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Multimodal mapping of balance dysfunction in Parkinson's disease: a consensus roadmap for research and intervention.

Multimodal mapping of balance dysfunction in Parkinson's disease: a consensus roadmap for research and intervention.

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US · Author affiliation · country only

Department of Neurology, University Hospitals, Cleveland, Ohio, USA.
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London, GB · Author affiliation

Department of Clinical and Movement Neuroscience, Queen Square Institute of Neurology, University College of London, London, UK.
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Nijmegen, NL · Author affiliation

Department of Neurology, Radboud University Medical Centre, Nijmegen, The Netherlands.
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Ann Arbor, US · Author affiliation

University of Michigan Udall Center of Excellence in Parkinson's Research, University of Michigan, Ann Arbor, Michigan, USA.
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Vancouver, CA · Author affiliation

School of Kinesiology, University of British Columbia, Vancouver, British Columbia, Canada.
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Leuven, BE · Author affiliation

Research Group for Neurorehabilitation, University Paris, Leuven, Belgium.
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IE · Author affiliation · country only

School of Psychology, Queen's University Belfast, Belfast, Ireland.
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Atlanta, US · Author affiliation

Jean and Paul Amos Parkinson's Disease and Movement Disorder Program, Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, USA.
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Milan, IT · Author affiliation

IRCCS Humanitas Research Hospital, Milan, Italy.
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Hamburg, DE · Author affiliation

Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
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Tel Aviv, IL · Author affiliation

Center for the Study of Movement, Cognition, and Mobility (CMCM), Neurological Institute Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
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Oregon, US · Author affiliation

Department of Neurology, Oregon Health & Science University, Portland, Oregon, USA.
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Faridabad, IN · Author affiliation

Department of Neurology, Amrita Hospital and Research Center, Faridabad, Haryana, India.
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Montréal, CA · Author affiliation

Faculty of Education, McGill University, Montreal, Quebec, Canada.
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Québec, CA · Author affiliation

Faculty of Education, McGill University, Montreal, Quebec, Canada.
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New York City, US · Author affiliation

Departments of Neurology and Ophthalmology, Grossman School of Medicine, New York University, New York, New York, USA.
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Little Rock, US · Author affiliation

Department of Neurology and Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA.
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Original abstract

PURPOSE OF REVIEW: Balance depends on accurate perception of self-motion and verticality and on multisensory integration for stance, and gait. In Parkinson's disease, balance is commonly impaired and variably affected by treatment. Although vestibular and multisensory contributions are increasingly recognized, progress is limited by fragmented evidence, inconsistent methods, and artifact-prone measures. We provide a consensus roadmap across four domains - video-oculography/vHIT, VEMPs, posturography, and perceptual paradigms - to improve clinical translation of balance research in Parkinson's disease. RECENT FINDINGS: An interdisciplinary taskforce conducted a comprehensive literature review and a modified Delphi process (≥80% agreement), using virtual meetings, surveys, and an in-person consensus session. Oculography/vHIT shows largely preserved aVOR in Parkinson's disease but is vulnerable to Parkinson's disease specific artifacts, requiring standardization. VEMPs relate to brainstem and non-motor features but are limited by EMG-dependent confounds. Posturography reveals impaired multisensory integration with visual dependence and cholinergic contributions; reactive-capacity measures outperform sway alone. Perceptual paradigms show task-specific distortions and increased variability linked to axial/postural syndromes. SUMMARY: This consensus offers a practical roadmap, de-emphasize aVOR/vHIT as primary unsteadiness outcomes; use VEMPs as ancillary measures; prioritize posturography probing adaptability and reactive stepping; integrate wearables and neurochemical imaging; and adopt consortium-level minimum datasets to enable reproducible, phenotype-aware advances in Parkinson's disease balance research.

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