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Record W3014020000 · doi:10.1186/s42234-020-00041-9

Spinal cord stimulation in Parkinson’s disease: a review of the preclinical and clinical data and future prospects

2020· review· en· W3014020000 on OpenAlex
Yi Cai, Rajiv Reddy, Vishal Varshney, Krishnan Chakravarthy

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBioelectronic Medicine · 2020
Typereview
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSpinal cord stimulationNeuroscienceParkinson's diseaseMedicineSpinal cordDiseaseStimulationPhysical medicine and rehabilitationPsychologyPathology

Abstract

fetched live from OpenAlex

Parkinson's disease (PD) is a progressive neurodegenerative disease with an incidence of 0.1 to 0.2% over the age of 40 and a prevalence of over 1 million people in North America. The most common symptoms include tremor, bradykinesia, rigidity, pain, and postural instability, with significant impact in quality of life and mortality. To date there is ongoing research to determine the optimum therapy for PD. In this review we analyze the current data in the use of spinal cord stimulation (SCS) therapy for treatment for Parkinsonian symptoms. We specifically address waveform pattern, anatomic location and the role of spinal cord stimulation (SCS) as a salvage therapy after deep brain stimulation (DBS) therapy. We also outline current experimental evidence from preclinical research highlighting possible mechanisms of beneficial effects of SCS in this context. Though the use of SCS therapy is in its infancy for treatment of PD, the data points to an exciting area for ongoing research and exploration with positive outcomes from both cervical and thoracic tonic and BURSTDR spinal cord stimulation.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.941
Threshold uncertainty score0.691

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.146
GPT teacher head0.462
Teacher spread0.316 · 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