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Record W2034015635 · doi:10.1155/2013/293826

Utility of Stellate Ganglion Block in Atypical Facial Pain: A Case Report and Consideration of Its Possible Mechanisms

2013· article· en· W2034015635 on OpenAlexaff
Harsha Shanthanna

Bibliographic record

VenueCase Reports in Medicine · 2013
Typearticle
Languageen
FieldMedicine
TopicPain Management and Treatment
Canadian institutionsHealth Sciences CentreMcMaster University Medical Centre
Fundersnot available
KeywordsMedicineStellate ganglionPostherpetic neuralgiaNeuropathic painAnesthesiaChronic painPhysical therapyPathology

Abstract

fetched live from OpenAlex

We present this report of a young patient with chronic severe atypical facial pain who was successfully controlled with stellate ganglion block under ultrasound guidance. The patient had a history of severe disabling, unilateral, facial neuropathic pain with minimal response to analgesic medications. Upon assessment the patient had features suggestive of trigeminal neuralgia, although postherpetic neuralgia could not be ruled out. As a diagnostic test intervention, stellate ganglion block was tried under ultrasound guidance. The patient showed significant improvement in pain control and functional disability lasting beyond 10 weeks. Subsequent blocks reinforced the analgesia. Atypical facial pain has several differential diagnoses. The involvement of sympathetic system in its causation or sustenance is uncertain. Stellate ganglion block achieves sympathetic block of cervicofacial structures, and its blockade has been shown to affect chronic pain conditions. Although its mechanism is not clear, one has to consider its possible role in conditions of stress apart from directly controlling the sympathetic activity. There is certainly a role in exploring the potential benefits of stellate ganglion block in such clinical conditions. The technique of stellate block under ultrasound is also described, as it influences the safety and precision of the block.

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)0.002
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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.470

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.032
GPT teacher head0.297
Teacher spread0.266 · 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 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

Citations15
Published2013
Admission routes1
Has abstractyes

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