MétaCan
Menu
Back to cohort
Record W3095692837 · doi:10.1002/mdc3.13111

Functional Dyskinesias following Subthalamic Nucleus Deep Brain Stimulation in Parkinson's Disease: A Report of Three Cases

2020· article· en· W3095692837 on OpenAlexafffund
Ricardo Maciel, Carlos Zúñiga‐Ramírez, Renato P. Munhoz, Mateusz Zurowski, Alfonso Fasano

Bibliographic record

VenueMovement Disorders Clinical Practice · 2020
Typearticle
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsOntario Brain InstituteToronto Western Hospital
FundersUniversity Health Network
KeywordsDeep brain stimulationChoreaPsychogenic diseaseSubthalamic nucleusMovement disordersParkinson's diseaseDystoniaMedicineStimulationDyskinesiaPallidotomyAnesthesiaThalamic stimulatorPsychologyNeurosciencePhysical medicine and rehabilitationDiseaseInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Functional (psychogenic) dyskinesias in patients with Parkinson's disease (PD) are exceedingly rare. CASES: Herein we report three patients with PD who presented with functional dyskinesias in the first 3 months after subthalamic nucleus deep brain stimulation (DBS). All patients presented with chorea mimicking levodopa or stimulation-induced dyskinesias in the first 24 hours following stimulation adjustment. Two patients had generalized chorea and one, hemichorea. In all patients the abnormal movements could be induced or resolved with placebo/nocebo changes to the stimulation parameters. Following the diagnosis of a functional movement disorder (FMD), all patients improved with appropriate management. CONCLUSIONS: Functional chorea following DBS might mimic organic dyskinesias in PD but can be accurately diagnosed using suggestibility and placebo responses to sham stimulation adjustments. Recognizing the presence of FMD following DBS is important for proper management of these patients.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0030.003
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.074
GPT teacher head0.365
Teacher spread0.290 · 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 designCase report
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

Citations7
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueMovement Disorders Clinical PracticeSame topicNeurological disorders and treatmentsFrench-language works237,207