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Burst Spinal Cord Stimulation

2010· article· en· W1989755128 on OpenAlexfundaboutno aff
Dirk De Ridder, Sven Vanneste, Mark Plazier, Elsa van der Loo, Tomas Menovsky

Bibliographic record

VenueNeurosurgery · 2010
Typearticle
Languageen
FieldMedicine
TopicPain Management and Treatment
Canadian institutionsnot available
FundersMcGill University
KeywordsMedicineStimulationNeuropathic painSpinal cord stimulationTonic (physiology)AnesthesiaVisual analogue scaleSpinal cordChronic painBurstingNeurosciencePhysical therapyInternal medicinePsychology

Abstract

fetched live from OpenAlex

INTRODUCTION: Spinal cord stimulation is commonly used for neuropathic pain modulation. The major side effect is the onset of paresthesia. The authors describe a new stimulation design that suppresses pain as well as, or even better than, the currently used stimulation, but without creating paresthesia. METHODS: A spinal cord electrode (Lamitrode) for neuropathic pain was implanted in 12 patients via laminectomy: 4 at the C2 level and 7 at the T8-T9 level for cervicobrachialgia and lumboischialgia, respectively (1 at T11 at another center). During external stimulation, the patients received the classic tonic stimulation (40 or 50 Hz) and the new burst stimulation (40-Hz burst with 5 spikes at 500 Hz per burst). RESULTS: Pain scores were measured using a visual analog scale and the McGill Short Form preoperatively and during tonic and burst stimulation. Paresthesia was scored as present or not present. Burst stimulation was significantly better for pain suppression, by both the visual analog scale score and the McGill Short Form score. Paresthesia was present in 92% of patients during tonic stimulation, and in only 17% during burst stimulation. Average follow-up was 20.5 months. CONCLUSION: The authors present a new method of spinal cord stimulation using bursts that suppress neuropathic pain without the mandatory paresthesia. Pain suppression seems as good as or potentially better than that achieved with the currently used stimulation. Average follow-up after nearly 2 years (20.5 months) suggests that this stimulation design is stable.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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)0.0080.002

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 head0.033
GPT teacher head0.303
Teacher spread0.271 · 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 designNot applicable
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

Citations377
Published2010
Admission routes2
Has abstractyes

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