Evidence map›Paper›PMID 40593773›Full record

ArticleNPJ Parkinson's disease2025

Digital speech biomarkers can measure acute effects of levodopa in Parkinson's disease.

M Sousa, P Krýže, D Amstutz, K Petermann, A Averna, M Castelli, A D Magalhães, A Jorge, J Švihlík, T Tykalová and 10 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NPJ Parkinson's disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

1 citing paper in PubMed.

  1. Article
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

20 authors.

M SousaDepartment of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland. mario.sousa@insel.ch.
P KrýžeDepartment of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
D AmstutzDepartment of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland.
K PetermannDepartment of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland.
A AvernaDepartment of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland.
M CastelliARTORG Center for Biomedical Engineering Research, Gerontechnology and Rehabilitation, University of Bern, Bern, Switzerland.
A D MagalhãesDepartment of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland.
A JorgeDepartment of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland.
J ŠvihlíkDepartment of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
T TykalováDepartment of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
V IllnerDepartment of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
M E Maradan-GachetDepartment of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland.
A A DiamantarasDepartment of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland.
J WaskönigDepartment of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland.
M L LachenmayerDepartment of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland.
I DeboveDepartment of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland.
G TinkhauserDepartment of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland.
T NefARTORG Center for Biomedical Engineering Research, Gerontechnology and Rehabilitation, University of Bern, Bern, Switzerland.
J Rusz *Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
P Krack *Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland.

Funding

Grantová Agentura České Republiky grant no. 21-14216LNational Institute for Neurological Research Programme EXCELES, ID Project No. LX22NPO5107Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung SNF 32003BL_197709
6 · The paper itself

Abstract

Speech abnormalities in Parkinson's disease (PD) are heterogeneous and often considered resistant to levodopa. However, human hearing may miss subtle treatment-related speech changes. Digital speech biomarkers offer a sensitive alternative to measure such changes objectively. Speech was recorded in 51 PD patients during ON and OFF medication states and compared to 43 healthy controls matched for language and gender. Acute levodopa effects were significant in prosodic (F0 standard deviation, p = 0.03, effect size = 0.47), respiratory (intensity slope, p = 0.02, effect size = 0.49), and spectral domains (LTAS mean, p = 0.01, effect size = 0.35). Stepwise backward regression identified 8 biomarkers reflecting hypokinetic symptoms, 6 for dyskinetic symptoms, and 7 for medication-state transitions. Hypokinetic compound score correlated strongly with MDS-UPDRS-III changes (r = 0.70; MAE = 6.06/92), and the dyskinetic compound score with dyskinesia ratings (r = 0.50; MAE = 1.81/12). Medication-state transitions were detected with AUC = 0.86. This study highlights the potential of digital speech biomarkers to objectively measure levodopa-induced changes in PD symptoms and medication states.

Identifiers

PMID40593773
PMCPMC12217330

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.