Evidence map›Paper›PMID 38610081›Full record

ArticleMovement disorders clinical practice2024

3D Kinematics Quantifies Gait Response to Levodopa earlier and to a more Comprehensive Extent than the MDS-Unified Parkinson's Disease Rating Scale in Patients with Motor Complications.

Raquel Barbosa, Marcelo Mendonça, Paulo Bastos, Patrícia Pita Lobo, Anabela Valadas, Leonor Correia Guedes, Joaquim J Ferreira, Mário Miguel Rosa, Ricardo Matias, Miguel Coelho

Open access · greenAbstract read
In one paragraph

Article in Movement disorders clinical practice, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
2.2field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 3 countries.

Raquel BarbosaNeurology Deparment, Centre Hospitalier Universitaire Toulouse, Toulouse, France.ORCID https://orcid.org/0000-0002-3138-2975
Marcelo MendonçaNova Medical School, Faculdade de Ciências Medicas, Universidade Nova de Lisboa, Lisbon, Portugal.ORCID https://orcid.org/0000-0003-3587-8553
Paulo BastosNeurology Deparment, Centre Hospitalier Universitaire Toulouse, Toulouse, France.ORCID https://orcid.org/0000-0002-1195-3611
Patrícia Pita LoboDepartment of Neurosciences and Mental Health, Neurology Hospital Santa Maria, CHLUN, Lisbon, Portugal.
Anabela ValadasDepartment of Neurosciences and Mental Health, Neurology Hospital Santa Maria, CHLUN, Lisbon, Portugal.
Leonor Correia GuedesDepartment of Neurosciences and Mental Health, Neurology Hospital Santa Maria, CHLUN, Lisbon, Portugal.
Joaquim J FerreiraInstituto de Medicina Molecular João Lobo Antunes, Faculty of Medicine, University of Lisbon, Lisbon, Portugal.
Mário Miguel RosaDepartment of Neurosciences and Mental Health, Neurology Hospital Santa Maria, CHLUN, Lisbon, Portugal.
Ricardo MatiasPhysics Department & Institute of Biophysics and Biomedical Engineering (IBEB), Faculty of Sciences, University of Lisbon, Lisbon, Portugal.
Miguel CoelhoDepartment of Neurosciences and Mental Health, Neurology Hospital Santa Maria, CHLUN, Lisbon, Portugal.
University of Lisbon · PTCentre Hospitalier Universitaire de Toulouse · FRChampalimaud Foundation · PT

Funding

Fundação para a Ciência e a Tecnologia SFRH/BD/143797/2019Santa Casa da Misericórdia de Lisboa
6 · The paper itself

Abstract

backgroundQuantitative 3D movement analysis using inertial measurement units (IMUs) allows for a more detailed characterization of motor patterns than clinical assessment alone. It is essential to discriminate between gait features that are responsive or unresponsive to current therapies to better understand the underlying pathophysiological basis and identify potential therapeutic strategies.

objectivesThis study aims to characterize the responsiveness and temporal evolution of different gait subcomponents in Parkinson's disease (PD) patients in their OFF and various ON states following levodopa administration, utilizing both wearable sensors and the gold-standard MDS-UPDRS motor part III.

methodsSeventeen PD patients were assessed while wearing a full-body set of 15 IMUs in their OFF state and at 20-minute intervals following the administration of a supra-threshold levodopa dose. Gait was reconstructed using a biomechanical model of the human body to quantify how each feature was modulated. Comparisons with non-PD control subjects were conducted in parallel.

resultsSignificant motor changes were observed in both the upper and lower limbs according to the MDS-UPDRS III, 40 minutes after levodopa intake. IMU-assisted 3D kinematics detected significant motor alterations as early as 20 minutes after levodopa administration, particularly in upper limbs metrics. Although all "pace-domain" gait features showed significant improvement in the Best-ON state, most rhythmicity, asymmetry, and variability features did not.

conclusionIMUs are capable of detecting motor alterations earlier and in a more comprehensive manner than the MDS-UPDRS III. The upper limbs respond more rapidly to levodopa, possibly reflecting distinct thresholds to levodopa across striatal regions.

Indexed as

Antiparkinson AgentsGaitLevodopaParkinson DiseaseAgedBiomechanical PhenomenaFemaleGait Disorders, NeurologicHumansMaleMiddle AgedSeverity of Illness IndexAntiparkinson AgentsLevodopagaitkinematic analysislevodopa challenge testParkinson's diseasewearable devices

Identifiers

PMID38610081
PMCPMC11233852
OpenAlexW4394785478

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.