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RESEARCH PRODUCT
Disability assessment using Google Maps.
Francesca TrojsiDomenico IppolitoPaolo RagoneseSabrina EspositoSabrina EspositoGiacomo LusGiovanna BorrielloGioacchino TedeschiMaddalena SparacoGianmarco AbbadessaLuigi LavorgnaFrancesco BrigoElisabetta SignorielloMarinella ClericoPietro IaffaldanoRoberta LanzilloSimona BonavitaRaffaele PalladinoRosa Gemma ViterboSimone CepparuloMarcello MocciaMaria Troianosubject
medicine.medical_specialtyNeurologyMultiple SclerosisConcordanceAmbulatory disordersDermatology03 medical and health sciencesDisability Evaluation0302 clinical medicineInternal medicinemedicineGoogle MapsHumans030212 general & internal medicineDepression (differential diagnoses)Ambulatory disorderFatigueNeuroradiologyExpanded Disability Status Scalebusiness.industryGeneral MedicineOdds ratioConfidence intervalSearch EnginePsychiatry and Mental healthCross-Sectional StudiesAmbulatorye-HealthOriginal ArticleNeurology (clinical)businessDigital health030217 neurology & neurosurgerydescription
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.
year | journal | country | edition | language |
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2021-01-01 | Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical NeurophysiologyReferences |