Disability assessment using Google Maps.
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| Title: | Disability assessment using Google Maps. |
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| Authors: | Lavorgna, Luigi (AUTHOR), Iaffaldano, Pietro (AUTHOR), Abbadessa, Gianmarco (AUTHOR), Lanzillo, Roberta (AUTHOR), Esposito, Sabrina (AUTHOR), Ippolito, Domenico (AUTHOR), Sparaco, Maddalena (AUTHOR), Cepparulo, Simone (AUTHOR), Lus, Giacomo (AUTHOR), Viterbo, Rosa (AUTHOR), Clerico, Marinella (AUTHOR), Trojsi, Francesca (AUTHOR), Ragonese, Paolo (AUTHOR), Borriello, Giovanna (AUTHOR), Signoriello, Elisabetta (AUTHOR), Palladino, Raffaele (AUTHOR), Moccia, Marcello (AUTHOR), Brigo, Francesco (AUTHOR), Troiano, Maria (AUTHOR), Tedeschi, Gioacchino (AUTHOR) |
| Source: | Neurological Sciences. Feb2022, Vol. 43 Issue 2, p1007-1014. 8p. 1 Diagram, 3 Charts. |
| 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. [ABSTRACT FROM AUTHOR] |
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| Database: | Psychology and Behavioral Sciences Collection |
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| 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. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 15901874 |
| DOI: | 10.1007/s10072-021-05707-z |
