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Record W2596238141 · doi:10.1097/brs.0000000000002033

New Developments in Spinal Cord Stimulation

2017· review· en· W2596238141 on OpenAlexaff
Seth M. Zeidman

Bibliographic record

VenueSpine · 2017
Typereview
Languageen
FieldMedicine
TopicPain Management and Treatment
Canadian institutionsObject Research Systems (Canada)
Fundersnot available
KeywordsMedicineNeuromodulationStimulationNociceptionIntractable painChronic painSpinal cordSpinal cord stimulationSpinal cord stimulatorNeuropathic painDorsal root ganglionNeuroscienceAnesthesiaPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

Technological advances in spinal cord stimulation (SCS) represent some of the most exciting developments in pain management. The gate-control theory, which proposes that activation of non-nociceptive fibers prevents painful stimuli from reaching the thalamus, serves as the basis for SCS. Devices that deliver SCS have evolved over the years from large instruments with batteries lasting 3, 5, or 10 years—later with rechargeable batteries—to miniaturized devices with multiple smaller leads and configurations. This technique has proved particularly useful for patients with complex regional pain syndrome, who present some of the greatest challenges for physicians who seek to relieve patient pain. Symptoms of this disorder, including swelling, loss of motion, and extreme sensitivity to light touch, are tremendously relieved by SCS, and the Neuromodulation Therapy Access Coalition has assigned a Grade A recommendation supporting use of SCS for patients with complex regional pain syndrome. A new technique, dorsal root ganglion (DRG) stimulation, involves placement of the stimulator directly on the DRG through an epidural (inside out) approach and selective stimulation of different parts of the DRG, providing superior treatment outcomes for many patients. For patients who find the traditional paresthesias associated with tonic SCS to be very painful, even intolerable, and for those who have developed tolerance to SCS, revolutionary new treatments are proving tremendously successful in providing pain relief. Burst stimulation offers SCS placement at higher levels of the spine and use of alternative waveforms, in which neurons fire in bursts, followed by periods of dormancy, leading to pain reduction without painful paresthesias. In combination with conventional tonic stimulation, burst stimulation represents a comprehensive approach to effective pain management. Additional exciting developments in this field include (A) high-frequency SCS, a novel SCS system that allows a pulse rate up to 10 kHz with more efficient anatomic positioning, providing paresthesia-free pain relief; (B) percutaneous leads and paddles, which permit tailored stimulation patterns for patients with chronic pain; (C) magnetic resonance imaging-compatible SCS systems, which allow magnetic resonance imaging scans on hips, shoulders, back, and elsewhere, without concern about lead heating, device damage, unintentional stimulation, and magnetic pull; and (D) battery-free SCS, which transmits energy wirelessly from an external unit. Recent developments in the field of SCS and devices and approaches of the future, although not curative, are expected to continue to significantly relieve pain and promote activity postoperatively, and among those whose cause of pain cannot be identified, for better outcomes and improved quality of life.

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)0.003
metaresearch head score (Gemma)0.004
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: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0190.007

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 head0.204
GPT teacher head0.462
Teacher spread0.258 · 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
GenreReview

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

Citations4
Published2017
Admission routes1
Has abstractyes

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