Evidence map›Paper›PMID 41656377›Full record

Trial reportJournal of neurology2026

Construct validity of instrumented gait assessments in hospital and daily life mobility in patients with Parkinson's disease and atypical Parkinson's syndromes: an exploratory study.

I Teckenburg, V Sidoroff, H Moradi, S Sapienza, G Prigent, F Krismer, D Benninger, B Eskofier, M Regensburger, A Ibrahim and 7 more

Abstract readMulticenter StudyRandomized Controlled TrialValidation Study
In one paragraph

Trial report in Journal of neurology, 2026. 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. Review
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

17 authors.

I TeckenburgDepartment of Molecular Neurology, Uniklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
V SidoroffDepartment of Neurology, Medical University of Innsbruck, Innsbruck, Austria.
H MoradiDepartment Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
S SapienzaDigital Medicine, Luxembourg Center for System Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg.
G PrigentÉcole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
F KrismerDepartment of Neurology, Medical University of Innsbruck, Innsbruck, Austria.
D BenningerService of Neurology, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
B EskofierDepartment Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
M RegensburgerDepartment of Molecular Neurology, Uniklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
A IbrahimDepartment of Molecular Neurology, Uniklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
J KluckenDepartment of Molecular Neurology, Uniklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
K AminianÉcole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
G Wenning *Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria.
C RaccagniDepartment of Neurology, Provincial Hospital of Bolzano, Bolzano, Italy.
J WinklerDepartment of Molecular Neurology, Uniklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
H GaßnerDepartment of Molecular Neurology, Uniklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany. heiko.gassner@uk-erlangen.de.ORCID http://orcid.org/0000-0003-2037-9460
Mobility_APP Study Group

Funding

Austrian Science Fund I-4795Deutsche Forschungsgemeinschaft ES 434/12-1Deutsche Forschungsgemeinschaft KL 1395/10-1Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung SNF320030E_192211 / 1
6 · The paper itself

Abstract

BACKGROUND AND

aimParkinsonian disorders are hallmarked by gait and balance impairments. Atypical parkinsonian disorders (APD) develop postural instability with falls and gait disorders early on. Sensor-based gait recordings provide objective data in hospital and everyday life, improving mobility assessment accuracy. However, the impact of duration and distance of instrumented assessments on construct validity remains unclear. This exploratory study aims to evaluate the construct validity of gait assessments compared with clinical, functional, and patient-reported scores.

methodsThe multi-centered Mobility_APP study recruited 43 PD and 49 APD patients. Among others, the Berg Balance Scale (BBS) and the postural instability and gait difficulty score (PIGD) were collected. Sensor-based gait parameters were captured during standardized 2 × 10 m and 2-min walk tests (2MWT) in the hospital and for 1 day of physical activity monitoring (PAM) at home. PAM was categorized by short (10-30 s), medium (30-60 s), and long (≥ 60 s) walking bouts (WB). Spearman correlations were applied to investigate associations between scores.

resultsMean gait velocity (GV) and stride length correlated more strongly with functional, clinical, and patient-reported scores in 2MWT than in 2 × 10 m. Additionally, the GV variability in the 2MWT correlated with BBS and PIGD (r = │0.3-0.7│), but was less prominent in 2 × 10 m (r = │0.0-0.5│). In PAM, GV of long WB correlated more strongly with the PIGD (r = │0.5-0.6│) than short WB (r = │0.2-0.4│).

conclusionThe 2MWT tended to show the highest construct validity. PAM offered complementary but weaker correlations, highlighting that PAM provides novel insights into daily life mobility of APD patients.

Indexed as

Activities of Daily LivingGait AnalysisGait Disorders, NeurologicParkinson DiseaseParkinsonian DisordersAgedAged, 80 and overFemaleHumansMaleMiddle AgedReproducibility of ResultsAtypical parkinsonismGait analysisMobility assessmentParkinson’s diseaseWearable sensors

Identifiers

PMID41656377
PMCPMC12883511

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Registered trials

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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.