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Cognitive impairments in Multiple Sclerosis (MS) are prevalent and disabling yet often unaddressed. Here, we optimised automated online assessment technology for people with MS and used it to characterise their cognitive deficits in greater detail and at a larger population scale than previously possible. The study involved 4526 UK MS Register members over three stages. Stage 1 evaluated 22 online cognitive tasks and established their feasibility. Based on MS discriminability a 12-task battery was selected. Stage 2 validated the resulting battery at scale, while Stage 3 compared it to a standard neuropsychological assessment. Clustering analysis identified a prevalent MS subtype exhibiting significant cognitive deficits with minimal motor impairment. Disability in this group is currently unrecognised and untreated. These findings underscore the importance of cognitive assessment in MS, the feasibility of integrating online tools into patient registries, and the potential of such large-scale data to derive insights into symptom heterogeneity. Online cognitive testing combined with the reach of a digital patient registry revealed a subtype of people with Multiple Sclerosis with significant cognitive impairment but no motor deficits. This hidden disability is often underestimated and left untreated.

Understanding the associations and potential drivers of long-term disability in Multiple Sclerosis (MS) is of clinical and prognostic value. Previous data have suggested a link between depression and disability accrual in MS. We aimed to determine whether depression in early MS predicts subsequent accrual of disability. Using data from the UK MS Register, we identified individuals with and without symptoms of depression and anxiety close to disease onset. We used Cox proportional hazards regression to evaluate whether early depressive or anxiety symptoms predict subsequent physical disability worsening, measured using the Expanded Disability Status Scale (EDSS). We analysed data from 862 people with MS of whom 134 (15.5%) reached an EDSS of ≥ 6.0. Early depressive symptoms were associated with an increased risk of reaching an EDSS of 6.0 (HR 2.42, 95% CI 1.49–3.95, p < 0.001), however this effect dissipated when adjusting for baseline EDSS (HR 1.40, 95% CI 0.84–2.32, p = 0.2). These data suggest that early depressive symptoms in MS are associated with subsequent disability accrual, but are likely the result of disability rather than its cause.

Background: Treatment guidelines recommend early disease-modifying therapy (DMT) initiation after diagnosis of multiple sclerosis (MS). Multinational comparative studies that assess time to DMT initiation in MS may allow detection of barriers inherent to healthcare systems to explain potential adverse systematic delays in commencing DMTs. Objectives: To investigate and compare the time to first DMT and its association with sociodemographic and clinical variables after MS diagnosis in three large MS registries. Design: This observational study was conducted using data from the German MS Registry (GMSR), the North American Research Committee on MS Registry (NARCOMS, US data only), and the United Kingdom MS Registry (UKMSR, both self- and clinician-reported). Methods: Data from relapsing people with MS (PwMS), with a diagnosis of MS between 2014 and 2019, and available DMT and disability status were pooled using a meta-analytic approach. Results: A total of 5395 PwMS were included in the analysis (GMSR: n = 2658; NARCOMS: n = 447; UKMSR: n = 2290). Kaplan–Meier estimates for the time to first DMT [median months (95% CI)] were 2.0 (1.9–2.0), 3.0 (2–4), and 9.0 (7.7–10.6) for GMSR, NARCOMS, and UKMSR, respectively. Pooled multivariable Cox regression demonstrated shorter time to first DMT for PwMS diagnosed after 2017 [1.65 (1.42–1.92), p < 0.01], and longer time to DMT when a higher-efficacy DMT was selected (0.69 (0.54–0.90), p < 0.0001]. Conclusion: Time to DMT initiation differs across the populations studied, indicating that barriers may exist in early access to DMT, particularly in the United Kingdom. However, a consistent decrease in time to DMT initiation was noted since 2017 across all registries. Further studies are warranted comparing the effects of time to DMT and time to higher-efficacy DMT on long-term outcome.

Introduction: Prescribing guidance for disease-modifying treatment (DMT) in multiple sclerosis (MS) is centred on a clinical diagnosis of relapsing–remitting MS (RRMS). DMT prescription guidelines and monitoring vary across countries. Standardising the approach to diagnosis of disease course, for example, assigning RRMS or secondary progressive MS (SPMS) diagnoses, allows examination of the impact of health system characteristics on the stated clinical diagnosis and treatment access. Methods: We analysed registry data from six cohorts in five countries (Czech Republic, Denmark, Germany, Sweden and United Kingdom) on patients with an initial diagnosis of RRMS. We standardised our approach utilising a pre-existing algorithm (DecisionTree, DT) to determine patient diagnoses of RRMS or secondary progressive MS (SPMS). We identified five global drivers of DMT prescribing: Provision, Availability, Funding, Monitoring and Audit, data were analysed against these concepts using meta-analysis and univariate meta-regression. Results: In 64,235 patients, we found variations in DMT use between countries, with higher usage in RRMS and lower usage in SPMS, with correspondingly lower usage in the UK compared to other registers. Factors such as female gender (p = 0.041), increasing disability via Expanded Disability Status Scale (EDSS) score (p = 0.004), and the presence of monitoring (p = 0.029) in SPMS influenced the likelihood of receiving DMTs. Standardising the diagnosis revealed differences in reclassification rates from clinical RRMS to DT-SPMS, with Sweden having the lowest rate Sweden (Sweden 0.009, range: Denmark 0.103 – UK portal 0.311). Those with higher EDSS at index (p < 0.03) and female gender (p < 0.049) were more likely to be reclassified from RRMS to DT-SPMS. The study also explored the impact of diagnosis on DMT usage in clinical SPMS, finding that the prescribing environment and auditing practices affected access to treatment. Discussion: This highlights the importance of a healthcare system’s approach to verifying the clinical label of MS course in facilitating appropriate prescribing, with some flexibility allowed in uncertain cases to ensure continued access to treatment.

IntroductionRepurposing treatments in multiple sclerosis (MS) has resulted in several candidates that are currently in phase 2 and 3 trials but to test candidate therapies requires a prolonged and costly study. Real world data offers the opportunity to assess in non-randomised data the potential of a range of commonly used therapies. The UK MS register is a UK-wide real-world dataset of 20,000 subjects where regular MS outcomes are collected. Using this dataset, we have recently shown the benefits of disease modifying therapies, and smoking cessation in MS. We aimed to determine if such a resource could be used to determine to utility of potential repurposed drug candidatesMethodsOf 20,000 subjects in the UK MS register we identified those on any antidepressants treatment who had at least 2 follow up visits from baseline after starting treatment. We then identified those who had completed the Hospital Anxiety and Depression Scale (HADS) and the Multiple Sclerosis Impact Scale (MSIS-29) scales in addition at each visit.Results3559 subjects on 4294 unique antidepressant treatments were identified (SSRIs: 1852, Tricyclics: 1893, SNRIs: 365. NaSSa: 164, and SARIs: 20). 533 had a baseline visit and 2 follow-up visits with HADS and MSIS-29 questionnaires, where baseline was the beginning of treatment.ConclusionsThe UK MS Register cohort of pwMS can be utilised to support real-world initiatives to inves- tigate potential repurposed candidates.

BackgroundLetters dictated by healthcare professionals in routine patient care form an invaluable dataset but are difficult to access and interpret. The UK MS Register (UKMSR) previously outlined (ABN2019) usage of Natural Language Processing Algorithms (NLP-A) to harvest and transform written language into analysable data in databases. We expanded the variables captured, increased the number of donating hospitals and compared the results to the previous NLP-A.AimApply the new NLP-A to a random letter selection and evaluate output and results.MethodsA random, seeded, selection algorithm chose 100 letters from a corpus of 2690 consented in/outpatient letters from 13 Trusts. Letters were reviewed by human domain experts for Date Of Birth, NHS Number, Gender, Clinic Date, Postcode, MS Type and Expanded Disability Status Score (EDSS). NLP-A was applied and assessment made against the same variables.ResultsRun time was 15.4s, Sensitivity and Specificity > 98% in all cases except Clinic Date (Sensitivity 87%, Specificity 20%), MSType (Sensitivity 84%, Specificity 98%) and Postcode (Sensitivity 100%, Specificity 66%). Low specificity in Clinic Date illustrates disagreement on criteria between reviewer and NLP-A. These results represent a 5% increase (in common variables) in Sensitivity and Specificity over the 2019 algorithm.ConclusionWe have improved the ability to accurately and rapidly identify required variables from the UKMSR minimum dataset using NLP-A. We are continuing to implement this on a widespread basis in the UKMSR.

Neurological conditions present with cognitive impairment that greatly affects the quality of life of the patients and should be routinely evaluated. However, it can be difficult to detect and impractical to monitor with classic in person cognitive assessment due to limitations of sensitivity, scalability and cost. Internet- and app-based tools for cognitive assessment are a potential solution of this problem, offering superior sensitivity and being deliverable remotely in the context of clinical registries, providing an acces- sible and cost-effective way to combine large-scale longitudinal cognitive and clinical data. To validate this idea, we administered a superset of 23 internet-deliverable cognitive tasks from the Cognitron platform to people with multiple sclerosis (PwMS) through the UKMSRegister. These tasks come with extensive normative data (N>400,000) collected during previous large-scale studies. We report high sensitivity to cognitive deficits in PwMS and identify the cognitive domains that are most vulnerable. We propose an optimal subset of tasks that can provide an efficient multivariate profile of cognitive decline in PwMS at scale and longitudinally via MSRegisters. This same approach will be extended to other neurological conditions, offering a way to measure and predict the evolution of cognitive impairment over time, and monitor the long-term impacts of interventions.

BackgroundProvision of care to patients with Multiple Sclerosis (MS) is complex and an effective multi- disciplinary team (MDT) approach is needed. We surveyed patients’ experiences of ideal care and care actually provided.MethodsWe designed a questionnaire to evaluate service provision and expectation in a nationwide cohort of patients from the UK MS Register with subsequent qualitative and quantitative data analysis.Results2512 patients responded. 58% attend a specialist MS Clinic. Mean age 56 years, median EDSS6.0. Of patients with established diagnoses, 48% had RRMS, 35% SPMS, 12% PPMS, 5% undetermined. The biggest reported gaps at clinic were; physiotherapy (reality vs preference) 13% vs 45%, occupational therapy 6% vs 31% and continence advice 6% vs 29%. Clinical course did not influence expectation in these services. Substantial gaps also existed for counselling and dietetics provision. 18% of patients did not report new symptoms/relapses to any healthcare professional. RRMS patients were less likely to be part of this group and PPMS patients more likely, with no difference between genders.ConclusionsThis study illustrates a gap between MDT service provision and patient preference at MS/neurology clinics throughout the UK, and across all patient subgroups. A concerning number of patients do not report new symptoms to MS services, particularly PPMS patients. Further resources should be directed towards bridging these care gaps for MS patients.rachaelkee@doctors.org.uk|ABN Bursary70

BackgroundGiven the expanding utility of cerebrospinal fluid biomarkers in clinical practice and research studies, it may become desirable to offer repeat lumbar puncture (LP) beyond diagnosis. Using the United Kingdom Multiple Sclerosis Register (UKMSR), we assessed patient attitude to LP beyond the diagnostic stage.Design/Methods An online questionnaire was designed and over 11,000 patients were invited to partici- pate. For specific questions, participants indicated willingness for LP on a Likert scale (0–10).ResultsAlmost 2500 patients completed the questionnaire and over half had relapsing remitting MS. Of the 1089 participants on disease-modifying treatment, almost 60% indicated feeling neutral-to-agreeable to having LP to evaluate treatment efficacy or evidence of relapse. Interestingly, those indicating complete willingness represented the modal point on the scale. Respondents were only slightly less receptive to undergoing LP for research, with just under half still neutral-to-agreeable. We did not observe an influence of age or sex on willingness for LP for either indication.ConclusionsSerial LPs may become informative in evaluating for active MS throughout the disease course. We found that patients on treatment are quite agreeable to considering LP for clinical evaluation. Perhaps understandably, respondents were slightly less willing to have LP solely for research purposes.rrobinson17@qub.ac.uk

In this paper, we briefly review the boxed molecular dynamics (BXD) method which allows analysis of thermodynamics and kinetics in complicated molecular systems. BXD is a multiscale technique, in which thermodynamics and long-time dynamics are recovered from a set of short-time simulations. In this paper, we review previous applications of BXD to peptide cyclization, solution phase organic reaction dynamics and desorption of ions from self-assembled monolayers (SAMs). We also report preliminary results of simulations of diamond etching mechanisms and protein unfolding in atomic force microscopy experiments. The latter demonstrate a correlation between the protein's structural motifs and its potential of mean force. Simulations of these processes by standard molecular dynamics (MD) is typically not possible, because the experimental time scales are very long. However, BXD yields well-converged and physically meaningful results. Compared with other methods of accelerated MD, our BXD approach is very simple; it is easy to implement, and it provides an integrated approach for simultaneously obtaining both thermodynamics and kinetics. It also provides a strategy for obtaining statistically meaningful dynamical results in regions of configuration space that standard MD approaches would visit only very rarely.