4.5 Article

Disability assessment using Google Maps

期刊

NEUROLOGICAL SCIENCES
卷 43, 期 2, 页码 1007-1014

出版社

SPRINGER-VERLAG ITALIA SRL
DOI: 10.1007/s10072-021-05389-7

关键词

Digital health; e-Health; Google Maps; Ambulatory disorders

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The study found discrepancies in AS and EDSS assessments between GM (R) and routine clinical methods in 243 patients with multiple sclerosis. Progressive phenotype, worse fatigue, and more severe depression were associated with discrepancies between GM (R) and routine clinical scoring.
Objectives To evaluate the concordance between Google Maps (R) application (GM (R)) and clinical practice measurements of ambulatory function (e.g., Ambulation Score (AS) and respective Expanded Disability Status Scale (EDSS)) in people with multiple sclerosis (pwMS). Materials and methods This is a cross-sectional multicenter study. AS and EDSS were calculated using GM (R) and routine clinical methods; the correspondence between the two methods was assessed. A multinomial logistic model is investigated which demographic (age, sex) and clinical features (e.g., disease subtype, fatigue, depression) might have influenced discrepancies between the two methods. Results Two hundred forty-three pwMS were included; discrepancies in AS and in EDDS assessments between GM (R) and routine clinical methods were found in 81/243 (33.3%) and 74/243 (30.4%) pwMS, respectively. Progressive phenotype (odds ratio [OR] = 2.8; 95% confidence interval [CI] 1.1-7.11, p = 0.03), worse fatigue (OR = 1.03; 95% CI 1.01-1.06, p = 0.01), and more severe depression (OR = 1.1; 95% CI 1.04-1.17, p = 0.002) were associated with discrepancies between GM (R) and routine clinical scoring. Conclusion GM (R) could easily be used in a real-life clinical setting to calculate the AS and the related EDSS scores. GM (R) should be considered for validation in further clinical studies.

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