Ruth Ann Marrie

Oct 16, 2024 | jnnp.bmj.com | Richard Nicholas |Emma Clare Tallantyre |James Witts |Ruth Ann Marrie

DiscussionWe describe an algorithm to identify pwMS within a national routine data repository. We used a clinician-confirmed population-based cohort, and a self-declared previously validated12 cohort to validate the algorithm, confirming high sensitivity and specificity. We were able to demonstrate that the age at diagnosis calculated by the algorithm is similar to the age at diagnosis self-reported by patients and confirmed by clinicians within both validation cohorts.

May 23, 2024 | jnnp.bmj.com | Richard Nicholas |Emma Clare Tallantyre |James Witts |Ruth Ann Marrie

MethodsWe used a cross-sectional population-based cohort study to develop an algorithm to identify pwMS living in Wales, using SAIL. SAIL uses a trusted third party (NHS Wales) to implement a unique Anonymous Linking Field (ALF) as records are loaded into the repository.4 Users of SAIL are not allowed to use any method to identify patients within it. We used the following datasets:Individuals registered with Welsh GPs (https://data.sail.ukserp.ac.uk/Asset/View/20).

Nov 27, 2023 | dom-pubs.onlinelibrary.wiley.com | Wajd Alkabbani |Ruth Ann Marrie |Max Rady College |Suzanne L. Tyas

1 BACKGROUND In a recent cohort study, insulin use was not associated with an increased risk of all-cause dementia after adjusting for confounding.1 The study showed how confounding by disease severity because of the lack of a clinically appropriate comparator could account for the higher risk of dementia with insulin use observed in previous observational studies.2, 3 However, questions surrounding the role of hypoglycaemia as a potential mediator of the insulin-dementia association...

Aug 9, 2023 | journals.sagepub.com | Maria Pia Sormani |Jeremy Chataway |Ruth Ann Marrie

IntroductionOutcomes in multiple sclerosis (MS) are well recognized to be heterogeneous. This heterogeneity may also extend to therapeutic responses and adverse effects and can be accounted for by multiple factors including genetic differences, as well as age, sex, liver or renal function, health behaviors, and disease severity.1 For example, genetic variation influences the expression of thiopurine S-methyltransferase (TPMT) enzyme.

Aug 9, 2023 | journals.sagepub.com | Ruth Ann Marrie |Jeremy Chataway |Barbara E. Bierer |Marcia Finlayson

AbstractBackground:Demographic characteristics, social determinants of health (SDoH), health inequities, and health disparities substantially influence the general and disease-specific health outcomes of people with multiple sclerosis (MS). Participants in clinical trials do not represent all people with MS treated in practice. Objective:To provide recommendations for enhancing diversity and inclusion in clinical trials in MS.