Journal of neuromuscular diseases最新文献

Background: Myotonic Dystrophy type 1 (DM1) is a slowly progressive hereditary neuromuscular disorder affecting several organ systems including the musculoskeletal system.

Objective: To examine the effects of rehabilitation technology on arm and hand function in the assessment and treatment of adults with DM1 with moderate to severe muscle impairment.

Methods: A single subject experimental design study (SSED) with 6 participants. The assessments were done weekly through remote study assessments using the video-conference system Whereby^®. Participants performed the nine-hole peg test (NHPT), active range of motion (AROM) of the shoulder and patient reported outcome measures (PROMS). Three participants also measured grip and pinch strength and performed the Nut and Bolt task. The intervention was a three-week in-patient rehabilitation stay with the use of rehabilitation technology for exercising arm and hand function. Exercises were performed in AMADEO and the ArmeoSenso. The participants exercised the upper extremities for 30 min 5 times a week.

Results: Improvement on the NHPT test on the dominant hand were found for five of the six participants. Three of six improved on the non-dominant hand and in AROM. Two of the three participants that measured pinch and grip strength improved, and all three improved on the Nut and Bolt task. Self- reported function, myotonia and fatigue remained stable. All participants were able to participate in video assessments.

Conclusions: Impairment in arm- and hand function affects independence in people with DM1.Our findings suggest that exercising arm- and hand using rehabilitation technology may have a positive effect on function measured by dexterity, strength, and movement in DM1. There is a need to study the effect of exercise on arm- and hand function in DM1 in larger studies. The use of video-consultations can be a supplement in assessment of people with neuromuscular conditions in research and clinical practise.

Up to 6% of the global population is estimated to be affected by one of about 10,000 distinct rare diseases (RDs). RDs are, to this day, often not understood, and thus, patients are heavily underserved. Most RD studies are chronically underfunded, and research faces inherent difficulties in analyzing scarce data. Furthermore, the creation and analysis of representative datasets are often constrained by stringent data protection regulations, such as the EU General Data Protection Regulation. This review examines the potential of federated learning (FL) as a privacy-by-design approach to training machine learning on distributed datasets while ensuring data privacy by maintaining the local patient data and only sharing model parameters, which is particularly beneficial in the context of sensitive data that cannot be collected in a centralized manner. FL enhances model accuracy by leveraging diverse datasets without compromising data privacy. This is particularly relevant in rare diseases, where heterogeneity and small sample sizes impede the development of robust models. FL further has the potential to enable the discovery of novel biomarkers, enhance patient stratification, and facilitate the development of personalized treatment plans. This review illustrates how FL can facilitate large-scale, cross-institutional collaboration, thereby enabling the development of more accurate and generalizable models for improved diagnosis and treatment of rare diseases. However, challenges such as non-independently distributed data and significant computational and bandwidth requirements still need to be addressed. Future research must focus on applying FL technology for rare disease datasets while exploring standardized protocols for cross-border collaborations that can ultimately pave the way for a new era of privacy-preserving and distributed data-driven rare disease research.

Artificial intelligence is the future of clinical practice and is increasingly utilized in medical management and clinical research. The release of ChatGPT3 in 2022 brought generative AI to the headlines and rekindled public interest in software agents that would complete repetitive tasks and save time. Artificial intelligence/machine learning underlies applications and devices which are assisting clinicians in the diagnosis, monitoring, formulation of prognosis, and treatment of patients with a spectrum of neuromuscular diseases. However, these applications have remained in the research sphere, and neurologists as a specialty are running the risk of falling behind other clinical specialties which are quicker to embrace these new technologies. While there are many comprehensive reviews on the use of artificial intelligence/machine learning in medicine, our aim is to provide a simple and practical primer to educate clinicians on the basics of machine learning. This will help clinicians specializing in neuromuscular and electrodiagnostic medicine to understand machine learning applications in nerve and muscle ultrasound, MRI imaging, electrical impendence myography, nerve conductions and electromyography and clinical cohort studies, and the limitations, pitfalls, regulatory and ethical concerns, and future directions. The question is not whether artificial intelligence/machine learning will change clinical practice, but when and how. How future neurologists will look back upon this period of transition will be determined not by how much changed or by how fast clinicians embraced this change but by how much patient outcomes were improved.

Neuromuscular diseases (NMDs), in their phenotypic heterogeneity, share quite invariably common issues that involve several clinical and socio-economical aspects, needing a deep critical analysis to develop better management strategies. From diagnosis to treatment and follow-up, the development of technological solutions can improve the detection of several critical aspects related to the diseases, addressing both the met and unmet needs of clinicians and patients. Among several aspects of the digital transformation of health and care, this congress expands what has been learned from previous congresses editions on applicability and usefulness of technological solutions in NMDs. In particular the focus on new solutions for remote monitoring provide valuable insights to increase disease-specific knowledge and trigger prompt decision-making. In doing that, several perspectives from different areas of expertise were shared and discussed, pointing out strengths and weaknesses on the current state of the art on topic, suggesting new research lines to advance technology in this specific clinical field.

Rationale: Myasthenia gravis (MG) is a rare, chronic neurological disorder leading to fluctuating muscle weakness and potentially life-threatening crises. Patients often require life-long specialized treatment, but timely interventions are frequently hindered by the limited availability of specialists. Telemedical solutions at specialized centers enabling patient-physician interaction hold promise in bridging this gap, but are not yet available for MG. We developed 'MyaLink,' a remote monitoring platform tailored for MG, and outline the study design assessing the platform and clinical outcomes regarding telemedical intervention. Additionally, we present study results on care-related aspects in MG prior to telemedical intervention to identify challenges in the current care provision process.

Design: The platform comprises a patient app and a physician portal, enabling systematic symptom monitoring using data from patient-reported outcome measures (PROMs), coupled devices and a communication module. The randomized controlled study included 45 study participants (SP) over a 12-weeks period, including a group receiving standard care (15 MG patients) and a group with additional telemedical treatment (30 MG patients) including assessment of PROMs, wearable data collection and telemedical check-ups. Questions regarding care-related aspects were assessed at baseline visit.

Results: Many SP (N = 33, 73.3%) communicate with the physician managing their MG via email. 73.3% (N = 33) of SP identify areas for improvement in their MG care including symptom monitoring (N = 23, 69.7%), specialist appointment availability (N = 22, 66.7%), medication (N = 22, 66.7%) and specialist accessibility (N = 20, 60.6%). Additionally, 73.3% (N = 33) reported that the effort required to manage their MG was high.

Conclusion: Our results emphasize the high demand of affected MG patients for continuous telemedicine services. MyaLink can provide such a service through personalized support based on the exchange of health data. Telemedicine solutions such as MyaLink promise to improve myasthenia care by providing accessible, patient-centred care that enables early detection of worsening symptoms and non-response to treatment.

Trial registration: The study was registered under DRKS00029907 on August 19, 2022.

Background: Telemedicine, the application of those information technologies to remotely provide health services either for synchronously catching or asynchronous monitoring patient medical data, has shown a growing and widespread application in several chronic diseases, and, especially during and after COVID-19 pandemics, also in neuromuscular diseases.

Objective: this review aims at providing an updated overview on the application of telemedicine and telemonitoring tools in neuromuscular diseases, in clinical practice, research and trials.

Methods: a literature search was conducted on PubMed using keywords regarding telemedicine applications and several neuromuscular diseases, including papers up to May 2024.

Conclusions: several tools have been developed and tested in myopathies, motoneuron diseases, myasthenia gravis and peripheral neuropathies, providing monitoring, assistance, and rehabilitation protocols for such frail population, for which obtaining real life data remotely can represent a concrete advantage in clinical trials and clinical practice. Although several barriers in the implementation of telemedicine in NMD still need to be overcome, there is evidence for both clinicians and patients showing positive acceptance and satisfaction on the use of remote supports, regarding them as confident outcome measures of quality of life in view of a more general concept of e-health solutions in routine medical care.

Background: The clinical course of Spinal Muscular Atrophy (SMA) has been transformed by new disease-modifying therapies (DMT). Before DMT, the clinical course of SMA was marked by an inflection point between developmental improvement and degenerative functional losses. The well-established SMA classification by "type" was based upon the age and functional level at which this inflection point manifested. Following DMT, the natural history of SMA has evolved. The evolution of the SMA clinical course following DMT thus necessitates an updated means to characterize individuals with SMA.

Objective: To address both clinical and research needs, an updated assessment should target meaningful function; apply broadly across the range of SMA; maximize the granularity of functional tiers with minimal compromise of reliability; require minimal or no specific training; and be validated with measurable consistency between both naïve and experienced clinicians, and between these clinicians and members of the SMA community.

Methods/design: Development of the Functional Ability Scale for Evolving SMA (EVOLVE-SMA) proceeded as an iterative scale creation and refinement process using retrospective cohorts (for design, reliability, and validity) followed by prospective assessments of real-world feasibility and reliability.

Results: Excellent interrater reliability (ICC >0.9, p < 0.001) was established between expert and novice clinicians (physician and physical therapist) and clinicians versus SMA community members.

Conclusions: EVOLVE-SMA is a tiered evaluation of function applicable to the new DMT-treated era of SMA. It is a simple, granular, and reliable means to assess meaningful functions that will have value to research, resource allocation, and individual clinical care.

Objective: The objective of this scoping review was to map the body of existing literature regarding muscle strength, balance and mobility limitations in oculopharyngeal muscular dystrophy (OPMD).

Methods: The Joanna Briggs Institute's methodology was followed. All original research including participants with OPMD 18 years or older and describing muscle strength, balance and/or mobility limitations using clinical outcome assessments retrieved from the PubMed, MEDLINE, PEDro, Cochrane Database of Systematic Reviews, and CINHAL Plus databases (searched before January 30^th, 2023) were included.

Results: Titles and abstracts from 416 studies were screened, and 54 articles were fully reviewed. Proximal upper and lower limb muscle strength were assessed in majority (92.6% of studies). Lack of common methodology made conclusions on their prevalence and severity difficult. Regarding balance, no performance outcome measures was retrieved. 29.6 to 63.0% of studies addressed mobility limitations; only two prospective longitudinal studies were retrieved, and two studies used reference values to assess impairments/limitations severity.

Conclusion: This scoping review highlights the current knowledge on muscle strength, balance and mobility limitations in OPMD. A lack of balance and complete mobility assessments, and OPMD-specific questionnaire for motor impairments or mobility limitations are noted. Future studies should focus on using standardized clinical outcome assessments to better document these impairments/limitations.

Numerous potential treatments are being developed for facioscapulohumeral muscular dystrophy (FSHD). Project Mercury was initiated to overcome challenges that could slow or prevent effective therapies from widespread availability to patients. It is important that upcoming trials include trial sites from different countries. We share our lessons learnt in clinical trials to assist inexperienced sites to become eligible for upcoming clinical trials. To become an eligible site, several key elements need to be in place such as personnel, facilities, and accessible patient populations. Clinical trial networks, patient advocacy groups and patient registries can support new sites in establishing these elements. As the preparation, execution and close-out of clinical trials generally involve the same steps every time, it is recommended to create and follow a trial roadmap. Most clinical trials are sponsor-initiated and involve working closely with the sponsor and vendors. It is therefore important to understand each other perspectives and goals for each trial. Once a drug receives regulatory approval and becomes available for market use new challenges arise such as patient reimbursement and phase 4 surveillance of the patients. In summary, we are at a pivotal time for FSHD and other rare neuromuscular disorders with the development of new disease modifying therapies. It is vital that as many sites as possible can participate in upcoming trials.