Evidence map›Paper›PMID 34896930›Full record

ArticleParkinsonism & related disorders2022

An equation to calculate UPDRS motor severity for online and rural assessments of Parkinson's.

Kishoree Sangarapillai, Benjamin M Norman, Quincy J Almeida

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Article in Parkinsonism & related disorders, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

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6citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Kishoree SangarapillaiMovement Disorders Research and Rehabilitation Centre, Wilfrid Laurier University, Ontario, Canada.
Benjamin M NormanMovement Disorders Research and Rehabilitation Centre, Wilfrid Laurier University, Ontario, Canada.
Quincy J AlmeidaMovement Disorders Research and Rehabilitation Centre, Wilfrid Laurier University, Ontario, Canada. Electronic address: qalmeida@wlu.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveManagement of PD has largely been affected by COVID-19. Due to the restrictions posed by COVID-19, there has been a shift from in-person to online forms of assessment. This presents a challenge as not all motor symptoms can be assessed virtually. Two of the four cardinal symptoms of PD (rigidity and postural instability) cannot be assessed virtually using the gold-standard Unified Parkinson's Disease Rating Scale (UPDRS-III). As a result, an accurate total motor severity score can not be computed from the remaining subsections. Recently, one study stated that in order for accurate scores to be calculated, only three sections could be absent. Virtually, six sections are unable to be evaluated with online assessments. This inability to compute a total motor severity score may result in poor disease management. Thus, in this study a regression equation was developed to predict total motor severity scores from partial scores.

methodsTotal motor severity scores (UPDRS-III) from N = 234 individuals with idiopathic Parkinson's were retrospectively analyzed. In order to conduct a linear regression analysis predictor and outcome variables were created. The variables were then used for the linear regression. The equation was then tested on an independent data set N = 1168.

resultsThe regression analysis resulted in the equation to predict total motor symptom severity of PD.

conclusionsIn conclusion, the developed equation will be very useful for outreach in rural communities, as well as the continued remote management of PD during COVID-19 and beyond.

Indexed as

Mental Status and Dementia TestsNeurologic ExaminationCOVID-19HumansLinear ModelsParkinson DiseaseReproducibility of ResultsSARS-CoV-2Severity of Illness IndexStatistics as TopicTelemedicineCOVID-19Motor severityParkinson's diseasePredictionRegression analysisUPDRS-III

Identifiers

PMID34896930
PMCPMC9759848

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.