Characterizing Parkinson´s disease from gait dynamics using chaos descriptors

Olfactory proteotyping: towards the enlightenment of the neurodegeneration

No neuroprotective treatment has been able to successfully halt the progression of Parkinson disease or prevent development of associated complications. Recombinant erythropoetin (EPO), an erythropoiesis-stimulating agent originally indicated in anemia, produced and manufactured in Cuba (iorEPOCIM, CIMAB S.A, Havana, Cuba) has neuroprotective properties. NeuroEPO is a new nasal formulation of recombinant EPO with a low content of sialic acid and without hematopoietic effects. It has neuroprotective effects in animal models. Evaluate short-term tolerance of intranasal NeuroEPO in patients with Parkinson disease. As part of a monocentric randomized placebo-controlled double-blind study (registered at www.clinicaltrials.gov number NCT04110678), 26 patients with Parkinson disease (stages 1 and 2 on Hoehn & Yahr Scale), were randomly divided into two groups: NeuroEPO (n = 15) and placebo (n = 11), both treated intranasally either with the drug (1 mL, at a concentration of 1 mg/mL of NeuroEPO) or placebo once a week for 5 weeks. At each application, we recorded any adverse events and blood pressure. To assess potential hematopoietic effects of the drug, hematological and biochemical variables were evaluated one week before and one week after the intervention. There were no significant differences (p = 0.22) between the two groups in terms of frequency of adverse events (20.0% in NeuroEPO and 9.1% in placebo groups). Three patients in NeuroEPO presented nausea, and one vomited (possibly due to the patient's positioning during drug application). One patient in placebo group reported polyuria and nasal irritation. In both groups, the adverse events were mild, brief, required no treatment and did not present sequelae. Nasally administered NeuroEPO for five weeks in patients with Parkinson disease stages 1 and 2 on Hoehn & Yahr Scale is well tolerated.

Purpose. Physiotherapists frequently prescribe home exercise programmes for individuals with Parkinson's disease (PD) and Huntington's disease (HD); however, little is known about clients' perceptions of such programmes and any barriers that may affect participation and compliance.Method. A qualitative design was used to capture the attitudes and experiences of people with early-mid stage HD and PD, and with physiotherapists who have experience in neurodegenerative diseases. Two focus groups were conducted for physiotherapists (n = 8); individual interviews were conducted for clients with HD and PD (n = 10). Conversations were digitally recorded and transcribed, and transcriptions were analysed using grounded theory and validated through researcher triangulation. Concepts were categorised according to emerging themes and findings were verified by participants.Results. Both groups cited several barriers to engagement in exercise programmes, which included disease-specific impairments, individual safety and the location at which exercising takes place. Therapists felt that a client's cognition could affect their ability to participate in an exercise programme. Therapists and clients offered a number of strategies to overcome barriers to exercise.Conclusions. Therapists should work in collaboration with clients to evaluate their individual considerations, identify barriers to exercise and design a client-specific programme that is acceptable and feasible for the client.

As digital health technology becomes more pervasive, machine learning (ML) provides a robust way to analyze and interpret the myriad of collected features. The purpose of this preliminary work was to use ML classification to assess the benefits and relevance of neurocognitive features both tablet-based assessments and self-reported metrics, as they relate to Parkinson’s Disease (PD) and its stages [Hoehn and Yahr (H&Y) Stages 1–5]. Further, this work aims to compare perceived versus sensor-based neurocognitive abilities. In this study, 75 participants (n = 50 PD; n = 25 control) completed 14 tablet-based neurocognitive functional tests (e.g., motor, memory, speech, executive, and multifunction), functional movement assessments (e.g., Berg Balance Scale), and standardized health questionnaires (e.g., PDQ-39). Decision tree classification of sensor-based features allowed for the discrimination of PD from healthy controls with an accuracy of 92.6%, and early and advanced stages of PD with an accuracy of 73.7%; compared to the current gold standard tools [e.g., standardized health questionnaires (78.3% accuracy) and functional movement assessments (70% accuracy)]. Significant features were also identified using decision tree classification. Device magnitude of acceleration was significant in 12 of 14 tests (85.7%), regardless of test type. For classification between diagnosed and control populations, 17 motor (e.g., device magnitude of acceleration), 9 accuracy (e.g., number of correct/incorrect interactions), and 8 timing features (e.g., time to between interactions) were significant. For classification between early (H&Y Stages 1 and 2) and advanced (H&Y Stages 3, 4, and 5) stages of PD, 7 motor, 12 accuracy, and 14 timing features were significant. Finally, this work depicts that perceived functionality of individuals with PD differed from sensor-based functionalities. In early-stage PD was shown to be 21.6% lower than sensor-based scores with notable perceived deficits in memory and executive function. However, individuals in advanced stages had elevated perceptions (1.57x) for executive and behavioral functions compared to early-stage populations. Machine learning in digital health systems allows for a more comprehensive understanding of neurodegenerative diseases and their stages and may also depict new features that influence the ways digital health technology should be configured.

Correlation dimension (CD) and the largest Lyapunov exponent (LLE), which are two most important nonlinear invariant measures of nonlinear system, are adopted to characterize the complexity and stability of human brain during all sleep stages. In order to find an optimal embedding to reconstruct phase space, the C-C method and Cao's algorithm were thoroughly analyzed and implemented in efficient ways. Additionally, the G-P algorithm and Kantz's algorithm are also implemented for calculation of CD and LLE respectively. Eight normal sleep EEG records are acquired from MIT-BIH sleep- EDF database for this study. The values of CD and LLE for 30s epochs are calculated, and their mean and standard deviation values are evaluated as well. The results indicate that CD and LLE decrease from the waking stage to stages I, II and III-IV, and they have large values during rapid eye movement (REM) sleep stage. Then, a qualitative conclusion may be drawn that during waking stage and REM sleep stage, brain activity has higher complexity and lower stability than during other stages.

Recently, we demonstrated that staging Parkinson's disease (PD) with a novel simple classification called MNCD, based on four axes (motor, non-motor, cognition, and dependency) and five stages, correlated with disease severity and patients' quality of life. Here, we analyzed the correlation of MNCD staging with PD caregiver's status. Data from the baseline visit of PD patients and their principal caregiver recruited from 35 centers in Spain from the COPPADIS cohort from January 2016 to November 2017 were used to apply the MNCD total score (from 0 to 12) and MNCD stages (from 1 to 5) in this cross-sectional analysis. Caregivers completed the Zarit Caregiver Burden Inventory (ZCBI), Caregiver Strain Index (CSI), Beck Depression Inventory-II (BDI-II), PQ-10, and EUROHIS-QOL 8-item index (EUROHIS-QOL8). Two hundred and twenty-four PD patients (63±9.6 years old; 61.2% males) and their caregivers (58.5±12.1 years old; 67.9% females) were included. The frequency of MNCD stages was 1, 7.6%; 2, 58.9%; 3, 31.3%; and 4-5, 2.2%. A more advanced MNCD stage was associated with a higher score on the ZCBI (p<.0001) and CSI (p<.0001), and a lower score on the PQ-10 (p=.001), but no significant differences were observed in the BDI-II (p=.310) and EUROHIS-QOL8 (p=.133). Moderate correlations were observed between the MNCD total score and the ZCBI (r=.496; p<.0001), CSI (r=.433; p<.0001), and BDI-II (r=.306; p<.0001) in caregivers. Staging PD according to the MNCD classification is correlated with caregivers' strain and burden.

Feasibility, appropriateness, meaningfulness and effectiveness of nursing interventions on the well-being of people with Parkinsonʼs disease and their caregivers living in the community: a mixed-methods systematic review protocol

The article discusses ambulation disorders in Parkinson's disease, which result from both disease progression and aging. It focuses on multisensory impairments and the critical link between cognitive and motor disorders, particularly the motor-cognitive deficit. Diagnosing ambulation disorders presents several challenges because it's essential to identify the specific cause in each case. Key factors include the ineffectiveness of standard antiparkinsonian therapy, varying degrees of cognitive impairments (including visual and spatial difficulties), and the presence of comorbidities. The potential role of changes in gait patterns and motor activity as a marker for the progression of cognitive deficits is discussed. The use of modern techniques in complex diagnostics and therapy for assessing and treating higher-level ambulation disorders in Parkinson's disease is discussed. The author's data underscore the importance of combining both drug and non-drug methods in the treatment of advanced ambulation disorders in Parkinson's disease. This includes the use of transcranial magnetic stimulation, interactive ergometric exercises, and anticholinesterase agents.

Introduction: Olfactory dysfunction is an early warning and most common symptom of Parkinson's disease (PD). It is a promising marker mainly at the early stage of the disease for PD. The purpose of the survey was to evaluate the deficits in odor detection in Elderly with PD. We hypothesized that trigeminal sensitivity dysfunction would be less important than olfactory sensitivity impairment in elderly with PD and could improve diagnostic accuracy. Experimental procedure: Olfactory detection thresholds to Phenyl ethyl alcohol (PEA) [activating only the olfactory system] and n- Butanol (BUT) [activating both olfactory and trigeminal systems], were determined in twenty four patients with PD aged over 65 years old [mean age: 75 +/-4.5 years, range: 70-86 years] and in twenty-four healthy controls who were matched for age and gender [mean age: 73 +/-7.1 years, range: 65- 84 years]. The study also included neuropsychological evaluations and stage of PD estimations. Results: Results show a trend towards an impaired olfactory (CN I) detection sensitivity in relation to PEA thresholds in patients with PD compared to controls independently of age and stage of PD, although no significant difference was observed. Furthermore, no significant difference was observed for BUT thresholds between PD’s patients and controls. PEA and BUT thresholds were significantly correlated in both patients with PD and controls. Conclusion: These findings suggest that the olfactory senescence and decreased detection threshold in elderly (both patients with PD and controls) may influence our results by reducing detection olfactory threshold differential between the two groups, contrary to previous findings in young adults with PD and controls. Trigeminal sensitivity seems to be preserved in Elderly with PD. Future investigations should focus on odorants with higher properties to highlight a potential difference between the two groups.

Gait impairment leads to reduced social activities and low quality of life in people with Parkinson's disease (PD). PD is associated with unique gait signs and distributions of gait features. The assessment of gait characteristics is crucial in the diagnosis and treatment of PD. At present, the number and distribution of gait features associated with different PD stages are not clear. Here, we used whole-body multinode wearable devices combined with machine learning to build a classification model of early PD (EPD) and mild PD (MPD). Our model exhibited significantly improved accuracy for the EPD and MPD groups compared with the healthy control (HC) group (EPD vs. HC accuracy=0.88, kappa=0.75, AUC=0.88; MPD vs. HC accuracy=0.94, kappa=0.84, AUC =0.90). Furthermore, the distribution of gait features was distinguishable among the HC, EPD and MPD groups (EPD based on variability features (40%); MPD based on amplitude features (30%)). Here, we showed promising gait models for PD classification and provided reliable gait features for distinguishing different PD stages. Further multicentre clinical studies are needed to generalize the findings.

To identify the characteristics of cervical deformities in Parkinson's disease (PD) and the role of severity of PD in the development of cervical spine deformities, the authors investigated the prevalence of the cervical deformities, cervical kyphosis (CK), and cervical positive sagittal malalignment (CPSM) in patients with PD. They also analyzed the association of severity of cervical deformities with the stage of PD in the context of global sagittal spinopelvic alignment. This study was a prospective assessment of consecutively treated patients (n = 89) with PD. A control group of the age- and sex-matched patients was selected from patients with degenerative cervical spine disease but without PD. Clinical and demographic parameters including age, sex, duration of PD, and Hoehn and Yahr (H&Y) stage were collected. Full-length standing radiographs were used to assess spinopelvic parameters. CK was defined as a C2-7 Cobb angle < 0°. CPSM was defined as C2-7 sagittal vertical axis (SVA) > 4 cm. A significantly higher prevalence of CPSM (28% vs. 1.1%, p < 0.001), but not CK (12% vs. 10.1%, p = 0.635), was found in PD patients compared with control patients. Among patients with PD, those with CK were younger (62.1 vs. 69.0 years, p = 0.013) and had longer duration of PD (56.4 vs. 36.2 months, p = 0.034), but the severity of PD was not significantly different. Logistic regression analysis revealed that the presence of CK was associated with younger age, higher mismatch between pelvic incidence and lumbar lordosis, and lower C7-S1 SVA. The patients with CPSM had significantly greater thoracic kyphosis (TK) (p < 0.001) and a trend toward more advanced H&Y stage (p = 0.05). Logistic regression analysis revealed that CPSM was associated with male sex, greater TK, and more advanced H&Y stage. Patients with PD have a significantly higher prevalence of CPSM compared with age- and sex-matched control patients with cervical degenerative disease but without PD. Among patients with PD, CK is not associated with the severity of PD but is associated with overall global sagittal malalignment. In contrast, the presence of CPSM is associated more with the severity of PD than it is with the presence of global sagittal malalignment. Collectively, these data suggest that the neuromuscular pathogenesis of PD may affect the development of CPSM more than of CK.

A transversal study of fundamental frequency contours in parkinsonian voices

According to numerous worldwide studies, patients with Parkinson’s disease (PD) often experience sleep disturbances, the most common of which are insomnia and excessive daytime sleepiness. The purpose of this study was to determine the quantitative and qualitative profile of sleep disorders in patients with the newly diagnosed PD, stages 1 and 2 according to Hoehn and Yahr. The assessment was carried out using the SCOPA-SLEEP scale. The study involved 95 people: 56 patients with a newly diagnosed PD, who had not previously received treatment (main group), and 39 individuals from the control group. Results. The profile of nocturnal sleep disturbances in PD patients was characterized by various symptoms: difficulty falling asleep (62,5%), night awakening (51,8%), long lying awake (57,1%), early awakening (50,0%), feeling lack of sleep (46,4%). In women, irrespective of the form and stage of PD, disturbances in nighttime sleep were found more often. Daytime hypersomnia among healthy volunteers was observed only in 5 participants (12,8%). The profile of daytime hypersomnia in PD patients was diverse: unexpected falling asleep during the day (n = 15, 26,8%), falling asleep in a calm environment (n = 17, 30,4%) or while reading and watching TV (n = 18, 32,1%). Difficulties in maintaining wakefulness during the day were noted by 13 patients (n = 13, 23,2%) with PD, and 4 patients (7,2%) reported difficulties due to excessive daytime sleepiness. Thus, given the prevalence and profile of dyssomnias, sleep disturbances may be an important sign of PD.

In Parkinson's disease oxidative stress and calcium-induced excitotoxicity have been considered important mechanisms leading to cell death for decades, but the factors that make some neurons vulnerable to neurodegeneration while others remain resistant are not fully understood. Studies of the disorder in animal models suggest that the voltage-gated calcium channel subtype Ca(V)1.3 has a role in making neurons susceptible to neurodegeneration and support earlier work in post-mortem human brain that suggested loss of calcium buffering capacity in neurons correlated with areas of neuronal loss in the substantia nigra of parkinsonian brain. This study examined expression of Ca(V)1 subtypes and the calcium-binding proteins calbindin, calmodulin and calreticulin in areas vulnerable and resistant to neurodegeneration in Parkinson's disease, in brain from neurologically normal individuals and patients with Parkinson's disease. In control brain the expression of a specific Ca(V)1 subtype or distribution of each calcium-binding protein did not associate with those regions prone to neurodegeneration in Parkinson's disease. Whereas, alterations in the amount of both Ca(V)1 subtypes and the calcium-binding proteins were found throughout the brain in Parkinson's disease. Some changes reflected the cell loss seen in Parkinson's disease, whereas others represented altered levels of cellular expression, which as they occurred in the absence of cell loss could not be explained as solely compensatory to the neurodegeneration. The finding of increased Ca(V)1.3 subtype expression in the cerebral cortex of early stage Parkinson's disease, before the appearance of pathological changes, supports the view that disturbed calcium homeostasis is an early feature of Parkinson's disease and not just a compensatory consequence to the neurodegenerative process. This interpretation is supported further by the finding that the ratio of Ca(V)1 subtypes differed throughout the brain in patients with Parkinson's disease compared with control subjects, in favour of an increased use of Ca(V)1.3, which would add to the metabolic burden for cells that rely on this Ca(V)1 subtype for electrical activity and could therefore render specific neuronal populations more vulnerable to neurodegeneration.

Parkinson's disease (PD) is the second most common neurodegenerative disease and affects millions of people. Accurate diagnosis and subsequent treatment in the early stages can slow down disease progression. However, making an accurate diagnosis of PD at an early stage is challenging. Previous studies have revealed that even for movement disorder specialists, it was difficult to differentiate patients with PD from healthy individuals until the average modified Hoehn-Yahr staging (mH&Y) reached 1.8. Recent researches have shown that dysarthria provides good indicators for computer-assisted diagnosis of patients with PD. However, few studies have focused on diagnosing patients with PD in the early stages, specifically those with mH&Y ≤ 1.5. We used a machine learning algorithm to analyze voice features and developed diagnostic models for differentiating between healthy controls (HCs) and patients with PD, and for differentiating between HCs and patients with mild PD (mH&Y ≤ 1.5). The models were independently validated using separate datasets. Our results demonstrate that, a remarkable diagnostic performance of the model in identifying patients with mild PD (mH&Y ≤ 1.5) and HCs, with area under the ROC curve 0.93 (95% CI: 0.851.00), accuracy 0.85, sensitivity 0.95, and specificity 0.75. The results of our study are helpful for screening PD in the early stages in the community and primary medical institutions where there is a lack of movement disorder specialists and special equipment.