Clinical Research: Posters and Presentations

Prior Conference Posters




Poster URL

The Association between MRI Brain Volumes and Computerized Multi-Domain Cognitive Scores of People with Multiple Sclerosis N/A Cognitive impairment (CI) is common and disabling among people with Multiple Sclerosis (PwMS). The presence of CI is not often monitored or only partially screened due to the complexity of evaluation. Cross sectional analysis of computerized cognitive scores are significantly associated with quantified MRI measures (whole brain volumes, white matter volumes, lesion volume, etc.). These findings could lead to enhanced routine clinical care and improved patient outcomes. Here
Multiple Sclerosis Management: Predicting Disease Trajectory of People with Multiple Sclerosis Utilizing Multi-Dimensional Data Including Digital Cognitive Assessments and Patient Reported Outcomes Using Machine Learning Techniques N/A Multiple Sclerosis (MS) disease impact and progression is traditionally measured by neuro-radiologist reported MRI changes, patient reported relapse rates, and neurological examination determined disability status. Expanded Disability Status Scale (EDSS) does not reflect cognitive impairment (CI) and neurologist detection of CI is neither sensitive nor quantitative. CI, independent of EDSS, can impact patients’ employability, ability to drive, fall risk, and quality of life (QoL). Patient reported outcomes (PROs) and digital functional measures (cognition, gait) are emerging as more meaningful, patient-centered measures. Combining multidimensional PRO and quantified, digital, objective, examiner-independent disease impact information might enhance clinical decision making. Machine learning can help clinicians predict the trajectory of MS using ongoing streams of such population data. Real-time collection of de-identified data can continuously improve predictions and surface the relevant features that predict both treatment and expected PRO outcomes. Here
Multiple Sclerosis Management and EDSS: A Great Start, But a Reason for Change Was Never So Apparent and Needed N/A Since the Expanded Disability Status Scale (EDSS) was pioneered by
Dr. John Kurtzke in 1967, it has been incorporated into clinical trial and routine care measurements in people with Multiple Sclerosis (PwMS). The use of non-linear scales to measure disability can be problematic if there is large variability within EDSS groupings. Practical abilities of PwMS include both “visible” and “invisible” disease impact aspects, such as cognitive function, ambulation, manual dexterity, and other factors. Objective, patient-centric, multidimensional, quantitative, validated, examiner-independent measures of disease impact should be used over the traditional measures that only capture “visible” disease impacts. This would allow identification of critical impact earlier, leading to improved treatment selection, monitoring for progression, need for treatment change, or other interventions.
Exploring and Quantifying Performance Differences in Real World Ambulation Parameters in People with Multiple Sclerosis: Multi-Dimensional Objective Gait Parameters N/A Improved understanding of “real world walking” (RWW) in people with Multiple Sclerosis (PwMS) could enhance treatment decisions and understanding of what underlies the Patient Reported Outcomes (PRO) that reflect patient perceptions of RWW (MSWS-12, Activity Balance Confidence, Modified Falls Efficacy Scale). RWW generally includes combinations of “preferred walking speed” (PWS), walking while performing a cognitive task (Dual Tasking, DT) and/or prolonged walking (PWS after 6 minute timed walk, “6MTW”).Through the comparison of multi-dimensional objective gait domains between PwMS within 3 different ability groups based on their EDSS scores, the significance of disease impact on ambulation can be explored. Here