Evidence map›Paper›PMID 40761234›Full record

ArticleClinical parkinsonism & related disorders2025

Speech subtypes are associated with worsened tremor and axial symptoms in Parkinson's disease patients.

Vanessa Brzoskowski Dos Santos, Rafaela Ravazio, Daniel Teixeira-Dos-Santos, Artur Francisco Schumacher Schuh, Christian Mattjie, Joana M Pasquali, Mauricia Denise de Borba, Rodrigo C Barros, Maira Rozenfeld Olchik

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Article in Clinical parkinsonism & related disorders, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Vanessa Brzoskowski Dos SantosPostgraduate Program in Medicine, Medical Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.
Rafaela RavazioMachine Learning Theory and Applications Lab, School of Technology, Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS), Porto Alegre, RS, Brazil.
Daniel Teixeira-Dos-SantosPostgraduate Program in Medicine, Medical Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.
Artur Francisco Schumacher SchuhPostgraduate Program in Medicine, Medical Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.
Christian MattjieMachine Learning Theory and Applications Lab, School of Technology, Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS), Porto Alegre, RS, Brazil.
Joana M PasqualiMachine Learning Theory and Applications Lab, School of Technology, Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS), Porto Alegre, RS, Brazil.
Mauricia Denise de BorbaFaculty of Medicine, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.
Rodrigo C BarrosMachine Learning Theory and Applications Lab, School of Technology, Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS), Porto Alegre, RS, Brazil.
Maira Rozenfeld OlchikPostgraduate Program in Medicine, Medical Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Parkinson's disease (PD) is a heterogeneous disorder, suggesting the presence of distinct subtypes. Speech data, though easy to collect, remains underutilized in subtyping PD. Methods: Cross-sectional study with PD patients recruited from the Movement Disorders Outpatient Clinic of the Neurology Service at the University Hospital in Porto Alegre, Brazil. We included participants diagnosed with idiopathic PD and excluded participants with other disorders that could affect speech. Clinical and sociodemographic data were collected alongside MDS-UPDRS Parts II and III motor assessments. Tremor and gait-posture scores were derived from specific MDS-UPDRS items, with additional data on Deep Brain Stimulation (DBS) status and Levodopa Equivalent Daily Dose (LEDD). The tasks diadochokinesis (DDK) and monologue were recorded and acoustically analyzed using software. We compared our identified clusters using clinical data through an analysis of covariance adjusted for age, sex, and disease duration. Results: Ninety individuals with PD were included, with 61.2 (± 9.4) years old, 13.6 (± 6.6) disease duration, and 47.6 (± 10) age at onset. We identified three speech groups with strong separation between them, comprising 49 (mild), 13 (moderate), and 29 (severe) patients. Tremor and postural-gait stability scores differed significantly across the three clusters, with cluster 3 exhibiting higher tremor (13.42 ± 10.66 vs. 7.09 ± 6.62, p = 0.020) and greater postural-gait instability (10.25 ± 6.69 vs. 5.46 ± 4.91, p = 0.009) than cluster 1. These differences weren't explainable by distinct age, sex, or disease duration. Conclusion: Our speech-based clustering algorithm effectively differentiated Parkinson's disease subtypes in this sample, identifying distinct groups based on tremor and axial symptoms.

Indexed as

Machine learningParkinson’s diseaseSpeech acousticsSpeech disorders

Identifiers

PMID40761234
PMCPMC12320695

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