Activity ID
13473Expires
March 1, 2025Format Type
LiveCME Credit
16.50Fee
675CME Provider: Interstate Postgraduate Medical Association
Description of CME Course
Practice Gap: The current lack of updated knowledge among clinicians regarding the latest advances in MS research, including pathogenic mechanisms, novel measures to capture disease activity, and treatment options, hinders optimal patient care and may limit the use of cutting-edge strategies.
Practice Gap: Despite advancements in understanding MS, there remains a significant knowledge gap in how aging, both biological and chronological, influences disease pathology and progression. This gap extends to the effects of aging on the immune system, central nervous system (CNS), and response to therapy, which are critical factors in managing older MS patients.
Practice Gap: While there have been significant strides in understanding MS, clinicians and researchers often lack a comprehensive perspective on how MS compares to other neurological conditions in terms of genetic risk, transcriptomes, prodromes, and pathophysiology. This gap hinders the development of more effective, targeted therapies that could benefit a broader range of neurodegenerative and autoimmune disorders.
Practice Gap: There is a significant knowledge gap in understanding the functional connections between different regions of the central nervous system (CNS), the interactions between CNS compartments, and the communication between the CNS and the peripheral nervous system in the context of MS. This gap limits the ability of clinicians to fully comprehend disease mechanisms and hampers the development of effective therapeutic strategies.
Practice Gap: Despite the rapid advancement of machine learning technologies in healthcare, there is a significant gap in their application to MS clinical practice. Clinicians often lack the tools and expertise to effectively leverage machine learning for understanding MS pathology, predicting disease progression, and managing clinical heterogeneity, which limits the potential for personalized treatment strategies.
Practice Gap: Despite advances in understanding MS, there is a gap in knowledge regarding the factors that drive remyelination and the reasons for its failure. This gap hinders the development of effective clinical strategies to protect axonal health and accurately measure remyelination in MS patients.
ABMS Member Board Approvals by Type
ABMS Lifelong Learning CME Activity
Psychiatry and Neurology
Commercial Support?
NoNOTE: If a Member Board has not deemed this activity for MOC approval as an accredited CME activity, this activity may count toward an ABMS Member Board’s general CME requirement. Please refer directly to your Member Board’s MOC Part II Lifelong Learning and Self-Assessment Program Requirements.
Educational Objectives
* Update clinicians on the latest advances in pathogenic mechanisms of multiple sclerosis to enhance their diagnostic and treatment strategies.
* Equip clinicians with knowledge of novel measures to capture disease activity and emerging treatment options to optimize personalized care for MS patients.
* Assess the impact of biological aging on multiple sclerosis by exploring the role of MRI in evaluating biological age, the influence of aging T cells, and the gut-brain axis in neuroinflammation.
* Evaluate the influence of aging on therapeutic responses in MS to develop more effective, age-specific treatment strategies.
* Compare genetic risk loci and transcriptomic profiles between multiple sclerosis and other autoimmune or demyelinating diseases to identify common and distinct therapeutic targets.
* Evaluate the prodromes and pathophysiological differences between MS and related conditions such as MOGAD to improve early diagnosis and tailor treatment strategies.
* Investigate the structural and functional disconnectivity within the CNS and its impact on grey matter pathology and disease progression in multiple sclerosis.
* Explore the role of peripheral nervous system elements, such as the vagus nerve and skull bone marrow, in influencing CNS pathology and promoting remyelination in multiple sclerosis.
* Utilize machine learning techniques to analyze clinical and imaging data in MS, improving the prediction of disease progression and enhancing personalized treatment strategies.
* Interpret machine learning outputs to identify clinical subtypes and tailor treatments to individual MS patients based on their specific genetic and molecular profiles.
*Investigate the heterogeneity of oligodendrocyte responses and the mechanisms leading to axonal vulnerability in MS to develop targeted therapies for enhancing remyelination and protecting axonal health.
* Explore novel imaging techniques, including PET, to accurately measure remyelination and demyelination in MS, facilitating improved clinical assessment and therapeutic guidance.
Keywords
MS Conference, Multiple Sclerosis, MS Research, MS Education
Competencies
Medical Knowledge, Patient Care & Procedural Skills
CME Credit Type
AMA PRA Category 1 Credit
Practice Setting
Academic Medicine, Inpatient, Outpatient, Physician Scientists, Rural, Urban, VA/Military
