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Record W3041194932 · doi:10.1017/cjn.2020.143

Spinal Cord Stimulation Therapy for Gait Dysfunction in Two Corticobasal Syndrome Patients

2020· article· en· W3041194932 on OpenAlexaffvenue
Olivia Samotus, Andrew G. Parrent, Mandar Jog

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2020
Typearticle
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsLondon Health Sciences CentreLawson Health Research InstituteWestern University
Fundersnot available
KeywordsPhysical medicine and rehabilitationMedicineStimulationContent (measure theory)Spinal cordPsychologyPhysical therapyNeuroscience

Abstract

fetched live from OpenAlex

dysfunction, Neuromodulation, Spinal cord stimulationGait impairments such as freezing of gait (FOG) and postural instability are frequently described in corticobasal syndrome (CBS) patients.1 CBS parkinsonism is typically levodopa resistant, and there are currently no effective treatments or any disease-modifying therapies.1 Thus, there is a significant unmet need for an effective gait therapy.Tonic spinal cord stimulation (SCS) has shown significant promise for improving gait impairments and reducing FOG episodes in advanced Parkinson's disease patients with levodopa-resistant gait difficulties.2,3 As these axial gait features are also observed in CBS, the effect of SCS was investigated over 12 months in a convenience sampling of two CBS participants (~3 years with disease) who had significant gait impairment while OFF-and ON-levodopa medication.This monocentric, investigational, pilot study was approved by the Western University Research Ethics Board (REB#107451) and registered at ClinicalTrials.gov(NCT03079310).Participants recruited from the London Movement Disorders Centre provided signed informed consent.Due to the limited availability of SCS devices allocated for off-label use in our center, we explored the use of SCS in two participants with clinically certain CBS that met international criteria, 4 resistant gait disorder, and significant FOG.Neither participants had a history of stroke, spinal disorders nor any other neurological diseases, significant cognitive impairment, chronic back and/or lower limb pain and were not on unstable pharmacological treatment.Although physiotherapy (PT) regimes were not part of the study protocol, PT was not effective for gait in either participants.However, prior to study recruitment, Case I continued in-home PT for home safety and range of motion exercises.Endpoints were assessed before surgery and at 3, 6, and 12 months of SCS use while OFF (≥12 h) and ON (150% of usual morning dose) levodopa.Primary endpoint was the change in spatiotemporal parameters (STPs) during self-paced walking on the ProtoKinetics Walkway.Sensors embedded in the walkway detect footfalls in real time which are captured by the Protokinetics Movement Analysis Software (PKMAS) program.PKMAS provides accurate and validated measurements of various gait parameters.Gait asymmetry and variability (CV%) values were calculated by averaging step length and stride velocity measures.FOG episodes were analyzed using foot pressure changes as previously described.2 Secondary endpoints were MDS-UPDRS part III, comprehensive apraxia upper limb assessment, 5 freezing of gait questionnaire (FOG-Q), and activities-specific balance confidence scale (ABC). 2 Two electrodes with eight contacts/lead (Boston Scientific ® Precision Novi) were implanted in the medial, epidural space of T8-T10 spinal segments.2 Electrode localization was confirmed by paresthesias fully covering the lower trunk, both lower extremities and feet.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.059
GPT teacher head0.314
Teacher spread0.255 · 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

Citations6
Published2020
Admission routes2
Has abstractyes

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