Quantification characteristics of digital spiral analysis for understanding the relationship among tremor and clinical measures in persons with multiple sclerosis

Abstract

BackgroundMultiple sclerosis (MS) is a degenerative neurological condition causing demyelination and neuronal loss. Tremor, a symptom of MS, is prevalent in 45.0–46.8% NARCOMS registrants. Although several tools to measure tremor exist, few outcomes are quantitative or regularly utilized clinically. New methodIntroduction of a novel adaptation of the digital spiral drawing to find a quick, sensitive, and clinically useful technique, to predict tremor in persons with MS (pwMS). Digital spiral measures included: Segment Rate (SEGRT), Standard Deviation (SD) of Radial Velocity (VSD-R), SD of Tangential Velocity (VSD-T), SD of Overall Velocity (VSD-O), Mean Drawing Velocity (MNV-O) and Mean Pen Pressure Acceleration (MNA-P). Digital spiral measures were compared with the manual Archimedes Spiral (AS) drawing and the following clinical measures: Finger-Nose Test (FNT), presence of visually observed intention tremor (VOT), Nine-Hole Peg Test (NHPT), and Box and Block Test (BBT). ResultsAll clinical measures utilized demonstrated significant relationships with all digital variables, except VSD-R. The forward-stepwise regression revealed BBT accounted for the most variance, followed by SEGRT.Comparison with Existing Methods: SEGRT is more sensitive in detecting VOT and better for quantifying tremor than AS. BBT and SEGRT are optimal predictive measures for tremor. ConclusionsSEGRT has stronger sensitivity and negative predictive value than AS in detecting VOT. All clinical measures (NHPT, FNT, BBT, and AS) were significantly associated with the digital variables (SEGRT, VSD-T, VSD-O, MNV-O, and MNA-P) except for VSD-R. After controlling for Patient Determined Disease Steps (PDDS), BBT and SEGRT are the best predictive measures for tremor.