Objectives: To evaluate the concordance between Google Maps® application (GM®) 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® 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® 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® and routine clinical scoring. Conclusion: GM® could easily be used in a real-life clinical setting to calculate the AS and the related EDSS scores. GM® should be considered for validation in further clinical studies.
Correction to: Disability assessment using Google Maps (Neurological Sciences, (2022), 43, 2, (1007-1014), 10.1007/s10072-021-05389-7)
Iaffaldano, P.;Troiano, M.;
2022-01-01
Abstract
Objectives: To evaluate the concordance between Google Maps® application (GM®) 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® 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® 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® and routine clinical scoring. Conclusion: GM® could easily be used in a real-life clinical setting to calculate the AS and the related EDSS scores. GM® should be considered for validation in further clinical studies.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
