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Record W2135544878 · doi:10.1186/1748-717x-6-143

Spinal cord stimulators and radiotherapy: First case report and practice guidelines

2011· article· en· W2135544878 on OpenAlexaff
Lorraine Walsh, Daipayan Guha, Thomas G. Purdie, Philippe L. Bédard, Alexandra Easson, Fei‐Fei Liu, Mojgan Hodaie

Bibliographic record

VenueRadiation Oncology · 2011
Typearticle
Languageen
FieldMedicine
TopicPain Management and Treatment
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsMedicineRadiation therapySpinal cordSpinal cord stimulatorCardiac pacemakerAdjuvant radiotherapyRadiologyInternal medicineSpinal cord stimulation

Abstract

fetched live from OpenAlex

Spinal cord stimulators (SCS) are a well-recognised treatment modality in the management of a number of chronic neuropathic pain conditions, particularly failed back syndrome and radiculopathies. The implantable pulse generator (IPG) component of the SCS is designed and operates in a similar fashion to that of a cardiac pacemaker. The IPG consists of an electrical generator, lithium battery, transmitter/receiver and a minicomputer. When stimulated, it generates pulsed electrical signals which stimulate the dorsal columns of the spinal cord, thus alleviating pain. Analogous to a cardiac pacemaker, it can be potentially damaged by ionising radiation from a linear accelerator, in patients undergoing radiotherapy. Herein we report our clinical management of the first reported case of a patient requiring adjuvant breast radiotherapy who had a SCS in situ. We also provide useful practical recommendations on the management of this scenario within a radiation oncology department.

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)0.005
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 score0.011
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.002
Science and technology studies0.0030.002
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0110.004
Insufficient payload (model declined to judge)0.0090.004

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 head0.097
GPT teacher head0.426
Teacher spread0.329 · 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
Published2011
Admission routes1
Has abstractyes

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