Evidence map›Paper›PMID 41919631›Full record

ReviewMovement disorders : official journal of the Movement Disorder Society2026

Adaptive Deep Brain Stimulation for Parkinson's Disease: Navigating the Roadblocks to Clinical Implementation.

Thomas Koeglsperger, Maximilian Scherer, Andrea A Kühn, Alexandre Eusebio, Alfonso Fasano, Joachim K Krauss

Abstract readReview
In one paragraph

Review in Movement disorders : official journal of the Movement Disorder Society, 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. 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

6 authors.

Thomas KoeglspergerGerman Center for Neurodegenerative Diseases (DZNE), Munich, Germany.
Maximilian SchererDepartment of Neurology, LMU University Hospital, LMU Munich, Munich, Germany.ORCID https://orcid.org/0000-0002-5280-2828
Andrea A KühnBerlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany.
Alexandre EusebioAPHM, Department of Neurology and Movement Disorders, Timone University Hospital, Marseille, France.
Alfonso FasanoEdmond J Safra Program in Parkinson's disease and Morton and Gloria Shulman Movement Disorders Centre, Toronto Western Hospital, UHN and Division of Neurology, University of Toronto, Toronto, Ontario, Canada.ORCID https://orcid.org/0000-0001-5346-0180
Joachim K KraussDepartment of Neurosurgery, Hannover Medical School, Hannover, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adaptive deep brain stimulation (aDBS) represents an important evolution in the treatment of Parkinson's disease (PD), building on conventional DBS (cDBS) by adjusting stimulation in response to real-time physiological signals. By enabling dynamic targeting of disease-related neural activity, aDBS offers the potential for more precise modulation of motor symptoms. Additional anticipated advantages include reduced stimulation-related side effects and improved energy efficiency, supporting long-term device performance. Although clinical uptake is still at an early stage, growing experience has highlighted both opportunities and areas requiring further refinement. Key challenges include inter-individual variability in biomarker expression, diversity in programming approaches, and ongoing debate regarding optimal thresholds and response latencies. The clinical significance of short-term local field potential (LFP) recordings continues to be actively investigated, particularly in the context of signal artifacts, physiological variability, and current hardware limitations. Beyond technical considerations, factors such as patient selection, ethical frameworks, and cost-effectiveness remain important determinants of broader implementation. Continued progress will depend on the development of robust and flexible control strategies that incorporate multimodal biomarkers, including wearable-derived motor metrics and patient-reported outcomes, to support personalized therapy. With an expanding evidence base and recent regulatory approvals, aDBS is increasingly transitioning from an experimental concept to a viable clinical tool. Future efforts should prioritize the translation of research paradigms into scalable clinical workflows that effectively balance automation with individualized patient care. © 2026 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Indexed as

Deep Brain StimulationParkinson DiseaseHumansLocal Field Potential Measurementadaptive DBSbiomarkercontrol algorithmdeep brain stimulation (DBS)Parkinson's disease

Identifiers

PMID41919631
PMCPMC13307242

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.