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Record W4409566898 · doi:10.1002/mdc3.70087

Stimulation‐Induced Dyskinesia in <scp>STN DBS</scp> Patients

2025· article· en· W4409566898 on OpenAlexafffund
Carolina Candeias da Silva, Wilson Fung, Duha Al‐Shorafat, Aaron Loh, Brendan Santyr, Suneil K. Kalia, Andrés M. Lozano, Alfonso Fasano

Bibliographic record

VenueMovement Disorders Clinical Practice · 2025
Typearticle
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsOntario Brain InstituteToronto Western HospitalUniversity of Toronto
FundersUniversity of TorontoUniversity Health Network
KeywordsDeep brain stimulationDyskinesiaSubthalamic nucleusMedicineParkinson's diseaseDopaminergicStimulationAnesthesiaNeurosciencePhysical medicine and rehabilitationInternal medicineDiseasePsychologyDopamine

Abstract

fetched live from OpenAlex

BACKGROUND: Stimulation-induced dyskinesia (SID) is a poorly studied and usually transient manifestation of subthalamic deep brain stimulation (STN DBS) for Parkinson's disease (PD), which can be troubling for patients. OBJECTIVES: The aim of our study was to describe the features and management of SID in PD patients undergoing STN DBS. METHODS: We conducted a retrospective study among 86 STN DBS patients. Clinical features and volume of tissue activated (VTA) were correlated to SID occurrence. RESULTS: SID was identified in 28 (32.6%) patients and persisted for 6 months in six patients (7.0%). VTA overlap with the right motor STN was associated (P < 0.02) with SID. Weaning dopaminergic drugs and reducing the DBS amplitude were the most used strategies to control SID. CONCLUSIONS: SID is a relatively common complication of STN DBS and can be persistent. It often requires specific postoperative management strategies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.034
GPT teacher head0.388
Teacher spread0.354 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2025
Admission routes2
Has abstractyes

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