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Disability assessment using Google Maps
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 cro...
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8211455/ https://www.ncbi.nlm.nih.gov/pubmed/34142263 http://dx.doi.org/10.1007/s10072-021-05389-7 |
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author | Lavorgna, Luigi Iaffaldano, Pietro Abbadessa, Gianmarco Lanzillo, Roberta Esposito, Sabrina Ippolito, Domenico Sparaco, Maddalena Cepparulo, Simone Lus, Giacomo Viterbo, Rosa Clerico, Marinella Trojsi, Francesca Ragonese, Paolo Borriello, Giovanna Signoriello, Elisabetta Palladino, Raffaele Moccia, Marcello Brigo, Francesco Troiano, Maria Tedeschi, Gioacchino Bonavita, Simona |
author_facet | Lavorgna, Luigi Iaffaldano, Pietro Abbadessa, Gianmarco Lanzillo, Roberta Esposito, Sabrina Ippolito, Domenico Sparaco, Maddalena Cepparulo, Simone Lus, Giacomo Viterbo, Rosa Clerico, Marinella Trojsi, Francesca Ragonese, Paolo Borriello, Giovanna Signoriello, Elisabetta Palladino, Raffaele Moccia, Marcello Brigo, Francesco Troiano, Maria Tedeschi, Gioacchino Bonavita, Simona |
author_sort | Lavorgna, Luigi |
collection | PubMed |
description | 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10072-021-05389-7. |
format | Online Article Text |
id | pubmed-8211455 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-82114552021-06-21 Disability assessment using Google Maps Lavorgna, Luigi Iaffaldano, Pietro Abbadessa, Gianmarco Lanzillo, Roberta Esposito, Sabrina Ippolito, Domenico Sparaco, Maddalena Cepparulo, Simone Lus, Giacomo Viterbo, Rosa Clerico, Marinella Trojsi, Francesca Ragonese, Paolo Borriello, Giovanna Signoriello, Elisabetta Palladino, Raffaele Moccia, Marcello Brigo, Francesco Troiano, Maria Tedeschi, Gioacchino Bonavita, Simona Neurol Sci Original Article 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10072-021-05389-7. Springer International Publishing 2021-06-17 2022 /pmc/articles/PMC8211455/ /pubmed/34142263 http://dx.doi.org/10.1007/s10072-021-05389-7 Text en © Fondazione Società Italiana di Neurologia 2021, corrected publication 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Article Lavorgna, Luigi Iaffaldano, Pietro Abbadessa, Gianmarco Lanzillo, Roberta Esposito, Sabrina Ippolito, Domenico Sparaco, Maddalena Cepparulo, Simone Lus, Giacomo Viterbo, Rosa Clerico, Marinella Trojsi, Francesca Ragonese, Paolo Borriello, Giovanna Signoriello, Elisabetta Palladino, Raffaele Moccia, Marcello Brigo, Francesco Troiano, Maria Tedeschi, Gioacchino Bonavita, Simona Disability assessment using Google Maps |
title | Disability assessment using Google Maps |
title_full | Disability assessment using Google Maps |
title_fullStr | Disability assessment using Google Maps |
title_full_unstemmed | Disability assessment using Google Maps |
title_short | Disability assessment using Google Maps |
title_sort | disability assessment using google maps |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8211455/ https://www.ncbi.nlm.nih.gov/pubmed/34142263 http://dx.doi.org/10.1007/s10072-021-05389-7 |
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