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1.
Mov Disord ; 2021 May 06.
Artigo em Inglês | MEDLINE | ID: mdl-33955603

RESUMO

BACKGROUND: It is not clear how specific gait measures reflect disease severity across the disease spectrum in Parkinson's disease (PD). OBJECTIVE: To identify the gait and mobility measures that are most sensitive and reflective of PD motor stages and determine the optimal sensor location in each disease stage. METHODS: Cross-sectional wearable-sensor records were collected in 332 patients with PD (Hoehn and Yahr scale I-III) and 100 age-matched healthy controls. Sensors were adhered to the participant's lower back, bilateral ankles, and wrists. Study participants walked in a ~15-meter corridor for 1 minute under two walking conditions: (1) preferred, usual walking speed and (2) walking while engaging in a cognitive task (dual-task). A subgroup (n = 303, 67% PD) also performed the Timed Up and Go test. Multiple machine-learning feature selection and classification algorithms were applied to discriminate between controls and PD and between the different PD severity stages. RESULTS: High discriminatory values were found between motor disease stages with mean sensitivity in the range 72%-83%, specificity 69%-80%, and area under the curve (AUC) 0.76-0.90. Measures from upper-limb sensors best discriminated controls from early PD, turning measures obtained from the trunk sensor were prominent in mid-stage PD, and stride timing and regularity were discriminative in more advanced stages. CONCLUSIONS: Applying machine-learning to multiple, wearable-derived features reveals that different measures of gait and mobility are associated with and discriminate distinct stages of PD. These disparate feature sets can augment the objective monitoring of disease progression and may be useful for cohort selection and power analyses in clinical trials of PD. © 2021 International Parkinson and Movement Disorder Society.

3.
Artigo em Inglês | MEDLINE | ID: mdl-33812348

RESUMO

BACKGROUND: Optimal care for Parkinson's disease (PD) requires coordination and collaboration between providers within a complex care network. Individual patients have personalised networks of their own providers, creating a unique informal network of providers who treat ('share') the same patient. These 'patient-sharing networks' differ in density, ie, the number of identical patients they share. Denser patient-sharing networks might reflect better care provision, since providers who share many patients might have made efforts to improve their mutual care delivery. We evaluated whether the density of these patient-sharing networks affects patient outcomes and costs. METHODS: We analysed medical claims data from all PD patients in the Netherlands between 2012 and 2016. We focused on seven professional disciplines that are commonly involved in Parkinson care. We calculated for each patient the density score: the average number of patients that each patient's providers shared. Density scores could range from 1.00 (which might reflect poor collaboration) to 83.00 (which might reflect better collaboration). This score was also calculated at the hospital level by averaging the scores for all patients belonging to a specific hospital. Using logistic and linear regression analyses we estimated the relationship between density scores and health outcomes, healthcare utilization, and healthcare costs. RESULTS: The average density score varied considerably (average 6.7, SD 8.2). Adjusted for confounders, higher density scores were associated with a lower risk of PD-related complications (odds ratio [OR]: 0.901; P<.001) and with lower healthcare costs (coefficients: -0.018, P=.005). Higher density scores were associated with more frequent involvement of neurologists (coefficient 0.068), physiotherapists (coefficient 0.052) and occupational therapists (coefficient 0.048) (P values all <.001). CONCLUSION: Patient sharing networks showed large variations in density, which appears unwanted as denser networks are associated with better outcomes and lower costs.

4.
Lancet ; 2021 Apr 09.
Artigo em Inglês | MEDLINE | ID: mdl-33848468

RESUMO

Parkinson's disease is a recognisable clinical syndrome with a range of causes and clinical presentations. Parkinson's disease represents a fast-growing neurodegenerative condition; the rising prevalence worldwide resembles the many characteristics typically observed during a pandemic, except for an infectious cause. In most populations, 3-5% of Parkinson's disease is explained by genetic causes linked to known Parkinson's disease genes, thus representing monogenic Parkinson's disease, whereas 90 genetic risk variants collectively explain 16-36% of the heritable risk of non-monogenic Parkinson's disease. Additional causal associations include having a relative with Parkinson's disease or tremor, constipation, and being a non-smoker, each at least doubling the risk of Parkinson's disease. The diagnosis is clinically based; ancillary testing is reserved for people with an atypical presentation. Current criteria define Parkinson's disease as the presence of bradykinesia combined with either rest tremor, rigidity, or both. However, the clinical presentation is multifaceted and includes many non-motor symptoms. Prognostic counselling is guided by awareness of disease subtypes. Clinically manifest Parkinson's disease is preceded by a potentially long prodromal period. Presently, establishment of prodromal symptoms has no clinical implications other than symptom suppression, although recognition of prodromal parkinsonism will probably have consequences when disease-modifying treatments become available. Treatment goals vary from person to person, emphasising the need for personalised management. There is no reason to postpone symptomatic treatment in people developing disability due to Parkinson's disease. Levodopa is the most common medication used as first-line therapy. Optimal management should start at diagnosis and requires a multidisciplinary team approach, including a growing repertoire of non-pharmacological interventions. At present, no therapy can slow down or arrest the progression of Parkinson's disease, but informed by new insights in genetic causes and mechanisms of neuronal death, several promising strategies are being tested for disease-modifying potential. With the perspective of people with Parkinson's disease as a so-called red thread throughout this Seminar, we will show how personalised management of Parkinson's disease can be optimised.

5.
Mov Disord ; 2021 Apr 02.
Artigo em Inglês | MEDLINE | ID: mdl-33797786

RESUMO

In the advanced stages of Parkinson's disease (PD), patients frequently experience disabling motor complications. Treatment options include deep brain stimulation (DBS), levodopa-carbidopa intestinal gel (LCIG), and continuous subcutaneous apomorphine infusion (CSAI). Choosing among these treatments is influenced by scientific evidence, clinical expertise, and patient preferences. To foster patient engagement in decision-making among the options, scientific evidence should be adjusted to their information needs. We conducted a systematic review from the patient perspective. First, patients selected outcomes for a treatment choice: quality of life, activities of daily living, ON and OFF time, and adverse events. Second, we conducted a systematic review and meta-analysis for each treatment versus best medical treatment using Grading of Recommendations, Assessment, Development, and Evaluation (GRADE). Finally, the evidence was transformed into comprehensible and comparable information. We converted the meta-analysis results into the number of patients (per 100) who benefit clinically from an advanced treatment per outcome, based on the minimal clinically important difference and the cumulative distribution function. Although this approach allows for a comparison of outcomes across the three device-aided therapies, they have never been compared directly. The interpretation is hindered by the relatively short follow-up time in the included studies, usually less than 12 months. These limitations should be clarified to patients during the decision-making process. This review can help patients integrate the evidence with their own preferences, and with their clinician's expertise, to reach an informed decision. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

6.
NPJ Parkinsons Dis ; 7(1): 29, 2021 Mar 19.
Artigo em Inglês | MEDLINE | ID: mdl-33741988

RESUMO

Peripheral decarboxylase inhibitors (PDIs) prevent conversion of levodopa to dopamine in the blood by the enzyme aromatic L-amino acid decarboxylase (AADC). Alterations in enzyme activity may contribute to the required higher dosages of levodopa observed in many patients with Parkinson's disease. We evaluated the effect of levodopa/PDI use on serum AADC enzyme activity. Serum AADC enzyme activity was evaluated in three independent cohorts of patients with Parkinson's disease or parkinsonism (n = 301) and compared between patients on levodopa/PDI vs. patients not on this medication. AADC enzyme activity was elevated in 62% of patients on levodopa/PDI treatment, compared to 19% of patients not on levodopa/PDI (median 90 mU/L vs. 50 mU/L, p < 0.001). Patients with elevated AADC activity had longer disease duration and higher doses of levodopa/PDI. These findings may implicate that peripheral AADC induction could underlie a waning effect of levodopa, necessitating dose increases to maintain a sustained therapeutic effect.

7.
J Parkinsons Dis ; 11(1): 3-8, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33523021

RESUMO

Several COVID-19 vaccines have recently been approved for emergency use according to governmental immunization programs. The arrival of these vaccines has created hope for people with Parkinson's disease (PD), as this can help to mitigate their risk of becoming infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which can lead to serious, life-threatening disease, at least among those with more advanced PD. However, both persons with PD and physicians looking after these individuals have expressed concerns about the vaccine's efficacy and safety in the specific context of PD and its symptomatic treatment. Here, we discuss our perspective on these concerns, based on our interpretation of the literature plus the unfolding experience with widespread vaccination in the population at large. Because the benefits and risks of COVID-19 vaccines do not appear to be different than in the general population, we recommend COVID-19 vaccination with approved vaccines to persons with PD, unless there is a specific contraindication. Some caution seems warranted in very frail and terminally ill elderly persons with PD living in long-term care facilities.


Assuntos
/uso terapêutico , Doença de Parkinson , Idoso , Idoso de 80 Anos ou mais , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Vacinação
10.
Parkinsonism Relat Disord ; 84: 155-163, 2021 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-33487544

RESUMO

BACKGROUND: Interest has risen in identifying individuals at high risk of incident Parkinson's disease (PD) to facilitate inclusion in neuroprotective treatment trials. Current risk estimates of prodromal markers are based on aggregated data of an entire population, but this approach disregards differences in risk estimates by subgroups of a population. In this proof of concept, we determine subgroup-specific risk estimates of olfactory dysfunction for incident PD. METHODS: PubMed, EMBASE and Cochrane were searched for prospective studies investigating the association between olfactory dysfunction and incident PD. Random-effects meta-analysis, subgroup analyses and meta-regression were performed to investigate general and subgroup risk estimates. RESULTS: Individuals with odor identification dysfunction seemed to be at greater risk of incident PD compared to controls without olfactory dysfunction (OR = 4.18; 95%CI [2.47-7.07]). Risk estimates were higher in studies that included higher percentages of women (regression slope ß = 0.053 increase in log odds ratio per 1% increase 1%, p = 0.0006), increased with mean study age (ß = 0.21 per one year increase; p = 0.005) and in REM-sleep behavior disorder cohorts (ß = 1.95; p = 0.03). Furthermore, the association between olfactory dysfunction and incident PD was most distinct in studies with shorter follow-up duration (ß = -0.56; p = 0.0047). CONCLUSION: The presence of olfactory dysfunction conveys a considerably elevated risk of incident PD, likely more in studies with a higher proportion of women, older individuals or short follow-up duration. Individual patient data are warranted to confirm these findings and to yield subgroup-specific risk estimates of other common markers to refine prodromal PD criteria.

13.
Artigo em Inglês | MEDLINE | ID: mdl-33180738

RESUMO

Passive monitoring in daily life may provide valuable insights into a persons health throughout the day. Wearable sensor devices are likely to play a key role in enabling such monitoring in a non-obtrusive fashion.However, sensor data collected in daily life reflect multiple health and behavior-related factors together. This creates the need for a structured principled analysis to produce reliable and interpretable predictions that can be used to support clinical diagnosis and treatment. In this work we develop a principled modelling approach for free-living gait (walking) analysis. Gait is a promising target for non-obtrusive monitoring because it is common and indicative of many different movement disorders such as Parkinsons disease (PD), yet its analysis has largely been limited to experimentally controlled lab settings. To locate and characterize stationary gait segments in free living using accelerometers, we present an unsupervised probabilistic framework designed to segment signals into differing gait and non-gait patterns. This framework incorporates empirical assumptions about gait into a principled graphical model with all of its merits. We evaluate the approach using a new video-referenced dataset including 25 PD patients with motor fluctuations and 25 age-matched controls,performing unscripted daily living activities in and around their own houses. Using this dataset, we demonstrate the frameworks ability to detect gait and predict medication induced fluctuations in PD patients based on free living gait. We show that our approach is robust to varying sensor locations, including the wrist, ankle, trouser pocket and lower back.

14.
Eur J Neurol ; 2020 Nov 03.
Artigo em Inglês | MEDLINE | ID: mdl-33141474

RESUMO

BACKGROUND AND PURPOSE: To determine how the coverage of specialized allied health services for patients with Parkinson's disease (PD) has developed in the Netherlands since the publication of trials that demonstrated cost-effectiveness. METHODS: We used healthcare expenditure-based data on all insured individuals in the Netherlands to determine the annual proportion of patients with PD who received either specialized or generic allied health services (physiotherapy, occupational therapy, speech-language therapy) in 2 calendar years separated by a 5-year interval (2012 and 2017). Specialized allied health services were delivered through the ParkinsonNet approach, which encompassed professional training and concentration of care among specifically trained professionals. RESULTS: Between 2012 and 2017, there was an increase in the number of patients with any physiotherapy (from 17,843 [62% of all patients with PD that year] to 22,282 [68%]), speech-language therapy (from 2171 [8%] to 3378 [10%]), and occupational therapy (from 2813 [10%] to 5939 [18%]). Among therapy-requiring patients, the percentage who were treated by a specialized therapist rose substantially for physiotherapy (from 36% in 2012 to 62% in 2017; χ2  = 2460.2; p < 0.001), speech-language therapy (from 59% to 85%; χ2  = 445.4; p < 0.001), and occupational therapy (from 61% to 77%; χ2  = 231.6; p < 0.001). By contrast, the number of patients with generic therapists did not change meaningfully. By 2017, specialized care delivery had extended to regions that had been poorly covered in 2012, essentially achieving nationwide coverage. CONCLUSIONS: Following the publication of positive trials, specialized allied healthcare delivery was successfully scaled for patients with PD in the Netherlands, potentially serving as a template for other healthcare innovations for patients with PD elsewhere.

17.
Mov Disord ; 2020 Oct 01.
Artigo em Inglês | MEDLINE | ID: mdl-33002231

RESUMO

BACKGROUND: Previous studies reported various symptoms of Parkinson's disease (PD) associated with sex. Some were conflicting or confirmed in only one study. OBJECTIVES: We examined sex associations to PD phenotypes cross-sectionally and longitudinally in large-scale data. METHODS: We tested 40 clinical phenotypes, using longitudinal, clinic-based patient cohorts, consisting of 5946 patients, with a median follow-up of 3.1 years. For continuous outcomes, we used linear regressions at baseline to test sex-associated differences in presentation, and linear mixed-effects models to test sex-associated differences in progression. For binomial outcomes, we used logistic regression models at baseline and Cox regression models for survival analyses. We adjusted for age, disease duration, and medication use. In the secondary analyses, data from 17 719 PD patients and 7588 non-PD participants from an online-only, self-assessment PD cohort were cross-sectionally evaluated to determine whether the sex-associated differences identified in the primary analyses were consistent and unique to PD. RESULTS: Female PD patients had a higher risk of developing dyskinesia early during the follow-up period, with a slower progression in activities of daily living difficulties, and a lower risk of developing cognitive impairments compared with male patients. The findings in the longitudinal, clinic-based cohorts were mostly consistent with the results of the online-only cohort. CONCLUSIONS: We observed sex-associated contributions to PD heterogeneity. These results highlight the necessity of future research to determine the underlying mechanisms and importance of personalized clinical management. © 2020 International Parkinson and Movement Disorder Society.

18.
J Med Internet Res ; 22(10): e19068, 2020 Oct 09.
Artigo em Inglês | MEDLINE | ID: mdl-33034562

RESUMO

BACKGROUND: Wearable sensors have been used successfully to characterize bradykinetic gait in patients with Parkinson disease (PD), but most studies to date have been conducted in highly controlled laboratory environments. OBJECTIVE: This paper aims to assess whether sensor-based analysis of real-life gait can be used to objectively and remotely monitor motor fluctuations in PD. METHODS: The Parkinson@Home validation study provides a new reference data set for the development of digital biomarkers to monitor persons with PD in daily life. Specifically, a group of 25 patients with PD with motor fluctuations and 25 age-matched controls performed unscripted daily activities in and around their homes for at least one hour while being recorded on video. Patients with PD did this twice: once after overnight withdrawal of dopaminergic medication and again 1 hour after medication intake. Participants wore sensors on both wrists and ankles, on the lower back, and in the front pants pocket, capturing movement and contextual data. Gait segments of 25 seconds were extracted from accelerometer signals based on manual video annotations. The power spectral density of each segment and device was estimated using Welch's method, from which the total power in the 0.5- to 10-Hz band, width of the dominant frequency, and cadence were derived. The ability to discriminate between before and after medication intake and between patients with PD and controls was evaluated using leave-one-subject-out nested cross-validation. RESULTS: From 18 patients with PD (11 men; median age 65 years) and 24 controls (13 men; median age 68 years), ≥10 gait segments were available. Using logistic LASSO (least absolute shrinkage and selection operator) regression, we classified whether the unscripted gait segments occurred before or after medication intake, with mean area under the receiver operator curves (AUCs) varying between 0.70 (ankle of least affected side, 95% CI 0.60-0.81) and 0.82 (ankle of most affected side, 95% CI 0.72-0.92) across sensor locations. Combining all sensor locations did not significantly improve classification (AUC 0.84, 95% CI 0.75-0.93). Of all signal properties, the total power in the 0.5- to 10-Hz band was most responsive to dopaminergic medication. Discriminating between patients with PD and controls was generally more difficult (AUC of all sensor locations combined: 0.76, 95% CI 0.62-0.90). The video recordings revealed that the positioning of the hands during real-life gait had a substantial impact on the power spectral density of both the wrist and pants pocket sensor. CONCLUSIONS: We present a new video-referenced data set that includes unscripted activities in and around the participants' homes. Using this data set, we show the feasibility of using sensor-based analysis of real-life gait to monitor motor fluctuations with a single sensor location. Future work may assess the value of contextual sensors to control for real-world confounders.

19.
Front Neurol ; 11: 576121, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33071952

RESUMO

The impact of sex and gender on disease incidence, progression, and provision of care has gained increasing attention in many areas of medicine. Biological factors-sex-and sociocultural and behavioral factors-gender-greatly impact on health and disease. While sex can modulate disease progression and response to therapy, gender can influence patient-provider communication, non-pharmacological disease management, and need for assistance. Sex and gender issues are especially relevant in chronic progressive diseases, such as Parkinson's disease (PD), because affected patients require multidisciplinary care for prolonged periods of time. In this perspective paper, we draw from evidence in the field of PD and various other areas of medicine to address how sex and gender could impact PD care provision. We highlight examples for which differences have been reported and formulate research topics and considerations on how to optimize the multidisciplinary care of persons with PD.

20.
J Geriatr Psychiatry Neurol ; : 891988720968263, 2020 Oct 23.
Artigo em Inglês | MEDLINE | ID: mdl-33094677

RESUMO

BACKGROUND: Patients in the late stages of parkinsonism are highly dependent on others in their self-care and activities of daily living. However, few studies have assessed the physical, psychological and social consequences of caring for a person with late-stage parkinsonism. PATIENTS AND METHODS: Five hundred and six patients and their caregivers from the Care of Late Stage Parkinsonism (CLaSP) study were included. Patients' motor and non-motor symptoms were assessed using the UPDRS and Non-motor symptom scale (NMSS), Neuropsychiatric inventory (NPI-12), and caregivers' health status using the EQ-5D-3 L. Caregiver burden was assessed by the Zarit Burden Interview (ZBI). RESULTS: The majority of caregivers were the spouse or life partner (71.2%), and were living with the patient at home (67%). Approximately half of caregivers reported anxiety/depression and pain/discomfort (45% and 59% respectively). The factors most strongly associated with caregiver burden were patients' neuropsychiatric features on the total NPI score (r = 0.38, p < 0.0001), total NMSS score (r = 0.28, p < 0.0001), caring for male patients and patients living at home. Being the spouse, the hours per day assisting and supervising the patient as well as caregivers' EQ-5D mood and pain scores were also associated with higher ZBI scores (all p < 0.001). CONCLUSION: The care of patients with late stage parkinsonism is associated with significant caregiver burden, particularly when patients manifest many neuropsychiatric and non-motor features and when caring for a male patient at home.

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