Evidence map›Paper›PMID 37153678›Full record

ArticleFrontiers in neurology2023

A non-expensive bidimensional assessment can detect subtle alterations in gait performance in people in the early stages of Parkinson's disease.

Matheus Silva d'Alencar, Gabriel Venas Santos, André Frazão Helene, Antonio Carlos Roque, José Garcia Vivas Miranda, Maria Elisa Pimentel Piemonte

Abstract read
In one paragraph

Article in Frontiers in neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Matheus Silva d'AlencarDepartment of Physical Therapy, Speech Therapy and Occupational Therapy, Faculty of Medical Science, University of São Paulo, São Paulo, Brazil.
Gabriel Venas SantosDepartment of Physical Therapy, Speech Therapy and Occupational Therapy, Faculty of Medical Science, University of São Paulo, São Paulo, Brazil.
André Frazão HeleneDepartment of Physiology, Institute of Biosciences, University of São Paulo, São Paulo, Brazil.
Antonio Carlos RoqueDepartment of Physics, School of Philosophy, Sciences and Letters of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil.
José Garcia Vivas MirandaLaboratory of Biosystems, Institute of Physics, Federal University of Bahia, Salvador, Brazil.
Maria Elisa Pimentel PiemonteDepartment of Physical Therapy, Speech Therapy and Occupational Therapy, Faculty of Medical Science, University of São Paulo, São Paulo, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Gait is one of the activities most affected by the symptoms of Parkinson's disease and may show a linear decline as the disease progresses. Early assessment of its performance through clinically relevant tests is a key factor in designing efficient therapeutic plans and procedures, which can be enhanced using simple and low-cost technological instruments. Objective: To investigate the effectiveness of a two-dimensional gait assessment to identify the decline in gait performance associated with Parkinson's disease progression. Methods: One hundred and seventeen people with Parkinson's disease, classified between early and intermediate stages, performed three clinical gait tests (Timed Up and Go, Dynamic Gait Index, and item 29 of the Unified Parkinson's Disease Rating Scale), in addition to a six-meter gait test recorded by a two-dimensional movement analysis software. Based on variables generated by the software, a gait performance index was created, allowing a comparison between its results with the results obtained by clinical tests. Results: There were differences between sociodemographic variables directly related to the evolution of Parkinson's disease. Compared to clinical tests, the index proposed to analyze gait showed greater sensitivity and was able to differentiate the first three stages of disease evolution (Hoehn and Yahr I and II: Conclusion: Based on the index provided by a two-dimensional movement analysis software that uses kinematic gait variables, it was possible to differentiate the gait performance decline among the three first stages of Parkinson's disease evolution. This study offers a promising possibility of early identification of subtle changes in an essential function of people with Parkinson's disease.

Indexed as

disease early detectiongaitindexParkinson’s diseasespatio–temporal analysis

Identifiers

PMID37153678
PMCPMC10155096

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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.