS severity in PD. ConclusionsDiverse acyl-carnitines, bilirubin, tyramine and some adrenal gland derived metabolites are suggested as potential biomarkers able to distinguish between PD from controls and ET.

Changes in Cortical Excitability and Parkinson Tremor After Botulinum Toxin Therapy.

To investigate the relationship between botulinum toxin type A (BoNT-A) administration, tremor amplitude, and modulation of intracortical excitability and sensorimotor processing using paired-pulse transcranial magnetic stimulation (pp-TMS) in patients with early, tremor-dominant Parkinson disease (PD). Twelve de novo (naive to anti-PD medications) and 7 l-dopa (optimized on levodopa) participants with PD with tremor affecting one arm were recruited. All participants received 4 serial BoNT-A treatments for tremor every 12 weeks and peak effect was assessed 6 weeks posttreatment, totaling 8 visits over 42 weeks. Injection measures were based on kinematic tremor analysis. Short interval intracortical inhibition (SICI), intracortical facilitation (ICF), long interval intracortical inhibition (LICI), and measures of sensorimotor interaction (short-latency afferent [SAI] and long-latency afferent [LAI] stimulation) were assessed in both hemispheres using pp-TMS paradigms at each time point. Linear mixed models analyzed the effect of each pp-TMS measure and tremor severity within each cohort and the association between pp-TMS and tremor severity in the de novo cohort over 42 weeks. t Tests compared pp-TMS measures between hemispheres per time point. Baseline SICI, LICI, and SAI was reduced (higher motor evoked potential [MEP] ratio) on the tremulous/treated side compared to the nontremulous side in de novo participants. On the treated side in the de novo cohort, BoNT-A treatment significantly reduced ICF and increased LICI, SAI, and LAI (lower MEP ratio) at peak BoNT-A time points. The change in tremor severity was significantly associated with changes in SICI, LICI, and LAI. Our findings suggest that tremor severity in early PD may be related to impaired intracortical inhibition and defective sensorimotor integration.

Does MDS-UPDRS Provide Greater Sensitivity to Mild Disease than UPDRS in De Novo Parkinson's Disease?

The Movement Disorder Society revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) was designed to be more sensitive to mild motor severity than the Unified Parkinson's Disease Rating Scale (UPDRS). To test whether MDS-UPDRS Part III items provide increased sensitivity to mild motor severity when compared to the same items of the UPDRS in de novo PD patients. Using a sample of 129 de novo PD patients assessed at one time point simultaneously with both scales, we compared the scale's scores on the 17 items measuring the same motor function. The scaling anchors for the MDS-UPDRS were Slight, Mild, Moderate and Severe, and for the UPDRS were Mild, Moderate, Severe and Marked. Using Classical Test Theory (CTT) we compared the distributions of the scaling anchors from the individual items. Using Item Response Theory (IRT), we examined the sensitivity of the scaling anchors from each scale to the latent-trait measurement of overall parkinsonian motor severity. There was 2193 observations of individual scaling anchors from the 17 items in both scales. The CTT approach revealed frequent floor effects with only the item assessing Gait demonstrating a significance difference in the scaling distribution between the scales (P=0.005). The IRT analyses revealed similar levels of sensitivity to the latent trait of PD motor function. These results do not support increased sensitivity of MDS-UPDRS over the UPDRS for assessing mild motor severity in de novo PD patients, with significant difference in the scaling only for the item assessing gait.

Striatal Subdivisions Estimated via Deep Embedded Clustering With Application to Parkinson's Disease.

Recent fMRI connectivity-based parcellation (CBP) methods have been developed to obtain homogeneous and functionally coherent brain parcels. However, most of these studies utilize traditional clustering methods that neglect hidden nonlinear features. To enhance parcellation performance, here we propose a deep embedded connectivity-based parcellation (DECBP) framework and apply it to determine functional subdivisions of the striatum in public resting state fMRI data sets. This framework integrates fMRI connectivity features into deep embedded clustering (DEC), a deep neural network based on a stacked autoencoder. Compared to three prevalent clustering methods and their combinations with principal component analysis (PCA), the DECBP exhibited a significantly higher similarity between scans, individuals, and groups, indicating enhanced reproducibility. The generated reliable parcellations were also largely consistent with other public atlases. We further explored the functional subunits in the striatum in a data set from 23 Parkinson's disease (PD) subjects and 27 age-matched healthy controls (HC). All putaminal subregions of PD demonstrated lower interhemispheric connectivity than those of HC, which might reflect imbalance in the pathological progression of PD. Such hypo-connectivity was also observed between putaminal subregions and other brain regions, reflecting neuroimaging manifestations of the altered cortico-striato-thalamo-cortical circuit. These observed weaker couplings were associated with PD severity and duration. Our results support the utilization of the DECBP framework and suggest that abnormal connectivity in putaminal subregions may be a potential indicator of PD.

Connectivity of EEG synchronization networks increases for Parkinson\u2019s disease patients with freezing of gait

Freezing of gait (FoG), a paroxysmal gait disturbance commonly experienced by patients with Parkinson’s disease (PD), is characterized by sudden episodes of inability to generate effective forward stepping. Recent studies have shown an increase in beta frequency of local-field potentials in the basal-ganglia during FoG, however, comprehensive research on the synchronization between different brain locations and frequency bands in PD patients is scarce. Here, by developing tools based on network science and non-linear dynamics, we analyze synchronization networks of electroencephalography (EEG) brain waves of three PD patient groups with different FoG severity. We find higher EEG amplitude synchronization (stronger network links) between different brain locations as PD and FoG severity increase. These results are consistent across frequency bands (theta, alpha, beta, gamma) and independent of the specific motor task (walking, still standing, hand tapping) suggesting that an increase in severity of PD and FoG is associated with stronger EEG networks over a broad range of brain frequencies. This observation of a direct relationship of PD/FoG severity with overall EEG synchronization together with our proposed EEG synchronization network approach may be used for evaluating FoG propensity and help to gain further insight into PD and the pathophysiology leading to FoG.

A-131 Treating Parkinson’s Disease with Mindfulness: A Systematic Review

Abstract Objective Mindfulness has been recognized as an evidence-based treatment in a range of psychological and medical (i.e., chronic pain, dementia, diabetes) conditions. Despite several randomized and non-randomized control trials, there continues to be a lack of consensus regarding mindfulness as an effective treatment for individuals with Parkinson’s disease (PD). Methods PsychINFO, Medline, ProQuest, and Embase, were searched using a combination of terms such as “Parkinson’s” and “Mindfulness” or “Meditation.” Studies were included if they reported method, participants, interventions used, and outcomes. Results were extracted and assessed for quality and relevance. Data Synthesis The systematic analysis revealed that mindfulness was primarily effective in reducing non-motor symptoms of PD, except for one survey study of PD patients, which indicated that mindfulness was associated with improved motor symptoms. Otherwise, mindfulness resulted in decreased anxiety and distress while also improving social support. Of the two studies that included caregivers in treatment, mindfulness was associated with reduced caregiver burden. Conclusion The results supported the use of mindfulness as an effective adjunct to PD treatment, with the strongest effects on non-motor symptoms and caregiver distress. Notably, the studies included were limited by small sample sizes and patients with mild to moderate symptoms of PD. Further random controlled trials with larger sample sizes and differing degrees of PD severity are needed to conclusively determine the effects of mindfulness in treating PD.

Parkinson's Disease Rating Scale Using Synchronization Analysis of Gait Dynamics.

Analysis of gait dynamics is a noninvasive and totally painless test, and it can be an ideal method for the diagnosis of neurodegenerative diseases. In this study, based on the strength of synchronization between dynamics of strides, we have suggested a rating scale method for Parkinson's disease (PD). Methods. The sample included 15 persons with PD (age: 66.8 ± 10.9 years) and 16 healthy persons (age: 39.3 ± 18.5 years) which were recruited from the Neurology Outpatient Clinic at Massachusetts General Hospital and were instructed to walk a 77 m long, straight hallway. The time interval of strides and subphases of strides were measured. Using the Hilbert transformation method, we obtained the data phase and used mean absolute error (MAE) to calculate the synchronization strength of the data phase. Results. In order to check the accuracy of our method, we measured the correlation between our numerical results (MAE) and values of the Hoehn-Yahr scale. Spearman's rank correlation coefficients (r) and the P values were calculated. MAE of left and right stride intervals (LRSI) significantly correlates with the Hoehn-Yahr scale for the subjects with PD (with r = 0.60 and P = 0.025 < 0.05). Conclusion. We have revealed that the synchronization weakness of LRSI shows the severity of PD. This method seems to be well suited as a rating scale for people with PD.

The Impact of Non-dopaminergic Medication on Quality of Life in Parkinson's Disease.

Quality of life (QoL) in Parkinson's disease (PD) depends on multiple factors. Due to PD treatment and accompanying, age-related or independent comorbidities, pill burden is often high. The relation of QoL and pharmacotherapy for comorbidities in PD has not been widely studied. This study investigated if and to what extent non-dopaminergic drugs are related to QoL in PD. Second, the impact of demographics and non-motor symptoms were evaluated. A better understanding of the impact of different non-dopaminergic drugs and polypharmacy on QoL will have added value in selecting appropriate (medication) interventions. In a cross-sectional analysis, medication prescription data of 209 PD patients were analyzed and grouped according to the Rx-Risk comorbidity index. QoL was measured using the PDQ-39 questionnaire. Non-motor symptoms were analyzed with the Non-Motor Symptoms questionnaire. Independent factors associated with a reduced QoL were identified with a multivariate linear regression analysis. Non-dopaminergic drugs, subdivided into Rx-Risk comorbidity categories, were not associated with reduced QoL, except for the use of anti-epileptic drugs. However, using more daily non-dopaminergic drugs was also negatively associated with QoL, as well as female sex, increased PD severity, and more non-motor symptoms. Contraindicated non-dopaminergic medication was barely prescribed (0.4%). Non-dopaminergic drugs are frequently prescribed, and higher numbers are associated with impaired QoL in PD. However, when divided in drug types, only anti-epileptic drugs were negatively associated with QoL. In these patients, physicians might improve QoL by further optimizing the condition it was prescribed for (e.g., pain or anxiety), or managing of side effects. Netherlands Trial Register; NL4360.

Does antiretroviral therapy alter the course of Parkinson's disease in people living with HIV?

South Africa has the world's largest antiretroviral programme which has resulted in an increase in life expectancy in persons living with HIV. Parkinson's disease (PD) is an age-related neurodegenerative disorder. No data has been published in this setting with regards to the interaction between PD and people infected with HIV. This was a retrospective study which matched two HIV non-infected PD patients to one HIV-infected patient with PD. Patients with secondary causes of Parkinsonism were excluded. Demographic, clinical and laboratory data were extracted from the charts. Hoehn and Yahr scale was used to assess PD severity. Twenty PD patients were recruited from 1 January 2008 to 31 October 2020 and were diagnosed with HIV for a median of 72 months. The median age at onset of PD was 52 years. All patients were on antiretroviral therapy. There were no statistically significant differences in the levodopa equivalent daily dose, clinical phenotype, impulse control disorders (ICDs) and frequency of a positive family history between the two groups. HIV-infected patients had a higher frequency of dopamine dysregulation syndrome. At the end of follow-up, 3 (15%) PLH-PD had moderate to severe PD compared to 16 (40%) of PD controls. The OR of having moderate to severe PD in HIV non-infected PD patients was 4. Persons living with HIV and Parkinson's disease present with PD symptoms at a younger age, progress slower to a severe stage and respond well to dopaminergic replacement therapy.

Implementation of a Deep Learning Algorithm Based on Vertical Ground Reaction Force Time-Frequency Features for the Detection and Severity Classification of Parkinson's Disease.

Conventional approaches to diagnosing Parkinson’s disease (PD) and rating its severity level are based on medical specialists’ clinical assessment of symptoms, which are subjective and can be inaccurate. These techniques are not very reliable, particularly in the early stages of the disease. A novel detection and severity classification algorithm using deep learning approaches was developed in this research to classify the PD severity level based on vertical ground reaction force (vGRF) signals. Different variations in force patterns generated by the irregularity in vGRF signals due to the gait abnormalities of PD patients can indicate their severity. The main purpose of this research is to aid physicians in detecting early stages of PD, planning efficient treatment, and monitoring disease progression. The detection algorithm comprises preprocessing, feature transformation, and classification processes. In preprocessing, the vGRF signal is divided into 10, 15, and 30 s successive time windows. In the feature transformation process, the time domain vGRF signal in windows with varying time lengths is modified into a time–frequency spectrogram using a continuous wavelet transform (CWT). Then, principal component analysis (PCA) is used for feature enhancement. Finally, different types of convolutional neural networks (CNNs) are employed as deep learning classifiers for classification. The algorithm performance was evaluated using k-fold cross-validation (kfoldCV). The best average accuracy of the proposed detection algorithm in classifying the PD severity stage classification was 96.52% using ResNet-50 with vGRF data from the PhysioNet database. The proposed detection algorithm can effectively differentiate gait patterns based on time–frequency spectrograms of vGRF signals associated with different PD severity levels.