I15 Electronic clinical dashboard for assessing symptomatic progression in huntington's disease. (13th September 2016)

• Record Type: Journal Article
• Authors: Walker, Thomas; Kipps, Christopher; Ghosh, Boyd
• Is Part Of: Journal of neurology, neurosurgery and psychiatry. Volume 87(2016)Supplement 1
• Page Start: A64
• Page End: A64
• Publication Date: 2016-09-13
• Subjects: UHDRS -- biomarkers -- longitudinal -- clinical dashboard -- Enroll-HD -- motor score -- functional capacity; Neurology -- Periodicals; Nervous system -- Surgery -- Periodicals; Psychiatry -- Periodicals; 616.8
• DOI: 10.1136/jnnp-2016-314597.180
• Languages: English
• ISSNs: 0022-3050

Abstract

Abstract : Background: Huntington's disease (HD) is characterised by progressive motor, cognitive and psychiatric symptoms. However, it is difficult for clinicians to identify whether clinical features in an individual with manifest HD are progressing at a rate comparable to that expected for peers with similar CAG repeat length (CAGn) and age. Aims: To develop an electronic dashboard to compare an individual's clinical symptom rating scores against a global cohort (Enroll-HD), controlling for age and CAGn. This dashboard could then be used by clinicians to monitor change in an individual's scores over time, and identify patients progressing at a disproportionate rate to his or her peers. Methods: Annualised longitudinal symptom scores from the Enroll-HD cohort were used to generate predicted decline trajectories and confidence intervals for UHDRS Total Motor Score (TMS), Total Functional Capacity (TFC) and Symbol Digit Modalities Test (SDMT), allowing comparison and mapping of individual clinical symptom rating scores with the global cohort, both cross-sectionally (n = 734) and longitudinally (n = 270). Results: An electronic dashboard with a dynamic output display was created that maps individual UHDRS scores (TMS, TFC, SDMT) against decline trajectories of affected peers from the global cohort with comparable CAGn. It was validated for design and output. Conclusions: This study shows the potential for use of multi-centre trial data in developing an electronic clinical dashboard to facilitate improved decision-making for individual patients. The dashboard may help identify those with disproportionate motor and functional decline, and suggest specific clinical intervention points.