Evidence map›Paper›PMID 33870190›Full record

ArticleBrain communications2021

Sign-specific stimulation 'hot' and 'cold' spots in Parkinson's disease validated with machine learning.

Alexandre Boutet, Jurgen Germann, Dave Gwun, Aaron Loh, Gavin J B Elias, Clemens Neudorfer, Michelle Paff, Andreas Horn, Andrea A Kuhn, Renato P Munhoz and 5 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Brain communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.5field-weighted citation impact, top 9% of its field
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

13 citing papers in PubMed, 27 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Advances in Technical Aspects of Deep Brain Stimulation Surgery.Stereotactic and functional neurosurgery · 2023
    Review
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  8. Article
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  11. Review
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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

15 authors at 4 institutions in 2 countries.

Alexandre BoutetJoint Department of Medical Imaging, University of Toronto, Toronto, ON, Canada.ORCID https://orcid.org/0000-0001-6942-5195
Jurgen GermannUniversity Health Network, Toronto, ON, Canada.ORCID https://orcid.org/0000-0003-0995-8226
Dave GwunUniversity Health Network, Toronto, ON, Canada.
Aaron LohUniversity Health Network, Toronto, ON, Canada.
Gavin J B EliasUniversity Health Network, Toronto, ON, Canada.
Clemens NeudorferUniversity Health Network, Toronto, ON, Canada.ORCID https://orcid.org/0000-0002-3153-1045
Michelle PaffUniversity Health Network, Toronto, ON, Canada.
Andreas HornDepartment of Neurology, Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Germany.ORCID https://orcid.org/0000-0002-0695-6025
Andrea A KuhnDepartment of Neurology, Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Germany.
Renato P MunhozEdmond J. Safra Program in Parkinson's Disease, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, UHN, Division of Neurology, University of Toronto, Toronto, ON, Canada.
Suneil K KaliaUniversity Health Network, Toronto, ON, Canada.
Mojgan HodaieUniversity Health Network, Toronto, ON, Canada.ORCID https://orcid.org/0000-0001-6278-4929
Walter KucharczykJoint Department of Medical Imaging, University of Toronto, Toronto, ON, Canada.
Alfonso FasanoEdmond J. Safra Program in Parkinson's Disease, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, UHN, Division of Neurology, University of Toronto, Toronto, ON, Canada.ORCID https://orcid.org/0000-0001-5346-0180
Andres M LozanoUniversity Health Network, Toronto, ON, Canada.
University Health Network · CAUniversity of Toronto · CAGerman Center for Neurodegenerative Diseases · DEHumboldt-Universität zu Berlin · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Deep brain stimulation of the subthalamic nucleus has become a standard therapy for Parkinson's disease. Despite extensive experience, however, the precise target of optimal stimulation and the relationship between site of stimulation and alleviation of individual signs remains unclear. We examined whether machine learning could predict the benefits in specific Parkinsonian signs when informed by precise locations of stimulation. We studied 275 Parkinson's disease patients who underwent subthalamic nucleus deep brain stimulation between 2003 and 2018. We selected pre-deep brain stimulation and best available post-deep brain stimulation scores from motor items of the Unified Parkinson's Disease Rating Scale (UPDRS-III) to discern sign-specific changes attributable to deep brain stimulation. Volumes of tissue activated were computed and weighted by (i) tremor, (ii) rigidity, (iii) bradykinesia and (iv) axial signs changes. Then, sign-specific sites of optimal ('hot spots') and suboptimal efficacy ('cold spots') were defined. These areas were subsequently validated using machine learning prediction of sign-specific outcomes with in-sample and out-of-sample data (

Indexed as

deep brain stimulationmachine learningneuroimagingParkinson’s diseasesubthalamic nucleus

Identifiers

PMID33870190
PMCPMC8042250
OpenAlexW3138575188

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.