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1.
WMJ ; 121(3): E46-E49, 2022 Oct.
Article in English | MEDLINE | ID: covidwho-2092955

ABSTRACT

INTRODUCTION: Atypical Parkinson's syndromes are a rare set of neurodegenerative conditions in which a patient experiences the typical symptoms of Parkinson's disease, in addition to various other unrelated issues. CASE PRESENTATION: We present the case of a 71-year-old White man with a 1-year history of weakness and upper extremity tremors that, per patient report, rapidly worsened after receiving the second dose of the Moderna COVID-19 vaccine. His symptoms were consistent with an asymmetric atypical Parkinson's disease, with electromyogram results indicating chronic motor neuron involvement. DISCUSSION: There have been multiple reports of deterioration in patients with Parkinson's disease and atypical Parkinson's syndromes in response to contracting COVID-19. However, there are few, if any, case reports that describe an acute change in Parkinson-related symptoms in association with the COVID-19 vaccines. CONCLUSIONS: As the pandemic continues, we must continue to remain vigilant as we learn more about the long-lasting effects of the virus and vaccines.


Subject(s)
COVID-19 Vaccines , COVID-19 , Parkinson Disease , Aged , Humans , Male , 2019-nCoV Vaccine mRNA-1273 , COVID-19/prevention & control , COVID-19 Vaccines/adverse effects , Parkinson Disease/complications , Parkinson Disease/diagnosis , Parkinson Disease/genetics , Syndrome
2.
WMJ ; 121(3): E46-E49, 2022 Oct.
Article in English | MEDLINE | ID: covidwho-2084108

ABSTRACT

INTRODUCTION: Atypical Parkinson's syndromes are a rare set of neurodegenerative conditions in which a patient experiences the typical symptoms of Parkinson's disease, in addition to various other unrelated issues. CASE PRESENTATION: We present the case of a 71-year-old White man with a 1-year history of weakness and upper extremity tremors that, per patient report, rapidly worsened after receiving the second dose of the Moderna COVID-19 vaccine. His symptoms were consistent with an asymmetric atypical Parkinson's disease, with electromyogram results indicating chronic motor neuron involvement. DISCUSSION: There have been multiple reports of deterioration in patients with Parkinson's disease and atypical Parkinson's syndromes in response to contracting COVID-19. However, there are few, if any, case reports that describe an acute change in Parkinson-related symptoms in association with the COVID-19 vaccines. CONCLUSIONS: As the pandemic continues, we must continue to remain vigilant as we learn more about the long-lasting effects of the virus and vaccines.


Subject(s)
COVID-19 Vaccines , COVID-19 , Parkinson Disease , Aged , Humans , Male , 2019-nCoV Vaccine mRNA-1273 , COVID-19/prevention & control , COVID-19 Vaccines/adverse effects , Parkinson Disease/complications , Parkinson Disease/diagnosis , Parkinson Disease/genetics , Syndrome
3.
Sensors (Basel) ; 22(17)2022 Aug 23.
Article in English | MEDLINE | ID: covidwho-2024045

ABSTRACT

The detection analysis of neurodegenerative diseases by means of low-cost sensors and suitable classification algorithms is a key part of the widely spreading telemedicine techniques. The choice of suitable sensors and the tuning of analysis algorithms require a large amount of data, which could be derived from a large experimental measurement campaign involving voluntary patients. This process requires a prior approval phase for the processing and the use of sensitive data in order to respect patient privacy and ethical aspects. To obtain clearance from an ethics committee, it is necessary to submit a protocol describing tests and wait for approval, which can take place after a typical period of six months. An alternative consists of structuring, implementing, validating, and adopting a software simulator at most for the initial stage of the research. To this end, the paper proposes the development, validation, and usage of a software simulator able to generate movement disorders-related data, for both healthy and pathological conditions, based on raw inertial measurement data, and give tri-axial acceleration and angular velocity as output. To present a possible operating scenario of the developed software, this work focuses on a specific case study, i.e., the Parkinson's disease-related tremor, one of the main disorders of the homonym pathology. The full framework is reported, from raw data availability to pathological data generation, along with a common machine learning method implementation to evaluate data suitability to be distinguished and classified. Due to the development of a flexible and easy-to-use simulator, the paper also analyses and discusses the data quality, described with typical measurement features, as a metric to allow accurate classification under a low-performance sensing device. The simulator's validation results show a correlation coefficient greater than 0.94 for angular velocity and 0.93 regarding acceleration data. Classification performance on Parkinson's disease tremor was greater than 98% in the best test conditions.


Subject(s)
Parkinson Disease , Tremor , Acceleration , Algorithms , Humans , Machine Learning , Parkinson Disease/diagnosis , Tremor/diagnosis
4.
JAMA Neurol ; 79(4): 359-369, 2022 04 01.
Article in English | MEDLINE | ID: covidwho-1971190

ABSTRACT

IMPORTANCE: Early features of Parkinson disease (PD) have been described through population-based studies that overrepresent White, affluent groups and may not be generalizable. OBJECTIVE: To investigate the association between risk factors and prediagnostic presentations of PD in an ethnically diverse UK population with high socioeconomic deprivation but universal access to health care. DESIGN, SETTING, AND PARTICIPANTS: A nested case-control study was conducted using electronic health care records on 1 016 277 individuals from primary care practices in East London to extract clinical information recorded between 1990 and February 6, 2018. The data were analyzed between September 3, 2020, and September 3, 2021. Individuals with a diagnosis of PD were compared with controls without PD or other major neurological conditions. MAIN OUTCOMES AND MEASURES: A matched analysis (10 controls matched for each patient with PD according to age and sex) and an unmatched analysis (adjusted for age and sex) were undertaken using multivariable logistic regression to determine associations between risk factors and prediagnostic presentations to primary care with subsequent diagnosis of PD. Three time periods (<2, 2-<5, and 5-10 years before diagnosis) were analyzed separately and together. RESULTS: Of 1 016 277 individuals included in the data set, 5699 were excluded and 1055 patients with PD and 1 009 523 controls were included in the analysis. Patients with PD were older than controls (mean [SD], 72.9 [11.3] vs 40.3 [15.2] years), and more were male (632 [59.9%] vs 516 862 [51.2%]). In the matched analysis (1055 individuals with PD and 10 550 controls), associations were found for tremor (odds ratio [OR], 145.96; 95% CI, 90.55-235.28) and memory symptoms (OR, 8.60; 95% CI, 5.91-12.49) less than 2 years before the PD diagnosis. The associations were also found up to 10 years before PD diagnosis for tremor and 5 years for memory symptoms. Among midlife risk factors, hypertension (OR, 1.36; 95% CI, 1.19-1.55) and type 2 diabetes (OR, 1.39; 95% CI, 1.19-1.62) were associated with subsequent diagnosis of PD. Associations with early nonmotor features, including hypotension (OR, 6.84; 95% CI, 3.38-13.85), constipation (OR, 3.29; 95% CI, 2.32-4.66), and depression (OR, 4.69; 95% CI, 2.88-7.63), were also noted. Associations were found for epilepsy (OR, 2.5; 95% CI, 1.63-3.83) and hearing loss (OR, 1.66; 95% CI, 1.06-2.58), which have not previously been well reported. These findings were replicated using data from the UK Biobank. No association with future PD diagnosis was found for ethnicity or deprivation index level. CONCLUSIONS AND RELEVANCE: This study provides data suggesting that a range of comorbidities and symptoms are encountered in primary care settings before PD diagnosis in an ethnically diverse and deprived population. Novel temporal associations were observed for epilepsy and hearing loss with subsequent development of PD. The prominence of memory symptoms suggests an excess of cognitive dysfunction in early PD in this population or difficulty in correctly ascertaining symptoms in traditionally underrepresented groups.


Subject(s)
Diabetes Mellitus, Type 2 , Parkinson Disease , Case-Control Studies , Humans , Male , Parkinson Disease/diagnosis , Parkinson Disease/epidemiology , Primary Health Care , Risk Factors , Tremor , United Kingdom/epidemiology
5.
Mov Disord ; 37(8): 1749-1755, 2022 08.
Article in English | MEDLINE | ID: covidwho-1898912

ABSTRACT

BACKGROUND: Telemedicine has become standard in clinical care and research during the coronavirus disease 2019 pandemic. Remote administration of Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Part III (Motor Examination) precludes ratings of all items, because Rigidity and Postural Stability (six scores) require in-person rating. OBJECTIVE: The objective of this study was to determine imputation accuracy for total-sum and item-specific MDS-UPDRS Motor Examination scores in remote administration. METHODS: We applied multivariate imputation by chained equations techniques in a cross-sectional dataset where patients had one MDS-UPDRS rating (International Translational Program, n = 8,588) and in a longitudinal dataset where patients had multiple ratings (Rush Program, n = 396). Successful imputation was stringently defined as (1) generalized Lin's concordance correlation coefficient >0.95, reflecting near-perfect agreement between total-sum score with complete data and surrogate score, calculated without patients' actual Rigidity and Postural Stability scores; and (2) perfect agreement for item-level scores for Rigidity and Postural Stability items. RESULTS: For total-sum score when Rigidity and Postural Stability scores were withdrawn, using one or multiple visits, multivariate imputation by chained equations imputation reached near-perfect agreement with the original total-sum score. However, at the item level, the degree of perfect agreement between the surrogate and actual Rigidity items and Postural Stability scores always fell below threshold. CONCLUSIONS: The MDS-UPDRS Part III total-sum score, a key clinical outcome in research and in clinical practice, can be accurately imputed without the Rigidity and Postural Stability items that cannot be rated by telemedicine. No formula, however, allows for specific item-level imputation. When Rigidity and Postural Stability item scores are of key clinical or research interest, patients with PD must be scored in person. © 2022 International Parkinson and Movement Disorder Society.


Subject(s)
COVID-19 , Parkinson Disease , Telemedicine , Cross-Sectional Studies , Humans , Mental Status and Dementia Tests , Parkinson Disease/diagnosis , Severity of Illness Index
6.
Int Rev Neurobiol ; 165: 135-171, 2022.
Article in English | MEDLINE | ID: covidwho-1866755

ABSTRACT

People with Parkinson's Disease (PwP) may be at higher risk for complications from the Coronavirus Disease 2019 (Covid-19) due to older age and to the multi-faceted nature of Parkinson's Disease (PD) per se, presenting with a variety of motor and non-motor symptoms. Those on advanced therapies may be particularly vulnerable. Taking the above into consideration, along with the potential multi-systemic impact of Covid-19 on affected patients and the complications of hospitalization, we are providing an evidence-based guidance to ensure a high standard of care for PwP affected by Covid-19 with varying severity of the condition. Adherence to the dopaminergic medication of PwP, without abrupt modifications in dosage and frequency, is of utmost importance, while potential interactions with newly introduced drugs should always be considered. Treating physicians should be cautious to acknowledge and timely address any potential complications, while consultation by a neurologist, preferably with special knowledge on movement disorders, is advised for patients admitted in non-neurological wards. Non-pharmacological approaches, including the patient's mobilization, falls prevention, good sleep hygiene, emotional support, and adequate nutritional and fluid intake, are essential and the role of telemedicine services should be strengthened and encouraged.


Subject(s)
COVID-19 , Parkinson Disease , Humans , Parkinson Disease/complications , Parkinson Disease/diagnosis , Parkinson Disease/therapy
7.
Curr Opin Neurol ; 34(4): 589-597, 2021 08 01.
Article in English | MEDLINE | ID: covidwho-1816369

ABSTRACT

PURPOSE OF REVIEW: The COVID-pandemic has facilitated the implementation of telemedicine in both clinical practice and research. We highlight recent developments in three promising areas of telemedicine: teleconsultation, telemonitoring, and teletreatment. We illustrate this using Parkinson's disease as a model for other chronic neurological disorders. RECENT FINDINGS: Teleconsultations can reliably administer parts of the neurological examination remotely, but are typically not useful for establishing a reliable diagnosis. For follow-ups, teleconsultations can provide enhanced comfort and convenience to patients, and provide opportunities for blended and proactive care models. Barriers include technological challenges, limited clinician confidence, and a suboptimal clinician-patient relationship. Telemonitoring using wearable sensors and smartphone-based apps can support clinical decision-making, but we lack large-scale randomized controlled trials to prove effectiveness on clinical outcomes. Increasingly many trials are now incorporating telemonitoring as an exploratory outcome, but more work remains needed to demonstrate its clinical meaningfulness. Finding a balance between benefits and burdens for individual patients remains vital. Recent work emphasised the promise of various teletreatment solutions, such as remotely adjustable deep brain stimulation parameters, virtual reality enhanced exercise programs, and telephone-based cognitive behavioural therapy. Personal contact remains essential to ascertain adherence to teletreatment. SUMMARY: The availability of different telemedicine tools for remote consultation, monitoring, and treatment is increasing. Future research should establish whether telemedicine improves outcomes in routine clinical care, and further underpin its merits both as intervention and outcome in research settings.


Subject(s)
COVID-19 , Parkinson Disease , Telemedicine , Humans , Pandemics , Parkinson Disease/diagnosis , Parkinson Disease/therapy , SARS-CoV-2
8.
Int Rev Neurobiol ; 165: 229-249, 2022.
Article in English | MEDLINE | ID: covidwho-1803313

ABSTRACT

Under the traditional models of care for People with Parkinson's Disease (PD, PwP), many of their needs remain unmet and a substantial burden of motor and non-motor symptoms they experience may not be tackled sufficiently. An introduction of palliative care (PC) interventions early in the course of PD offers profound benefits: it may improve quality of life of patients, their families and caregivers through the prevention and relief of medical symptoms, while, at the same time, emphasizing their emotional needs and spiritual wellbeing, establishing goals of care, and engaging in the advance care planning (ACP). The ongoing Coronavirus Disease 2019 (Covid-19) pandemic poses an unprecedented set of challenges for PwP and has in many ways (both directly and indirectly) magnified their suffering, thus rapidly raising the demand for PC interventions. Covid-19, as well as the repercussions of prolonged mobility restrictions and limited health-care access might exacerbate the severity of PD motor symptoms and interact negatively with a range of non-motor symptoms, with a detrimental effect on quality of life. Greater motor disability, higher amount of levodopa-induced motor fluctuations with an increased daily off-time, fatigue, anxiety, depression, sleep disturbances, pain and worsening of cognitive complaints might dominate the clinical presentation in PwP during the Covid-19 pandemic, alongside raising psychological and spiritual concerns and anticipatory grief. Here, we aim to provide a foundation for pragmatic and clinically orientated PC approach to improve quality of life and relieve suffering of PwP in the context of the current, ongoing Covid-19 pandemic.


Subject(s)
COVID-19 , Disabled Persons , Motor Disorders , Parkinson Disease , Ethnicity , Humans , Levodopa , Palliative Care , Pandemics , Parkinson Disease/diagnosis , Parkinson Disease/epidemiology , Parkinson Disease/therapy , Quality of Life/psychology
10.
Neurol Sci ; 43(6): 3479-3487, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-1750716

ABSTRACT

OBJECTIVE: Orthostatic hypotension (OH) represents a frequent but under-recognized phenomenon in Parkinson's disease (PD). During COVID-19 pandemic, Information and Communication Technologies (ICT) have become pivotal in the management of chronic diseases like PD, not only to assess motor impairment, but also for vital signs monitoring. This pilot study aimed to propose a real-time remote home-monitoring system and protocol for PD patients with OH. METHODS: Vital parameters were acquired by wireless devices and transmitted to an ICT platform, providing data and smart notifications to the healthcare provider through an interactive web portal. Eight patients with idiopathic PD and OH underwent 5-day monitoring. Data about OH episodes, therapeutic interventions, impact on daily activities, and patient satisfaction were collected and analyzed. RESULTS: The proposed solution allowed the identification of 65 OH episodes and subsequent medical interventions. Thirty-five episodes were asymptomatic, especially in the postprandial and in the afternoon recordings. Systolic-blood-pressure (SBP) and diastolic-blood-pressure (DBP) were significantly lower in symptomatic episodes, while the pressure drops resulted significantly higher in presence of symptoms. High usability and patient satisfaction scores were observed. CONCLUSION: The proposed home-monitoring system and protocol have proved to provide useful information and to allow prompt interventions in the management of PD patients with OH during COVID-19 pandemic.


Subject(s)
COVID-19 , Hypotension, Orthostatic , Parkinson Disease , Telemedicine , Blood Pressure/physiology , Humans , Hypotension, Orthostatic/diagnosis , Hypotension, Orthostatic/epidemiology , Hypotension, Orthostatic/etiology , Pandemics , Parkinson Disease/complications , Parkinson Disease/diagnosis , Parkinson Disease/drug therapy , Pilot Projects
11.
Sensors (Basel) ; 22(5)2022 Feb 24.
Article in English | MEDLINE | ID: covidwho-1742605

ABSTRACT

Parkinson's disease is a chronic neurodegenerative disease that affects a large portion of the population, especially the elderly. It manifests with motor, cognitive and other types of symptoms, decreasing significantly the patients' quality of life. The recent advances in the Internet of Things and Artificial Intelligence fields, including the subdomains of machine learning and deep learning, can support Parkinson's disease patients, their caregivers and clinicians at every stage of the disease, maximizing the treatment effectiveness and minimizing the respective healthcare costs at the same time. In this review, the considered studies propose machine learning models, trained on data acquired via smart devices, wearable or non-wearable sensors and other Internet of Things technologies, to provide predictions or estimations regarding Parkinson's disease aspects. Seven hundred and seventy studies have been retrieved from three dominant academic literature databases. Finally, one hundred and twelve of them have been selected in a systematic way and have been considered in the state-of-the-art systematic review presented in this paper. These studies propose various methods, applied on various sensory data to address different Parkinson's disease-related problems. The most widely deployed sensors, the most commonly addressed problems and the best performing algorithms are highlighted. Finally, some challenges are summarized along with some future considerations and opportunities that arise.


Subject(s)
Internet of Things , Neurodegenerative Diseases , Parkinson Disease , Aged , Artificial Intelligence , Humans , Machine Learning , Parkinson Disease/diagnosis , Parkinson Disease/therapy , Quality of Life
12.
Trials ; 22(1): 910, 2021 Dec 11.
Article in English | MEDLINE | ID: covidwho-1571920

ABSTRACT

BACKGROUND: The COVID-19 pandemic poses challenges for timely outcome assessment in randomized clinical trials (RCT). Our aim was to describe our remote neurocognitive testing (NCT) protocol administered by telephone in patients with Parkinson's disease (PD) and obstructive sleep apnea (OSA). METHODS: We studied PD patients with OSA and Montreal Cognitive Assessment (MoCA) score ≤ 27 participating in a RCT assessing OSA treatment impact on cognition. Trial outcomes included change in MoCA and specific cognitive domains from baseline to 3 and 6 months. With COVID19 pandemic-related restrictions, 3-month visits were converted from in-person to telephone administration with materials mailed to participants for compatible tests and retrieved by courier the same day. In exploratory analyses, we compared baseline vs. 3-month results in the control arm, which were not expected to change significantly (test-re-test), using a paired t-test and assessed agreement with the intraclass correlation coefficient (ICC). RESULTS: Seven participants were approached and agreed to remote NCT at 3-month follow-up. Compared to the in-person NCT control arm group, they were younger (60.6 versus 70.6 years) and had a shorter disease course (3.9 versus 9.2 years). Remote NCT data were complete. The mean test-retest difference in MoCA was similar for in-person and remote NCT control-arm groups (between group difference - 0.69; 95%CI - 3.67, 2.29). Agreement was good for MOCA and varied for specific neurocognitive tests. CONCLUSION: Telephone administration of the MoCA and a modified neurocognitive battery is feasible in patients with PD and OSA. Further validation will require a larger sample size.


Subject(s)
COVID-19 , Parkinson Disease , Sleep Apnea, Obstructive , Cognition , Feasibility Studies , Humans , Pandemics , Parkinson Disease/diagnosis , Parkinson Disease/therapy , SARS-CoV-2 , Sleep Apnea, Obstructive/diagnosis , Sleep Apnea, Obstructive/therapy
13.
J Med Internet Res ; 23(11): e29554, 2021 11 19.
Article in English | MEDLINE | ID: covidwho-1528771

ABSTRACT

BACKGROUND: Masked face is a characteristic clinical manifestation of Parkinson disease (PD), but subjective evaluations from different clinicians often show low consistency owing to a lack of accurate detection technology. Hence, it is of great significance to develop methods to make monitoring easier and more accessible. OBJECTIVE: The study aimed to develop a markerless 2D video, facial feature recognition-based, artificial intelligence (AI) model to assess facial features of PD patients and investigate how AI could help neurologists improve the performance of early PD diagnosis. METHODS: We collected 140 videos of facial expressions from 70 PD patients and 70 matched controls from 3 hospitals using a single 2D video camera. We developed and tested an AI model that performs masked face recognition of PD patients based on the acquisition and evaluation of facial features including geometric and texture features. Random forest, support vector machines, and k-nearest neighbor were used to train the model. The diagnostic performance of the AI model was compared with that of 5 neurologists. RESULTS: The experimental results showed that our AI models can achieve feasible and effective facial feature recognition ability to assist with PD diagnosis. The accuracy of PD diagnosis can reach 83% using geometric features. And with the model trained by random forest, the accuracy of texture features is up to 86%. When these 2 features are combined, an F1 value of 88% can be reached, where the random forest algorithm is used. Further, the facial features of patients with PD were not associated with the motor and nonmotor symptoms of PD. CONCLUSIONS: PD patients commonly exhibit masked facial features. Videos of a facial feature recognition-based AI model can provide a valuable tool to assist with PD diagnosis and the potential of realizing remote monitoring of the patient's condition, especially during the COVID-19 pandemic.


Subject(s)
COVID-19 , Facial Recognition , Parkinson Disease , Artificial Intelligence , Humans , Pandemics , Parkinson Disease/diagnosis , SARS-CoV-2
14.
J Neurol ; 269(3): 1107-1113, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1391865

ABSTRACT

BACKGROUND: With the explosion of COVID-19 globally, it was unclear if people with Parkinson's disease (PD) were at increased risk for severe manifestations or negative outcomes. OBJECTIVES: To report on people with PD who had suspected or confirmed COVID-19 to understand how COVID-19 manifested in PD patients. METHODS: We surveyed PD patients who reported COVID-19 to their Movement Disorders specialists at Columbia University Irving Medical Center and respondents from an online survey administered by the Parkinson's Foundation that assessed COVID-19 symptoms, general clinical outcomes and changes in motor and non-motor PD symptoms. RESULTS: Forty-six participants with PD and COVID-19 were enrolled. Similar to the general population, the manifestations of COVID-19 among people with PD were heterogeneous ranging from asymptomatic carriers (1/46) to death (6/46). The most commonly reported COVID-19 symptoms were fever/chills, fatigue, cough, weight loss, and muscle pain. Worsening and new onset of motor and non-motor PD symptoms during COVID-19 illness were also reported, including dyskinesia, rigidity, balance disturbances, anxiety, depression, and insomnia. CONCLUSION: We did not find sufficient evidence that PD is an independent risk factor for severe COVID-19 and death. Larger studies with controls are required to understand this further. Longitudinal follow-up of these participants will allow for observation of possible long-term effects of COVID-19 in PD patients.


Subject(s)
COVID-19 , Parkinson Disease , Anxiety/diagnosis , Humans , Parkinson Disease/complications , Parkinson Disease/diagnosis , Parkinson Disease/epidemiology , SARS-CoV-2 , Surveys and Questionnaires
15.
Sensors (Basel) ; 21(15)2021 Jul 21.
Article in English | MEDLINE | ID: covidwho-1346524

ABSTRACT

Mobile health (mHealth) has emerged as a potential solution to providing valuable ecological information about the severity and burden of Parkinson's disease (PD) symptoms in real-life conditions. Objective: The objective of our study was to explore the feasibility and usability of an mHealth system for continuous and objective real-life measures of patients' health and functional mobility, in unsupervised settings. Methods: Patients with a clinical diagnosis of PD, who were able to walk unassisted, and had an Android smartphone were included. Patients were asked to answer a daily survey, to perform three weekly active tests, and to perform a monthly in-person clinical assessment. Feasibility and usability were explored as primary and secondary outcomes. An exploratory analysis was performed to investigate the correlation between data from the mKinetikos app and clinical assessments. Results: Seventeen participants (85%) completed the study. Sixteen participants (94.1%) showed a medium-to-high level of compliance with the mKinetikos system. A 6-point drop in the total score of the Post-Study System Usability Questionnaire was observed. Conclusions: Our results support the feasibility of the mKinetikos system for continuous and objective real-life measures of a patient's health and functional mobility. The observed correlations of mKinetikos metrics with clinical data seem to suggest that this mHealth solution is a promising tool to support clinical decisions.


Subject(s)
Mobile Applications , Parkinson Disease , Telemedicine , Feasibility Studies , Humans , Parkinson Disease/diagnosis , Smartphone
16.
J Parkinsons Dis ; 11(s1): S11-S18, 2021.
Article in English | MEDLINE | ID: covidwho-1318376

ABSTRACT

Telemedicine programs are particularly suited to evaluating patients with Parkinson's disease (PD) and other movement disorders, primarily because much of the physical exam findings are visual. Telemedicine uses information and communication technologies to overcome geographical barriers and increase access to healthcare service. It is particularly beneficial for rural and underserved communities, groups that traditionally suffer from lack of access to healthcare. There is a growing evidence of the feasibility of telemedicine, cost and time savings, patients' and physicians' satisfaction, and its outcome and impact on patients' morbidity and quality of life. In addition, given the unusual current situation with the COVID-19 pandemic, telemedicine has offered the opportunity to address the ongoing healthcare needs of patients with PD, to reduce in-person clinic visits, and human exposures (among healthcare workers and patients) to a range of infectious diseases including COVID-19. However, there are still several challenges to widespread implementation of telemedicine including the limited performance of parts of the neurological exam, limited technological savvy, fear of loss of a personal connection, or uneasiness about communicating sensitive information. On the other hand, while we are facing the new wave of COVID-19 pandemic, patients and clinicians are gaining increasing experience with telemedicine, facilitating equity of access to specialized multidisciplinary care for PD. This article summarizes and reviews the current state and future directions of telemedicine from a global perspective.


Subject(s)
Parkinson Disease/diagnosis , Parkinson Disease/therapy , Telemedicine , COVID-19/complications , Health Services Accessibility , Humans , Pandemics
17.
In Vivo ; 35(4): 2327-2330, 2021.
Article in English | MEDLINE | ID: covidwho-1285629

ABSTRACT

BACKGROUND: Accurate assessment of symptoms in Parkinson's disease (PD) is essential for optimal treatment decisions. During the past few years, different monitoring modalities have started to be used in the everyday clinical practice, mainly for the evaluation of motor symptoms. However, monitoring technologies for PD have not yet gained wide acceptance among physicians, patients, and caregivers. The COVID-19 pandemic disrupted the patients' access to healthcare, bringing to the forefront the need for wearable sensors, which provide effective remote symptoms' evaluation and follow-up. CASE REPORT: We report two cases with PD, whose symptoms were monitored with a new wearable CE-marked system (PDMonitor®), enabling appropriate treatment modifications. CONCLUSION: Objective assessment of the patient's motor symptoms in his daily home environment is essential for an accurate monitoring in PD and enhances treatment decisions.


Subject(s)
COVID-19 , Parkinson Disease , Wearable Electronic Devices , Humans , Pandemics , Parkinson Disease/diagnosis , Parkinson Disease/epidemiology , Parkinson Disease/therapy , SARS-CoV-2
18.
Neurol Sci ; 42(8): 3089-3092, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1245657

ABSTRACT

BACKGROUND: Falls could be serious events in Parkinson's disease (PD). Patient remote monitoring strategies are on the raise and may be an additional aid in identifying patients who are at risk of falling. The aim of the study was to evaluate if balance and timed-up-and-go data obtained by a smartphone application during COVID-19 lockdown were able to predict falls in PD patients. METHODS: A cohort of PD patients were monitored for 4 weeks during the COVID-19 lockdown with an application measuring static balance and timed-up-and-go test. The main outcome was the occurrence of falls (UPDRS-II item 13) during the observation period. RESULTS: Thirty-three patients completed the study, and 4 (12%) reported falls in the observation period. The rate of falls was reduced with respect to patient previous falls history (24%). The stand-up time and the mediolateral sway, acquired through the application, differed between "fallers" and "non-fallers" and related to the occurrence of new falls (OR 1.7 and 1.6 respectively, p < 0.05), together with previous falling (OR 7.5, p < 0.01). In a multivariate model, the stand-up time and the history of falling independently related to the outcome (p < 0.01). CONCLUSIONS: Our study provides new data on falls in Parkinson's disease during the lockdown. The reduction of falling events and the relationship with the stand-up time might suggest that a different quality of falls occurs when patient is forced to stay home - hence, clinicians should point their attention also on monitoring patients' sit-to-stand body transition other than more acknowledged features based on step quality.


Subject(s)
COVID-19 , Parkinson Disease , Communicable Disease Control , Gait , Gait Analysis , Humans , Parkinson Disease/complications , Parkinson Disease/diagnosis , Postural Balance , SARS-CoV-2 , Smartphone , Time and Motion Studies
19.
J Parkinsons Dis ; 11(3): 971-992, 2021.
Article in English | MEDLINE | ID: covidwho-1201362

ABSTRACT

Sleep disturbances are among the common nonmotor symptoms in patients with Parkinson's disease (PD). Sleep can be disrupted by nocturnal motor and nonmotor symptoms and other comorbid sleep disorders. Rapid eye movement sleep behavior disorder (RBD) causes sleep-related injury, has important clinical implications as a harbinger of PD and predicts a progressive clinical phenotype. Restless legs syndrome (RLS) and its related symptoms can impair sleep initiation. Excessive daytime sleepiness (EDS) is a refractory problem affecting patients' daytime activities. In particular, during the COVID-19 era, special attention should be paid to monitoring sleep problems, as infection-prevention procedures for COVID-19 can affect patients' motor symptoms, psychiatric symptoms and sleep. Therefore, screening for and managing sleep problems is important in clinical practice, and the maintenance of good sleep conditions may improve the quality of life of PD patients. This narrative review focused on the literature published in the past 10 years, providing a current update of various sleep disturbances in PD patients and their management, including RBD, RLS, EDS, sleep apnea and circadian abnormalities.


Subject(s)
Disorders of Excessive Somnolence , Parkinson Disease , REM Sleep Behavior Disorder , Restless Legs Syndrome , Sleep Apnea Syndromes , Sleep Disorders, Circadian Rhythm , COVID-19 , Disorders of Excessive Somnolence/diagnosis , Disorders of Excessive Somnolence/etiology , Disorders of Excessive Somnolence/therapy , Humans , Parkinson Disease/complications , Parkinson Disease/diagnosis , Parkinson Disease/therapy , REM Sleep Behavior Disorder/diagnosis , REM Sleep Behavior Disorder/etiology , REM Sleep Behavior Disorder/therapy , Restless Legs Syndrome/diagnosis , Restless Legs Syndrome/etiology , Restless Legs Syndrome/therapy , Sleep Apnea Syndromes/diagnosis , Sleep Apnea Syndromes/etiology , Sleep Apnea Syndromes/therapy , Sleep Disorders, Circadian Rhythm/diagnosis , Sleep Disorders, Circadian Rhythm/etiology , Sleep Disorders, Circadian Rhythm/therapy
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