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Record W3100196020 · doi:10.55038/kvg02786

Epidural Space Cervical Spine: Review of Traumatic and Non-Traumatic Epidural Pathologies

2025· article· en· W3100196020 on OpenAlexaff
Yasser Noorelahi, Ahmed Alharthy, Arwa Badeeb

Bibliographic record

VenueSaudi Journal of Radiology · 2025
Typearticle
Languageen
FieldEngineering
TopicMedical Imaging and Analysis
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsEpidural spaceMedicineCervical spineSurgeryTraumatic injuryEpidural abscessTraumatic brain injuryAnesthesia

Abstract

fetched live from OpenAlex

The spinal epidural space located between the dura matter and the vertebral bodies can be affected by various pathologies. Understanding the radiological anatomy and clinical relevance of this space is of crucial importance for diagnostic and interventional therapeutic purposes. The cervical epidural space is particularly important due to its proximity to the cervical spinal cord and exiting nerve roots, where early detection of pathologies can prevent catastrophic neurological complications. In this concise review, we highlight the anatomy of the cervical epidural space and its boundaries and content as well as normal variants that mimic pathology on imaging. We discuss common etiologies that affect this space including traumatic and non-traumatic causes and their radiological appearance. Furthermore, the utility of computed tomography (CT) and magnetic resonance imaging (MRI) will be highlighted. Among the most common diseases affecting the cervical epidural space anteriorly is herniated discs and posteriorly facet degenerative changes. Infections and neoplastic processes integral to the cervical epidural space will be discussed in detail.

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)0.001
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.011
GPT teacher head0.273
Teacher spread0.262 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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