E-health and multiple sclerosis

Interventions to minimise hospital winter pressures related to discharge planning and integrated care: a rapid mapping review of UK evidence

Background

Winter pressures are a familiar phenomenon within the National Health Service and represent the most extreme of many regular demands placed on health and social care service provision. This review focuses on a part of the pathway that is particularly problematic: the discharge process from hospital to social care and the community. Although studies of discharge are plentiful, we identified a need to focus on identifying interventions and initiatives that are a specific response to 'winter pressures'. This mapping review focuses on interventions or initiatives in relation to hospital winter pressures in the United Kingdom with either discharge planning to increase smart discharge (both a reduction in patients waiting to be discharged and patients being discharged to the most appropriate place) and/or integrated care.

Methods

We conducted a mapping review of United Kingdom evidence published 2018-22. Initially, we searched MEDLINE, Health Management Information Consortium, Social Care Online, Social Sciences Citation Index and the King's Fund Library to find relevant interventions in conjunction with winter pressures. From these interventions we created a taxonomy of intervention types and a draft map. A second broader stage of searching was then undertaken for named candidate interventions on Google Scholar (Google Inc., Mountain View, CA, USA). For each taxonomy heading, we produced a table with definitions, findings from research studies, local initiatives and systematic reviews and evidence gaps.

Results

The taxonomy developed was split into structural, changing staff behaviour, changing community provision, integrated care, targeting carers, modelling and workforce planning. The last two categories were excluded from the scope. Within the different taxonomy sections we generated a total of 41 headings. These headings were further organised into the different stages of the patient pathway: hospital avoidance, alternative delivery site, facilitated discharge and cross-cutting. The evidence for each heading was summarised in tables and evidence gaps were identified.

Conclusions

Few initiatives identified were specifically identified as a response to winter pressures. Discharge to assess and hospital at home interventions are heavily used and well supported by the evidence but other responses, while also heavily used, were based on limited evidence. There is a lack of studies considering patient, family and provider needs when developing interventions aimed at improving delayed discharge. Additionally, there is a shortage of studies that measure the longer-term impact of interventions. Hospital avoidance and discharge planning are whole-system approaches. Considering the whole health and social care system is imperative to ensure that implementing an initiative in one setting does not just move the problem to another setting.

Limitations

Time limitations for completing the review constrained the period available for additional searches. This may carry implications for the completeness of the evidence base identified.

Future work

Further research to consider a realist review that views approaches across the different sectors within a whole system evaluation frame.

Funding

This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: NIHR130588) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 31. See the NIHR Funding and Awards website for further award information.

A Review on the Feasibility and Efficacy of Home-Based Cognitive Remediation in People with Multiple Sclerosis

Cognitive impairment affects 34-65% of People with Multiple Sclerosis (PwMS), significantly impacting their quality of life. Clinicians routinely address cognitive deficits with in-clinic neuro-behavioural interventions, but accessibility issues exist. Given these challenges, coupled with the lifelong need for continuous assistance in PwMS, researchers have underscored the advantageous role of telerehabilitation in addressing these requirements. Nonetheless, the feasibility and efficacy of home-based cognitive remediation remain to be firmly established. In this narrative review, we aimed to investigate the feasibility and efficacy of digital telerehabilitation for cognition in PwMS. Thirteen relevant studies were identified and carefully assessed. Regarding the feasibility of cognitive telerehabilitation, evidence shows adherence rates are generally good, although, surprisingly, not all studies reported measures of compliance with the cognitive training explored. Considering the efficacy of rehabilitative techniques on cognitive performance in PwMS, findings are generally inconsistent, with only one study reporting uniformly positive results. A range of methodological limitations are reported as potential factors contributing to the variable results. Future research must address these challenges, as more rigorous studies are required to draw definitive conclusions regarding the efficacy of home-based cognitive remediation in PwMS. Researchers must prioritise identifying optimal intervention approaches and exploring the long-term effects of telerehabilitation.

Exploring the Major Barriers to Physical Activity in Persons With Multiple Sclerosis: Observational Longitudinal Study

BACKGROUND

Physical activity (PA) represents a low-cost and readily available means of mitigating multiple sclerosis (MS) symptoms and alleviating the disease course. Nevertheless, persons with MS engage in lower levels of PA than the general population.

OBJECTIVE

This study aims to enhance the understanding of the barriers to PA engagement in persons with MS and to evaluate the applicability of the Barriers to Health Promoting Activities for Disabled Persons (BHADP) scale for assessing barriers to PA in persons with MS, by comparing the BHADP score with self-reported outcomes of fatigue, depression, self-efficacy, and health-related quality of life, as well as sensor-measured PA.

METHODS

Study participants (n=45; median age 46, IQR 40-51 years; median Expanded Disability Status Scale score 4.5, IQR 3.5-6) were recruited among persons with MS attending inpatient neurorehabilitation. They wore a Fitbit Inspire HR (Fitbit Inc) throughout their stay at the rehabilitation clinic (phase 1; 2-4 wk) and for the 4 following weeks at home (phase 2; 4 wk). Sensor-based step counts and cumulative minutes in moderate to vigorous PA were computed for the last 7 days at the clinic and at home. On the basis of PA during the last 7 end-of-study days, we grouped the study participants as active (≥10,000 steps/d) and less active (<10,000 steps/d) to explore PA barriers compared with PA level. PA barriers were repeatedly assessed through the BHADP scale. We described the relevance of the 18 barriers of the BHADP scale assessed at the end of the study and quantified their correlations with the Spearman correlation test. We evaluated the associations of the BHADP score with end-of-study reported outcomes of fatigue, depression, self-efficacy, and health-related quality of life with multivariable regression models. We performed separate regression analyses to examine the association of the BHADP score with different sensor-measured outcomes of PA.

RESULTS

The less active group reported higher scores for the BHADP items Feeling what I do doesn't help, No one to help me, and Lack of support from family/friends. The BHADP items Not interested in PA and Impairment were positively correlated. The BHADP score was positively associated with measures of fatigue and depression and negatively associated with self-efficacy and health-related quality of life. The BHADP score showed an inverse relationship with the level of PA measured but not when dichotomized according to the recommended PA level thresholds.

CONCLUSIONS

The BHADP scale is a valid and well-adapted tool for persons with MS because it reflects common MS symptoms such as fatigue and depression, as well as self-efficacy and health-related quality of life. Moreover, decreases in PA levels are often related to increases in specific barriers in the lives of persons with MS and should hence be addressed jointly in health care management.

Acceptability of a digital health application to empower persons with multiple sclerosis with moderate to severe disability: single-arm prospective pilot study

BACKGROUND

Many persons with multiple sclerosis (pwMS) desire to learn how health behaviour changes (e.g., dietary adjustments, physical activity, improvements in stress management) might help them manage their disease. Previous research has shown that certain health behaviour changes can improve quality of life (QoL), fatigue and other MS outcomes. Digital health applications may be well suited to deliver relevant health behavioural interventions because of their accessibility and flexibility. The digital health application "levidex" was designed to facilitate health behaviour change by offering evidence-based patient information and cognitive-behavioural therapy techniques to pwMS. By doing so, levidex aims to improve QoL and MS symptoms such as fatigue and mental health.

OBJECTIVES

A previous study reported on the development of levidex; this non-randomised pilot study examined the feasibility (practicability and acceptability) of levidex in pwMS with moderate to severe disability. Furthermore, the intervention's impact on empowerment, stress management, and relevant health behaviours (e.g., dietary behaviour, physical activity) was explored.

METHODS

levidex was originally developed for newly diagnosed pwMS in the first year after diagnosis and eventually modified to offer access to pwMS with moderate to severe disability. Participants (n = 43) with an Expanded Disability Status Scale between 3.5 and 7.5 and a disease duration of more than one year were eligible to participate. The intervention was used over a period of six months with measurement time points at baseline, month 3 and month 6.

RESULTS

Out of 38 participants who completed the six-month intervention period, 18 (47.4%) completed all 16 modules and 9 (23.7%) reached modules 13-16, the long-term maintenance part of levidex. Participants rated levidex positively in terms of practicability and acceptability and had only few points of criticism such as to include more physical exercise routine suggestions suitable for participants with severe impairment. Data on secondary endpoints showed no significant changes.

CONCLUSION

This pilot study provided evidence for the practicability and acceptability of levidex, a digital health application designed to facilitate health behaviour change in pwMS with moderate to severe disability. Adequately powered randomised controlled studies with longer follow-up periods are needed to clarify the benefit of levidex in pwMS with moderate to severe disability.

TRIAL REGISTRATION

German Clinical Trials Register (DRKS) DRKS00032667 (14/09/2023); Retrospectively registered.

A systematic review of the application of machine-learning algorithms in multiple sclerosis

INTRODUCTION

The applications of artificial intelligence, and in particular automatic learning or "machine learning" (ML), constitute both a challenge and a great opportunity in numerous scientific, technical, and clinical disciplines. Specific applications in the study of multiple sclerosis (MS) have been no exception, and constitute an area of increasing interest in recent years.

OBJECTIVE

We present a systematic review of the application of ML algorithms in MS.

MATERIALS AND METHODS

We used the PubMed search engine, which allows free access to the MEDLINE medical database, to identify studies including the keywords "machine learning" and "multiple sclerosis." We excluded review articles, studies written in languages other than English or Spanish, and studies that were mainly technical and did not specifically apply to MS. The final selection included 76 articles, and 38 were rejected.

CONCLUSIONS

After the review process, we established 4 main applications of ML in MS: 1) classifying MS subtypes; 2) distinguishing patients with MS from healthy controls and individuals with other diseases; 3) predicting progression and response to therapeutic interventions; and 4) other applications. Results found to date have shown that ML algorithms may offer great support for health professionals both in clinical settings and in research into MS.

Artificial Intelligence and Multiple Sclerosis: Up-to-Date Review

Multiple sclerosis (MS) remains a challenging neurological disorder for the clinician in terms of diagnosis and management. The growing integration of AI-based algorithms in healthcare offers a golden opportunity for clinicians and patients with MS. AI models are based on statistical analyses of large quantities of data from patients including "demographics, genetics, clinical and radiological presentation." These approaches are promising in the quest for greater diagnostic accuracy, tailored management plans, and better prognostication of disease. The use of AI in multiple sclerosis represents a paradigm shift in disease management. With ongoing advancements in AI technologies and the increasing availability of large-scale datasets, the potential for further innovation is immense. As AI continues to evolve, its integration into clinical practice will play a vital role in improving diagnostics, optimizing treatment strategies, and enhancing patient outcomes for MS. This review is about conducting a literature review to identify relevant studies on AI applications in MS. Only peer-reviewed studies published in the last four years have been selected. Data related to AI techniques, advancements, and implications are extracted. Through data analysis, key themes and tendencies are identified. The review presents a cohesive synthesis of the current state of AI and MS, highlighting potential implications and new advancements.

One-year prediction of cognitive decline following cognitive-stimulation from real-world data

Clinical evidence based on real-world data (RWD) is accumulating exponentially providing larger sample sizes available, which demand novel methods to deal with the enhanced heterogeneity of the data. Here, we used RWD to assess the prediction of cognitive decline in a large heterogeneous sample of participants being enrolled with cognitive stimulation, a phenomenon that is of great interest to clinicians but that is riddled with difficulties and limitations. More precisely, from a multitude of neuropsychological Training Materials (TMs), we asked whether was possible to accurately predict an individual's cognitive decline one year after being tested. In particular, we performed longitudinal modelling of the scores obtained from 215 different tests, grouped into 29 cognitive domains, a total of 124,610 instances from 7902 participants (40% male, 46% female, 14% not indicated), each performing an average of 16 tests. Employing a machine learning approach based on ROC analysis and cross-validation techniques to overcome overfitting, we show that different TMs belonging to several cognitive domains can accurately predict cognitive decline, while other domains perform poorly, suggesting that the ability to predict decline one year later is not specific to any particular domain, but is rather widely distributed across domains. Moreover, when addressing the same problem between individuals with a common diagnosed label, we found that some domains had more accurate classification for conditions such as Parkinson's disease and Down syndrome, whereas they are less accurate for Alzheimer's disease or multiple sclerosis. Future research should combine similar approaches to ours with standard neuropsychological measurements to enhance interpretability and the possibility of generalizing across different cohorts.

Large-scale cross-sectional online survey on patient-neurologist communication, burden of disease assessment and disease monitoring in people with multiple sclerosis

Background

Management of multiple sclerosis (MS) requires a high level of communication between health care professionals (HCPs) and people with MS (pwMS) including profound investigation and discussion of symptoms to identify therapeutic needs. For treatment decisions, monitoring of disease activity is important, in this respect self-monitoring devices and apps, as well as magnetic resonance imaging are important tools.

Methods

MS Perspectives is a cross-sectional online survey conducted in Germany which was designed to collect data, among others, on the communication between pwMS and HCPs regarding treatment goals, symptom assessment, usage of devices and apps to self-monitor health functions, as well as to identify patients' attitude toward the role of magnetic resonance imaging (MRI). Between December 2021 and February 2022, 4,555 pwMS completed the survey.

Results

In total, 63.7% of participants reported that treatment goals have been discussed with their HCPs. Symptoms worsening in the past 12 months independent of relapses was more often reported by pwMS than inquired by HCPs, according to patients' report. Devices or apps for health monitoring were used by less than half of participants. Frequency of MRI controls was much lower in participants with longer compared to shorter disease duration (47.5 vs. 86.3%). The proportion of patients with annual or semiannual scans was highest among pwMS receiving infusion therapy (93.5%), followed by oral medication (82.5%) and injectables (73.4%), and lowest for pwMS without immunotherapy (58.2%).

Conclusion

MS Perspectives identified a rather low patient involvement regarding treatment goals and symptom assessment in clinical practice. Regarding this and our findings for health self-monitoring and MRI usage, strategies for improving patient-HCP communication and disease monitoring may be considered.

Development and usability testing of your MS questionnaire: A patient-based digital tool to monitor symptoms of multiple sclerosis

Objectives

We describe the development of Your Multiple Sclerosis Questionnaire and present the real-world usability testing results of Your Multiple Sclerosis Questionnaire.

Methods

The Your Multiple Sclerosis Questionnaire tool was developed in four stages to collect feedback from people living with MS (plwMS), patient organizations, and clinicians on content, format, and applicability. To assess its usability, 13 clinicians across 7 countries completed an online survey after using the tool with plwMS in a total of 261 consultations from September, 2020 to July, 2021.

Results

The initial Your Multiple Sclerosis Questionnaire version was based on findings from previous research developing MSProDiscuss™, a clinician-completed tool. Subsequently, insights from plwMS obtained during cognitive debriefing, patient councils and advisory boards led to changes including the addition of mood and sexual problems and the definition of relapse. All 13 clinicians completed the individual survey, whereas 10 clinicians completed the final survey. Clinicians "strongly agreed" or "agreed" that Your Multiple Sclerosis Questionnaire was easy to use and understand (98.5%; 257/261 patient consultations). The clinicians were willing to use the tool again with the same patient (98.1%; 256/261 patient consultations). All clinicians who completed the final survey (100%; 10/10) reported the tool to have a positive influence on their clinical practice, helped patients engage with their MS, facilitated discussion with patients, and complemented neurological assessment.

Conclusion

Your Multiple Sclerosis Questionnaire benefits both plwMS and clinicians by facilitating a structured discussion and engaging the plwMS to self-monitor and self-manage. Your Multiple Sclerosis Questionnaire is compatible with telemedicine practice and integration of the tool into electronic health records would enable tracking of the disease evolution and individual monitoring of MS symptoms over time.

Feasibility and scalability of a fitness tracker study: Results from a longitudinal analysis of persons with multiple sclerosis

Background

Consumer-grade fitness trackers offer exciting opportunities to study persons with chronic diseases in greater detail and in their daily-life environment. However, attempts to bring fitness tracker measurement campaigns from tightly controlled clinical environments to home settings are often challenged by deteriorating study compliance or by organizational and resource limitations.

Objectives

By revisiting the study design and patient-reported experiences of a partly remote study with fitness trackers (BarKA-MS study), we aimed to qualitatively explore the relationship between overall study compliance and scalability. On that account, we aimed to derive lessons learned on strengths, weaknesses, and technical challenges for the conduct of future studies.

Methods

The two-phased BarKA-MS study employed Fitbit Inspire HR and electronic surveys to monitor physical activity in 45 people with multiple sclerosis in a rehabilitation setting and in their natural surroundings at home for up to 8 weeks. We examined and quantified the recruitment and compliance in terms of questionnaire completion and device wear time. Furthermore, we qualitatively evaluated experiences with devices according to participants' survey-collected reports. Finally, we reviewed the BarKA-MS study conduct characteristics for its scalability according to the Intervention Scalability Assessment Tool checklist.

Results

Weekly electronic surveys completion reached 96%. On average, the Fitbit data revealed 99% and 97% valid wear days at the rehabilitation clinic and in the home setting, respectively. Positive experiences with the device were predominant: only 17% of the feedbacks had a negative connotation, mostly pertaining to perceived measurement inaccuracies. Twenty-five major topics and study characteristics relating to compliance were identified. They broadly fell into the three categories: "effectiveness of support measures", "recruitment and compliance barriers", and "technical challenges". The scalability assessment revealed that the highly individualized support measures, which contributed greatly to the high study compliance, may face substantial scalability challenges due to the strong human involvement and limited potential for standardization.

Conclusion

The personal interactions and highly individualized participant support positively influenced study compliance and retention. But the major human involvement in these support actions will pose scalability challenges due to resource limitations. Study conductors should anticipate this potential compliance-scalability trade-off already in the design phase.

Wearable Sensors Applied in Movement Analysis

Recent advances in the miniaturization of electronics have resulted in sensors whose sizes and weights are such that they can be attached to living systems without interfering with their natural movements and behaviors [...].

MSProDiscuss™ Clinical Decision Support Tool for Identifying Multiple Sclerosis Progression

This article describes the rationale for the development of the MSProDiscuss™ clinical decision support (CDS) tool, its development, and insights into how it can help neurologists improve care for patients with multiple sclerosis (MS). MS is a progressive disease characterized by heterogeneous symptoms and variable disease course. There is growing consensus that MS exists on a continuum, with overlap between relapsing–remitting and secondary progressive phenotypes. Evidence demonstrates that neuroaxonal loss occurs from the outset, that progression can occur independent of relapse activity, and that continuous underlying pathological processes may not be reflected by inflammatory activity indicative of the patient’s immune response. Early intervention can benefit patients, and there is a need for a tool that assists physicians in rapidly identifying subtle signs of MS progression. MSProDiscuss, developed with physicians and patients, facilitates a structured approach to patient consultations. It analyzes multidimensional data via an algorithm to estimate the likelihood of progression (the MSProDiscuss score), the contribution of various symptoms, and the impact of symptoms on daily living, enabling a more personalized approach to treatment and disease management. Data from CDS tools such as MSProDiscuss offer new insights into disease course and facilitate informed decision-making and a holistic approach to MS patient care.

Digital tools in allergy and respiratory care

Patient care in the allergy and respiratory fields is advancing rapidly, offering the possibility of the inclusion of a variety of digital tools that aim to improve outcomes of care. Impaired access to several health care facilities during the COVID-19 pandemic has considerably increased the appetite and need for the inclusion of e-health tools amongst end-users. Consequently, a multitude of different e-health tools have been launched worldwide with various registration and access options, and with a wide range of offered benefits. From the perspective of both patients and healthcare providers (HCPs), as well as from a legal and device-related perspective, several features are important for the acceptance, effectiveness,and long-term use of e-health tools. Patients and physicians have different needs and expectations of how digital tools might be of help in the care pathway. There is a need for standardization by defining quality assurance criteria. Therefore, the Upper Airway Diseases Committee of the World Allergy Organization (WAO) has taken the initiative to define and propose criteria for quality, appeal, and applicability of e-health tools in the allergy and respiratory care fields from a patient, clinician, and academic perspective with the ultimate aim to improve patient health and outcomes of care.

Visual Search in Naturalistic Scenes Reveals Impaired Cognitive Processing Speed in Multiple Sclerosis

BACKGROUND

Standardized neuropsychological testing serves to quantify cognitive impairment in multiple sclerosis (MS) patients. However, the exact mechanism underlying the translation of cognitive dysfunction into difficulties in everyday tasks has remained unclear. To answer this question, we tested if MS patients with intact vs. impaired information processing speed measured by the Symbol Digit Modalities Test (SDMT) differ in their visual search behavior during ecologically valid tasks reflecting everyday activities.

METHODS

Forty-three patients with relapsing-remitting MS enrolled in an eye-tracking experiment consisting of a visual search task with naturalistic images. Patients were grouped into "impaired" and "unimpaired" according to their SDMT performance. Reaction time, accuracy and eye-tracking parameters were measured.

RESULTS

The groups did not differ regarding age, gender, and visual acuity. Patients with impaired SDMT (cut-off SDMT-z-score < -1.5) performance needed more time to find and fixate the target (q = 0.006). They spent less time fixating the target (q = 0.042). Impaired patients had slower reaction times and were less accurate (both q = 0.0495) even after controlling for patients' upper extremity function. Exploratory analysis revealed that unimpaired patients had higher accuracy than impaired patients particularly when the announced target was in unexpected location (p = 0.037). Correlational analysis suggested that SDMT performance is inversely linked to the time to first fixation of the target only if the announced target was in its expected location (r = -0.498, p = 0.003 vs. r = -0.212, p = 0.229).

CONCLUSION

Dysfunctional visual search behavior may be one of the mechanisms translating cognitive deficits into difficulties in everyday tasks in MS patients. Our results suggest that cognitively impaired patients search their visual environment less efficiently and this is particularly evident when top-down processes have to be employed.

Telemedicine as a strategic intervention for cognitive rehabilitation in MS patients during COVID-19

The recent COVID-19 pandemic has taken the lives of nearly 5.2 million up to now. With no definite treatment and considering close contact as the primary mode of transmission, telemedicine has emerged as an essential medical care platform. Virtual medical communications have offered clinicians the opportunity to visit and follow up on patients more efficiently during the lockdown. Not only has telemedicine improved multiple sclerosis (MS) patients’ health and quality of life during the pandemic, but it could also be used as a cost-effective platform for physical and cognitive MS rehabilitation programs. Cognitive impairment is a common problem among MS patients even at the initial phases of the disease. Rehabilitation training programs such as RehaCom, BrainHQ, Speed of Processing Training (PST), and COGNI-TRAcK have made great strides in improving a wide range of cognitive functions that MS patients are challenged with. Regarding the impact of COVID-19 on the cognitive aspects of MS patients, efforts to implement rehabilitation training applications have been increased. Web-based mobile applications, virtual visits, and telephone follow-ups are examples of such efforts. Having said that, limitations such as privacy, socioeconomic disparities, e-health literacy, study settings, and challenges of neurologic examinationss have been raised. Since most MS patients are young, all the beneficiaries are encouraged to embrace the research in the field to pave the road for more feasible and efficient ways of cognitive enhancement in MS patients.

An ID-Associated Application to Facilitate Patient-Tailored Management of Multiple Sclerosis

Despite improvements in diagnosis and treatment, multiple sclerosis (MS) is the leading neurological cause of disability in young adults. As a chronic disease, MS requires complex and challenging management. In this context, eHealth has gained an increasing relevance. Here, we aim to summarize beneficial features of a mobile app recently implemented in clinical MS routine as well as beyond MS. PatientConcept is a CE-certified, ID-associated multilingual software application allowing patients to record relevant health data without disclosing any identifying data. Patients can voluntarily share their health data with selected physicians. Since its implementation in 2018, about 3000 MS patients have used PatientConcept. Initially developed as a physician–patient communication platform, the app maps risk management plans of all current disease modifying therapies and thereby facilitates adherence to specified monitoring appointments. It also allows continuous monitoring of various PROs (Patient Reported Outcomes), enabling a broad overview of the disease course. In addition, various studies/projects currently assess monitoring, follow-up, diagnostics and telemetric evaluations of patients with other diseases beyond MS. Altogether, PatientConcept offers a broad range of possibilities to support physician–patient communication, implementation of risk management plans and assessment of PROs. It is a promising tool to facilitate patient-tailored management of MS and other chronic diseases.

Cross-Talk of the CNS With Immune Cells and Functions in Health and Disease

The immune system's role is much more than merely recognizing self vs. non-self and involves maintaining homeostasis and integrity of the organism starting from early development to ensure proper organ function later in life. Unlike other systems, the central nervous system (CNS) is separated from the peripheral immune machinery that, for decades, has been envisioned almost entirely as detrimental to the nervous system. New research changes this view and shows that blood-borne immune cells (both adaptive and innate) can provide homeostatic support to the CNS via neuroimmune communication. Neurodegeneration is mostly viewed through the lens of the resident brain immune populations with little attention to peripheral circulation. For example, cognition declines with impairment of peripheral adaptive immunity but not with the removal of microglia. Therapeutic failures of agents targeting the neuroinflammation framework (inhibiting immune response), especially in neurodegenerative disorders, call for a reconsideration of immune response contributions. It is crucial to understand cross-talk between the CNS and the immune system in health and disease to decipher neurodestructive and neuroprotective immune mechanisms for more efficient therapeutic strategies.

Multiple Sclerosis Patient Management During the COVID-19 Pandemic: Practical Recommendations From the Portuguese Multiple Sclerosis Study Group (GEEM)

The spread of the COVID-19 pandemic has imposed significant challenges on healthcare provision, requiring changes in the conventional patient management, particularly in chronic diseases like multiple sclerosis (MS). To increase patient safety and reduce the risk of infection, while ensuring an appropriate and regular follow-up, tele-medicine gained prominence as a valid alternative to face-to-face appointments. However, the urgency of the implementation and the lack of experience in most MS centers led to “ad hoc” and extremely diverse approaches, which now merit to be standardized and refined. Indeed, while tele-consultation cannot fully replace face-to-face visits, it certainly can, and will, be incorporated as part of the routine care of MS patients in the near future. Bearing this in mind, the Portuguese Multiple Sclerosis Study Group (GEEM) has developed a set of recommendations for the usage of tele-medicine in the management of MS patients, both during the pandemic and in the future. The consensus was obtained through a two-step modified Delphi methodology, resulting in 15 recommendations, which are detailed in the manuscript.

Machine Learning Use for Prognostic Purposes in Multiple Sclerosis

The course of multiple sclerosis begins with a relapsing-remitting phase, which evolves into a secondarily progressive form over an extremely variable period, depending on many factors, each with a subtle influence. To date, no prognostic factors or risk score have been validated to predict disease course in single individuals. This is increasingly frustrating, since several treatments can prevent relapses and slow progression, even for a long time, although the possible adverse effects are relevant, in particular for the more effective drugs. An early prediction of disease course would allow differentiation of the treatment based on the expected aggressiveness of the disease, reserving high-impact therapies for patients at greater risk. To increase prognostic capacity, approaches based on machine learning (ML) algorithms are being attempted, given the failure of other approaches. Here we review recent studies that have used clinical data, alone or with other types of data, to derive prognostic models. Several algorithms that have been used and compared are described. Although no study has proposed a clinically usable model, knowledge is building up and in the future strong tools are likely to emerge.

Experiences, distress and burden among neurologists in Norway during the COVID-19 pandemic

BACKGROUND

The ongoing COVID-19 pandemic has caused rapid changes in the healthcare system. Workforce reorganization, reduced standard of care and a lack of personal protection equipment (PPE) for health care workers were among the concerns raised in the first wave of the pandemic. Our aim was to explore the experiences, distress and burden among Norwegian neurologists during the first weeks of the pandemic.

METHODS

Hospital-based neurologists in Norway (n = 400) were invited to a web-based survey in April 2020. The study focused on patient management, organizational changes and personal stress during the first weeks of the pandemic lockdown. Work-home interface stress was assessed by the Cooper Job Stress Questionnaire.

RESULTS

In total, 135 neurologists participated. Seventy-three% experienced a change in their personal work situation, and 67% examined patients with suspected COVID-19 infection and neurological disease. Changed access to resources, and the perception that medical follow-up was unsatisfactory, were associated with a high degree of burden and stress. Neurologists were also worried about the potential lack of PPE and the fear of spreading SARS CoV-2 to close family members. The mean score of work-home interface stress was 2.8 with no significant differences between gender or specialist status. Reduced standard of care was reported for all neurological conditions, and in particular for non-emergency treatments.

CONCLUSION

The vast majority of neurologists in Norway experienced a change in their personal work situation during the first phase of the pandemic. The fear of becoming infected and ill was not a major contributor to burden and stress.

A systematic review of the application of machine-learning algorithms in multiple sclerosis

INTRODUCTION

The applications of artificial intelligence, and in particular automatic learning or "machine learning" (ML), constitute both a challenge and a great opportunity in numerous scientific, technical, and clinical disciplines. Specific applications in the study of multiple sclerosis (MS) have been no exception, and constitute an area of increasing interest in recent years.

OBJECTIVE

We present a systematic review of the application of ML algorithms in MS.

MATERIALS AND METHODS

We used the PubMed search engine, which allows free access to the MEDLINE medical database, to identify studies including the keywords "machine learning" and "multiple sclerosis." We excluded review articles, studies written in languages other than English or Spanish, and studies that were mainly technical and did not specifically apply to MS. The final selection included 76 articles, and 38 were rejected.

CONCLUSIONS

After the review process, we established 4 main applications of ML in MS: 1) classifying MS subtypes; 2) distinguishing patients with MS from healthy controls and individuals with other diseases; 3) predicting progression and response to therapeutic interventions; and 4) other applications. Results found to date have shown that ML algorithms may offer great support for health professionals both in clinical settings and in research into MS.

Electronic Health Interventions in the Case of Multiple Sclerosis: From Theory to Practice

(1) Background: eHealth interventions play a growing role in shaping the future healthcare system. The integration of eHealth interventions can enhance the efficiency and quality of patient management and optimize the course of treatment for chronically ill patients. In this integrative review, we discuss different types of interventions, standards and advantages of quality eHealth approaches especially for people with multiple sclerosis (pwMS). (2) Methods: The electronic databases PubMed, Cochrane and Web of Science were searched to identify potential articles for eHealth interventions in pwMS; based on 62 articles, we consider different ways of implementing health information technology with various designs. (3) Results: There already exist some eHealth interventions for single users with a single-use case, interventions with a social setting, as well as eHealth interventions that integrate various single and social interventions and even those that may be used additionally for complex use cases. A key determinant of consumer acceptance is a high-quality user-centric design for healthcare practitioners and pwMS. In pwMS, the different neurological disabilities should be considered, and particular attention must be paid to the course of the treatment and the safety processes of each treatment option. (4) Conclusion: Depending on the field of application and the respective users, interventions are designed for single, social, integrated or complex use. In order to be accepted by their target group, interventions must be beneficial and easy to use.

Experiences of telemedicine in neurological out-patient clinics during the COVID-19 pandemic

Objective

The COVID‐19 pandemic has led to rapid changes in the delivery of medical care worldwide. The main objective of this survey was to investigate the initial experiences of neurologists with the use of telemedicine for different neurological conditions during the first phase of the COVID‐19.

Methods

All hospital‐based neurologists in Norway (n = 400) were invited to a questionnaire survey by e‐mail in April 2020. The study focused on telemedicine and all questions were answered with regard to the first weeks of the pandemic lockdown in Norway.

Results

One‐hundred and thirty‐five neurologists responded. Overall, 87% reported a shift toward more telemedicine, with significantly more use of telephone than video consultations for both new referrals (54% vs. 30%, P < 0.001) and follow‐ups (99% vs. 50%, P < 0.001). Respondents deemed it much more professionally satisfactory to conduct follow‐up consultations by telephone, than to carry out consultations with new patients by telephone (85% vs. 13%, P < 0.001). Teleconsultations were better suited for headache and epilepsy patients as compared to multiple sclerosis and movement disorder patients. There was no significant difference between residents and senior consultants regarding how they experienced teleconsultations. Female neurologists found telemedicine better and more effective than male neurologists.

Interpretation

Telemedicine was rapidly implemented in Norwegian neurological departments during the first weeks of the COVID‐19 pandemic. Teleconsultations were better suited for follow‐ups than for new referrals, and better for headache and epilepsy patients as compared to multiple sclerosis and movement disorder patients.

Behavioral practices of patients with multiple sclerosis during Covid-19 pandemic

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, China, in late 2019 and Covid-19, a disease caused by SARS-CoV-2 became a pandemic in March 2020. As the pandemic still unfolds, uncertainty circles around the impact of SARS-CoV-2 infection on patients with chronic diseases, including autoimmune diseases such as multiple sclerosis (MS). To diminish the risk of SARS-CoV-2 infection and lessen the impact of the Covid-19 pandemic on the healthcare of MS patients, it is essential to understand knowledge, attitudes, and various behavioral practices related to Covid-19 among MS patients. Therefore, this study aimed to look at the behavioral practices related to Covid-19 among patients with MS. A total of 176 MS patients diagnosed at least one year before the survey were conveniently sampled online in Saudi Arabia and their data collected using a structured interview questionnaire in electronic Google form. We determined the reliability of the questionnaire by measuring its internal consistency in a pilot sample of 30 participants. Overall, more than 80% of participants had good knowledge and attitudes towards Covid-19. However, this did not correlate well with the impact on healthcare (r = 0.06). Our study revealed that 46% of participants were anxious about taking their medication, and 32% of participants missed their hospital appointments. Furthermore, 15% of the participants had a relapse but did not go to the hospital because of the pandemic, 15.9% stopped their DMTs, and 35.2% missed drug infusions or refills. Our study revealed overall good knowledge and attitudes related to Covid-19 among MS patients. However, the healthcare impact was considerable, as 32% of the participants missed their hospital appointments, and another 15% had a relapse. This highlights the significance of the impact of the Covid-19 pandemic on the healthcare of patients with MS. Measures to mitigate the effect of the pandemic on healthcare service delivery to patients with MS, such as telemedicine, should be strongly encouraged.

Feasibility of Real Time Internet-Based Teleconsultation in Patients With Multiple Sclerosis: Interventional Pilot Study

BACKGROUND

Telemedicine (TM) is currently flourishing in rural and emergency settings, but its implementation in the routine management of chronic neurological disorders has developed with more hesitation. Limited access to specialized care facilities and expanding patient populations, combined with unprecedented mobility restrictions imposed by the coronavirus disease pandemic, are currently stressing the need for remote solutions in this field. Studies in patients with multiple sclerosis (MS) have been heterogeneous in objectives and methodology but generally support the concept that TM interventions produce clinical benefits, cost-effectiveness, and user satisfaction. Nonetheless, data on live interaction between patients and health care providers for MS teleconsultation purposes remain scarce.

OBJECTIVE

The aim of this study is to demonstrate the feasibility of planned real time audiovisual teleconsultation over the internet for patients with MS.

METHODS

A total of 20 patients with MS presenting at a specialized MS center in Belgium were recruited for this study. One teleconsultation was scheduled for each participant. Patients were provided a unique hyperlink by mail in advance, leading them automatically and directly to the virtual waiting room, where they could accept or decline our incoming call. All teleconsultations were performed by a trained medical student with the intention to keep the conversation similar to what is usually discussed during a classic face-to-face MS consultation; no remote physical exams were performed. The approach was considered feasible if at least 80% of the planned TM visits could be successfully completed at the foreseen moment. Patient satisfaction (technical quality, convenience, and overall quality of care) was evaluated at the end of each teleconsultation by means of 5-point Likert scales containing the categories very unsatisfied, unsatisfied, neutral, satisfied, and highly satisfied.

RESULTS

Out of 20 consultations, 17 were successfully completed (85%). Failures were due to patients not responding (n=2) and technical issues (n=1). Out of the 17 consultations, 17 patients declared themselves satisfied or highly satisfied for technical quality, 15 patients for convenience, and 16 patients for overall quality of care.

CONCLUSIONS

Planned real time audiovisual teleconsultation over the internet is feasible and highly appreciated in patients with MS. Incorporation of such services in routine clinical MS practice is expected to improve access to specialized care facilities for affected patients.

Insights for Fostering Resilience in Young Adults With Multiple Sclerosis in the Aftermath of the COVID-19 Emergency: An Italian Survey

Objective: Recent evidence has demonstrated that the COVID-19 pandemic is taking a toll on the mental health of the general population. The psychological consequences might be even more severe for patients with special healthcare needs and psychological vulnerabilities due to chronic diseases, such as multiple sclerosis (MS). Thus, we aimed to explore the psychological impact of this pandemic and of the subsequent healthcare service changes on young adults with MS living in Italy and to examine their coping strategies and preferences regarding psychological support in the aftermath of the pandemic. Methods: Data were collected using a cross-sectional, web-based survey advertised on social networks. We report both quantitative (descriptive statistics, t-tests, and one-way ANOVA) and qualitative data (inductive content analysis). Results: Two hundred and forty-seven respondents (mean age 32 ± 7 years), mainly with relapsing-remitting MS, from all Italian regions participated. Participants felt more worried, confused, sad, and vulnerable because of the disease "during" the pandemic in comparison to their self-evaluation of the period "before" the COVID-19 outbreak. Similarly, their perception of control over MS decreased "during" the pandemic in comparison to the retrospective evaluation of the period "before" the COVID-19 outbreak (p < 0.01). Canceled/postponed visits/exams were listed as the most frequent MS management changes, with modified/postponed pharmacological treatment representing the most stressful change. Psychological support in dealing with pandemic-related fears and improving MS acceptance and well-being was considered extremely important by almost 40% of the respondents. Different coping strategies were mentioned in the qualitative section of the survey, with social support, hobbies, and keeping busy being the most frequent ones. Conclusions: Considering the enormous impact of the pandemic on young adults with MS, we urge MS clinical centers to implement psychological support programs that address the potentially long-lasting psychological negative impact, thus fostering the therapeutic alliance that is being threatened by the infection prevention measures imposed during the pandemic, and promoting psychological resources for adaptively managing future waves of COVID-19.