dc.contributor.author
Wenzel, Gregor R.
dc.contributor.author
Roediger, Jan
dc.contributor.author
Brücke, Christof
dc.contributor.author
Marcelino, Ana Luísa de A.
dc.contributor.author
Gülke, Eileen
dc.contributor.author
Pötter-Nerger, Monika
dc.contributor.author
Scholtes, Heleen
dc.contributor.author
Wynants, Kenny
dc.contributor.author
Juárez Paz, León M.
dc.contributor.author
Kühn, Andrea A.
dc.date.accessioned
2021-07-28T07:57:30Z
dc.date.available
2021-07-28T07:57:30Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/31288
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-31024
dc.description.abstract
BACKGROUND
Recent technological advances in deep brain stimulation (DBS) (e.g., directional leads, multiple independent current sources) lead to increasing DBS-optimization burden. Techniques to streamline and facilitate programming could leverage these innovations.
OBJECTIVE
We evaluated clinical effectiveness of algorithm-guided DBS-programming based on wearable-sensor-feedback compared to standard-of-care DBS-settings in a prospective, randomized, crossover, double-blind study in two German DBS centers.
METHODS
For 23 Parkinson's disease patients with clinically effective DBS, new algorithm-guided DBS-settings were determined and compared to previously established standard-of-care DBS-settings using UPDRS-III and motion-sensor-assessment. Clinical and imaging data with lead-localizations were analyzed to evaluate characteristics of algorithm-derived programming compared to standard-of-care. Six different versions of the algorithm were evaluated during the study and 10 subjects programmed with uniform algorithm-version were analyzed as a subgroup.
RESULTS
Algorithm-guided and standard-of-care DBS-settings effectively reduced motor symptoms compared to off-stimulation-state. UPDRS-III scores were reduced significantly more with standard-of-care settings as compared to algorithm-guided programming with heterogenous algorithm versions in the entire cohort. A subgroup with the latest algorithm version showed no significant differences in UPDRS-III achieved by the two programming-methods. Comparing active contacts in standard-of-care and algorithm-guided DBS-settings, contacts in the latter had larger location variability and were farther away from a literature-based optimal stimulation target.
CONCLUSION
Algorithm-guided programming may be a reasonable approach to replace monopolar review, enable less trained health-professionals to achieve satisfactory DBS-programming results, or potentially reduce time needed for programming. Larger studies and further improvements of algorithm-guided programming are needed to confirm these results.
en
dc.subject
deep brain stimulation
en
dc.subject
Parkinson’s disease
en
dc.subject
double-blind
en
dc.subject
subthalamic nucleus
en
dc.subject
wearable device feedback
en
dc.subject.ddc
600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit::610 Medizin und Gesundheit
dc.title
CLOVER-DBS: Algorithm-Guided Deep Brain Stimulation-Programming Based on External Sensor Feedback Evaluated in a Prospective, Randomized, Crossover, Double-Blind, Two-Center Study
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation.doi
10.3233/JPD-202480
dcterms.bibliographicCitation.journaltitle
Journal of Parkinson's Disease
dcterms.bibliographicCitation.originalpublishername
IOS Press
dcterms.rightsHolder.note
Copyright applies in this work.
dcterms.rightsHolder.url
https://www.iospress.nl/service/authors/permission-to-post-pre-print-post-print-and-publishers-pdf-articles/
refubium.affiliation
Charité - Universitätsmedizin Berlin
refubium.note.author
Original article first published: 2021-06-12.
en
refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.bibliographicCitation.pmid
34151855
dcterms.isPartOf.issn
1877-7171
dcterms.isPartOf.eissn
1877-718X