Opinion & Special Articles: Professionalism in neurology

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Fifteen years of wireless sensors for balance assessment in neurological disorders

Balance impairment is a major mechanism behind falling along with environmental hazards. Under physiological conditions, ageing leads to a progressive decline in balance control per se. Moreover, various neurological disorders further increase the risk of falls by deteriorating specific nervous system functions contributing to balance. Over the last 15 years, significant advancements in technology have provided wearable solutions for balance evaluation and the management of postural instability in patients with neurological disorders. This narrative review aims to address the topic of balance and wireless sensors in several neurological disorders, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, stroke, and other neurodegenerative and acute clinical syndromes. The review discusses the physiological and pathophysiological bases of balance in neurological disorders as well as the traditional and innovative instruments currently available for balance assessment. The technical and clinical perspectives of wearable technologies, as well as current challenges in the field of teleneurology, are also examined

Dysregulation of MS risk genes and pathways at distinct stages of disease

OBJECTIVE: To perform systematic transcriptomic analysis of multiple sclerosis (MS) risk genes in peripheral blood mononuclear cells (PBMCs) of subjects with distinct MS stages and describe the pathways characterized by dysregulated gene expressions. METHODS: We monitored gene expression levels in PBMCs from 3 independent cohorts for a total of 297 cases (including clinically isolated syndromes (CIS), relapsing-remitting MS, primary and secondary progressive MS) and 96 healthy controls by distinct microarray platforms and quantitative PCR. Differential expression and pathway analyses for distinct MS stages were defined and validated by literature mining. RESULTS: Genes located in the vicinity of MS risk variants displayed altered expression in peripheral blood at distinct stages of MS compared with the healthy population. The frequency of dysregulation was significantly higher than expected in CIS and progressive forms of MS. Pathway analysis for each MS stage–specific gene list showed that dysregulated genes contributed to pathogenic processes with scientific evidence in MS. CONCLUSIONS: Systematic gene expression analysis in PBMCs highlighted selective dysregulation of MS susceptibility genes playing a role in novel and well-known pathogenic pathways

Automatic assessment of the 2-minute walk distance for remote monitoring of people with multiple sclerosis

The aim of this study was to investigate the feasibility of automatically assessing the 2-Minute Walk Distance (2MWD) for monitoring people with multiple sclerosis (pwMS). For 154 pwMS, MS-related clinical outcomes as well as the 2MWDs as evaluated by clinicians and derived from accelerometer data were collected from a total of 323 periodic clinical visits. Accelerometer data from a wearable device during 100 home-based 2MWD assessments were also acquired. The error in estimating the 2MWD was validated for walk tests performed at hospital, and then the correlation (r) between clinical outcomes and home-based 2MWD assessments was evaluated. Robust performance in estimating the 2MWD from the wearable device was obtained, yielding an error of less than 10% in about two-thirds of clinical visits. Correlation analysis showed that there is a strong association between the actual and the estimated 2MWD obtained either at hospital (r = 0.71) or at home (r = 0.58). Furthermore, the estimated 2MWD exhibits moderate-to-strong correlation with various MS-related clinical outcomes, including disability and fatigue severity scores. Automatic assessment of the 2MWD in pwMS is feasible with the usage of a consumer-friendly wearable device in clinical and non-clinical settings. Wearable devices can also enhance the assessment of MS-related clinical outcomes

Conspicuous multidrug-resistant Mycobacterium tuberculosis cluster strains do not trespass country borders in Latin America and Spain

Multidrug-resistant Mycobacterium tuberculosis strain diversity in Ibero-America was examined by comparing extant genotype collections in national or state tuberculosis networks. To this end, genotypes from over 1000 patients with multidrug-resistant tuberculosis diagnosed from 2004 through 2008 in Argentina, Brazil, Chile, Colombia, Venezuela and Spain were compared in a database constructed ad hoc. Most of the 116 clusters identified by IS6110 restriction fragment length polymorphism were small and restricted to individual countries. The three largest clusters, of 116, 49 and 25 patients, were found in Argentina and corresponded to previously documented locally-epidemic strains. Only 13 small clusters involved more than one country, altogether accounting for 41 patients, of whom 13 were, in turn, immigrants from Latin American countries different from those participating in the study (Peru, Ecuador and Bolivia). Most of these international clusters belonged either to the emerging RD(Rio) LAM lineage or to the Haarlem family of M. tuberculosis and four were further split by country when analyzed with spoligotyping and rifampin resistance-conferring mutations, suggesting that they did not represent ongoing transnational transmission events. The Beijing genotype accounted for 1.3% and 10.2% of patients with multidrug-resistant tuberculosis in Latin America and Spain, respectively, including one international cluster of two cases. In brief, Euro-American genotypes were widely predominant among multidrug-resistant M. tuberculosis strains in Ibero-America, reflecting closely their predominance in the general M. tuberculosis population in the region, and no evidence was found of acknowledged outbreak strains trespassing country borders.Fil: Ritacco, Gloria Viviana. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Dirección Nacional de Instituto de Investigación.Administración Nacional de Laboratorios e Institutos de Salud "Dr. Carlos G. Malbrán"; ArgentinaFil: Iglesias, Maria Jose. Universidad de Zaragoza; EspañaFil: Ferrazoli, Lucilaine. Instituto Adolfo Lutz; BrasilFil: Monteserin, Johana. Dirección Nacional de Instituto de Investigación.Administración Nacional de Laboratorios e Institutos de Salud "Dr. Carlos G. Malbrán"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Dalla Costa, Elis R.. Centro de Desenvolvimento Científico e Tecnológico; BrasilFil: Cebollada, Alberto. Universidad de Zaragoza; EspañaFil: Morcillo, Nora Susana. Provincia de Buenos Aires. Ministerio de Salud. Hospital ; ArgentinaFil: Robledo, Jaime. No especifíca;Fil: de Waar, Jacobus H.. Instituto de Biomedicina; VenezuelaFil: Araya, Pamela. Instituto de Salud Pública de Chile; ChileFil: Aristimiño, Liselotte. Universidad Centroccidental Lisandro Alvarado (ucla);Fil: Diaz, Raúl. Instituto Pedro Khouri; CubaFil: Gavin, Patricia. Universidad de Zaragoza; EspañaFil: Imperiale, Belén Rocío. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Simonsen, Vera. Instituto Adolfo Lutz; BrasilFil: Zapata, Elsa M.. No especifíca;Fil: Jiménez, María S.. Instituto de Salud Carlos III. Centro Nacional de Microbiología; EspañaFil: Rossetti, Maria L.. No especifíca;Fil: Martin, Carlos. Universidad de Zaragoza; EspañaFil: Barrera, Lucía. Dirección Nacional de Instituto de Investigación.Administración Nacional de Laboratorios e Institutos de Salud "Dr. Carlos G. Malbrán"; ArgentinaFil: Samper, Sofia. Hospital Universitario Miguel Servet; Españ

Automatic Assessment of the 2-Minute Walk Distance for Remote Monitoring of People with Multiple Sclerosis

The aim of this study was to investigate the feasibility of automatically assessing the 2-Minute Walk Distance (2MWD) for monitoring people with multiple sclerosis (pwMS). For 154 pwMS, MS-related clinical outcomes as well as the 2MWDs as evaluated by clinicians and derived from accelerometer data were collected from a total of 323 periodic clinical visits. Accelerometer data from a wearable device during 100 home-based 2MWD assessments were also acquired. The error in estimating the 2MWD was validated for walk tests performed at hospital, and then the correlation (r) between clinical outcomes and home-based 2MWD assessments was evaluated. Robust performance in estimating the 2MWD from the wearable device was obtained, yielding an error of less than 10% in about two-thirds of clinical visits. Correlation analysis showed that there is a strong association between the actual and the estimated 2MWD obtained either at hospital (r = 0.71) or at home (r = 0.58). Furthermore, the estimated 2MWD exhibits moderate-to-strong correlation with various MS-related clinical outcomes, including disability and fatigue severity scores. Automatic assessment of the 2MWD in pwMS is feasible with the usage of a consumer-friendly wearable device in clinical and non-clinical settings. Wearable devices can also enhance the assessment of MS-related clinical outcomes

Using smartphones and wearable devices to monitor behavioural changes during COVID-19

We aimed to explore the utility of the recently developed open-source mobile health platform RADAR-base as a toolbox to rapidly test the effect and response to NPIs aimed at limiting the spread of COVID-19. We analysed data extracted from smartphone and wearable devices and managed by the RADAR-base from 1062 participants recruited in Italy, Spain, Denmark, the UK, and the Netherlands. We derived nine features on a daily basis including time spent at home, maximum distance travelled from home, maximum number of Bluetooth-enabled nearby devices (as a proxy for physical distancing), step count, average heart rate, sleep duration, bedtime, phone unlock duration, and social app use duration. We performed Kruskal-Wallis tests followed by post-hoc Dunns tests to assess differences in these features among baseline, pre-, and during-lockdown periods. We also studied behavioural differences by age, gender, body mass index (BMI), and educational background. We were able to quantify expected changes in time spent at home, distance travelled, and the number of nearby Bluetooth-enabled devices between pre- and during-lockdown periods. We saw reduced sociality as measured through mobility features, and increased virtual sociality through phone usage. People were more active on their phones, spending more time using social media apps, particularly around major news events. Furthermore, participants had lower heart rate, went to bed later, and slept more. We also found that young people had longer homestay than older people during lockdown and fewer daily steps. Although there was no significant difference between the high and low BMI groups in time spent at home, the low BMI group walked more. RADAR-base can be used to rapidly quantify and provide a holistic view of behavioural changes in response to public health interventions as a result of infectious outbreaks such as COVID-19

The utility of wearable devices in assessing ambulatory impairments of people with multiple sclerosis in free-living conditions

Background and objectives Multiple sclerosis (MS) is a progressive inflammatory and neurodegenerative disease of the central nervous system affecting over 2.5 million people globally. In-clinic six-minute walk test (6MWT) is a widely used objective measure to evaluate the progression of MS. Yet, it has limitations such as the need for a clinical visit and a proper walkway. The widespread use of wearable devices capable of depicting patients’ activity profiles has the potential to assess the level of MS-induced disability in free-living conditions. Methods In this work, we extracted 96 features in different temporal granularities (from minute-level to day-level) from wearable data and explored their utility in estimating 6MWT scores in a European (Italy, Spain, and Denmark) MS cohort of 337 participants over an average of 10 months’ duration. We combined these features with participants’ demographics using three regression models including elastic net, gradient boosted trees and random forest. In addition, we quantified the individual feature's contribution using feature importance in these regression models, linear mixed-effects models, generalized estimating equations, and correlation-based feature selection (CFS). Results The results showed promising estimation performance with R2 of 0.30, which was derived using random forest after CFS. This model was able to distinguish the participants with low disability from those with high disability. Furthermore, we observed that the minute-level (≤ 8 minutes) step count, particularly those capturing the upper end of the step count distribution, had a stronger association with 6MWT. The use of a walking aid was indicative of ambulatory function measured through 6MWT. Conclusions This study demonstrates the utility of wearables devices in assessing ambulatory impairments in people with MS in free-living conditions and provides a basis for future investigation into the clinical relevance

Walking-related digital mobility outcomes as clinical trial endpoint measures: protocol for a scoping review

Introduction Advances in wearable sensor technology now enable frequent, objective monitoring of real-world walking. Walking-related digital mobility outcomes (DMOs), such as real-world walking speed, have the potential to be more sensitive to mobility changes than traditional clinical assessments. However, it is not yet clear which DMOs are most suitable for formal validation. In this review, we will explore the evidence on discriminant ability, construct validity, prognostic value and responsiveness of walking-related DMOs in four disease areas: Parkinson’s disease, multiple sclerosis, chronic obstructive pulmonary disease and proximal femoral fracture. Methods and analysis Arksey and O’Malley’s methodological framework for scoping reviews will guide study conduct. We will search seven databases (Medline, CINAHL, Scopus, Web of Science, EMBASE, IEEE Digital Library and Cochrane Library) and grey literature for studies which (1) measure differences in DMOs between healthy and pathological walking, (2) assess relationships between DMOs and traditional clinical measures, (3) assess the prognostic value of DMOs and (4) use DMOs as endpoints in interventional clinical trials. Two reviewers will screen each abstract and full-text manuscript according to predefined eligibility criteria. We will then chart extracted data, map the literature, perform a narrative synthesis and identify gaps. Ethics and dissemination As this review is limited to publicly available materials, it does not require ethical approval. This work is part of Mobilise-D, an Innovative Medicines Initiative Joint Undertaking which aims to deliver, validate and obtain regulatory approval for DMOs. Results will be shared with the scientific community and general public in cooperation with the Mobilise-D communication team. Registration Study materials and updates will be made available through the Center for Open Science’s OSFRegistry (https://osf.io/k7395)

Autonomic response to walk tests is useful for assessing outcome measures in people with multiple sclerosis

Objective: The aim of this study was to evaluate the association between changes in the autonomic control of cardiorespiratory system induced by walk tests and outcome measures in people with Multiple Sclerosis (pwMS).Methods: Electrocardiogram (ECG) recordings of 148 people with Relapsing-Remitting MS (RRMS) and 58 with Secondary Progressive MS (SPMS) were acquired using a wearable device before, during, and after walk test performance from a total of 386 periodical clinical visits. A subset of 90 participants repeated a walk test at home. Various MS-related symptoms, including fatigue, disability, and walking capacity were evaluated at each clinical visit, while heart rate variability (HRV) and ECG-derived respiration (EDR) were analyzed to assess autonomic nervous system (ANS) function. Statistical tests were conducted to assess differences in ANS control between pwMS grouped based on the phenotype or the severity of MS-related symptoms. Furthermore, correlation coefficients (r) were calculated to assess the association between the most significant ANS parameters and MS-outcome measures.Results: People with SPMS, compared to RRMS, reached higher mean heart rate (HRM) values during walk test, and larger sympathovagal balance after test performance. Furthermore, pwMS who were able to adjust their HRM and ventilatory values, such as respiratory rate and standard deviation of the ECG-derived respiration, were associated with better clinical outcomes. Correlation analyses showed weak associations between ANS parameters and clinical outcomes when the Multiple Sclerosis phenotype is not taken into account. Blunted autonomic response, in particular HRM reactivity, was related with worse walking capacity, yielding r = 0.36 r = 0.29 (RRMS) and r > 0.5 (SPMS). A positive strong correlation r > 0.7 r > 0.65 between cardiorespiratory parameters derived at hospital and at home was also found.Conclusion: Autonomic function, as measured by HRV, differs according to MS phenotype. Autonomic response to walk tests may be useful for assessing clinical outcomes, mainly in the progressive stage of MS. Participants with larger changes in HRM are able to walk longer distance, while reduced ventilatory function during and after walk test performance is associated with higher fatigue and disability severity scores. Monitoring of disorder severity could also be feasible using ECG-derived cardiac and respiratory parameters recorded with a wearable device at home