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176 Deep Brain Stimulation of the Anterior Cingulate Cortex

2013· article· es· W2335753190 on OpenAlexaboutno aff
Erlick Pereira, Sandra Boccard, Liz Moir, James J. FitzGerald, Alexander L. Green, Tipu Z. Aziz

Bibliographic record

VenueNeurosurgery · 2013
Typearticle
Languagees
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAnterior cingulate cortexDeep brain stimulationNeuroscienceCingulate cortexStimulationCortex (anatomy)Internal medicinePsychiatryCentral nervous systemCognition

Abstract

fetched live from OpenAlex

INTRODUCTION: Deep brain stimulation (DBS) has shown considerable promise for relieving nociceptive and neuropathic symptoms of refractory chronic pain. We assessed the efficacy of a new target for the affective component of pain, the anterior cingulate cortex (ACC). METHODS: 15 patients (12 males and 3 females) with neuropathic pain underwent bilateral ACC DBS. Mean age at surgery was 49 [33-58] years. Patient reported outcome measures were collected before and after surgery, using a Visual Analogue Scale (VAS), Short Form 36 quality of life survey (SF-36), McGill pain questionnaire (MPQ) and EuroQol-5D questionnaires (EQ-5D; Health state). Electrode localisation was performed by registering postoperative CT to pre-operative MR in Montreal Neurological Institute space. RESULTS: Eleven patients (73.3 %) reported relief from their pain. Early post-surgery mean pain (VAS) was improved by 39.6% [P = .041], mean SF-36 score by 7.2%, mean MPQ score by 9.7%, mean EQ-5D score by 26.7% [P = .016] and their Health State by 14.0%. CONCLUSION: Affective ACC DBS can relieve chronic neuropathic pain refractory to pharmacotherapy and restore 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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.777

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
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)0.0010.000

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 head0.015
GPT teacher head0.254
Teacher spread0.239 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2013
Admission routes1
Has abstractyes

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