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Record W2752684758 · doi:10.2176/nmccrj.cr.2016-0152

Surgical Treatment of Rotational Vertebral Artery Syndrome Induced by Spinal Tumor: A Case Report and Literature Review

2017· article· en· W2752684758 on OpenAlexaff
Shoichi Haimoto, Yusuke Nishimura, Masahito Hara, Yuu Yamamoto, Toshiki Fukuoka, Ryuichi Fukuyama, Toshihiko Wakabayashi, Howard J. Ginsberg

Bibliographic record

VenueNMC Case Report Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicSpinal Fractures and Fixation Techniques
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineNeck painRadiologyVertebral arterySurgery

Abstract

fetched live from OpenAlex

Vertebrobasilar insufficiency (VBI) provoked by physiological head rotation is known as rotational vertebral artery syndrome (RVAS) or Bow Hunter syndrome. RVAS most often occurs at C1-2 level with head rotation and presents with symptoms of VBI. Several previously published studies have reported RVAS at subaxial sites (V2 segment), however, tumor-induced RVAS has never been reported. The authors report the first case of RVAS at V2 segment due to compression from a spinal tumor. A 71-year-old man presented with symptoms of dizziness provoked by head rotation or neck extension. computed tomography (CT) angiography and dynamic cerebral angiography revealed circumferential stenosis with neutral neck position and complete occlusion of the left dominant vertebral artery (VA) at C5 level with his neck extended or rotated to the left. Complete neurological recovery was achieved after removal of a spinal osteochondroma and surgical decompression of the left VA via an anterior approach. Spinal tumors should be included in the differential diagnosis in cases of RVAS. Spinal degenerations or sarcomatous transformation of the tumor could lead to clinical manifestations of RVAS in cases with spinal osteochondroma. Complete removal of the tumor with or without spinal fusion would be the treatment of choice, in addition to medical treatment in the cases of acute stroke.

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)0.001
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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.642

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.361
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 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

Citations12
Published2017
Admission routes1
Has abstractyes

Explore more

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