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T1-T2 Disk Herniation Presenting With Horner Syndrome: A Case Report With Literary Review

2018· article· en· W2909885440 on OpenAlexaff
Daniel R. Possley, S. Brandon Luczak, Andrew Angus, David Montgomery

Bibliographic record

VenueJAAOS Global Research and Reviews · 2018
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsObject Research Systems (Canada)
Fundersnot available
KeywordsMedicineHorner syndromeForaminotomySurgeryAnisocoriaMiosisAnhidrosisParesisLaminectomyCorpectomyThoracic outlet syndromeSpinal cordPupilAnesthesiaDecompression

Abstract

fetched live from OpenAlex

Horner syndrome or oculosympathetic paresis is caused by interruption of the sympathetic nerve supply to the face and eye that manifests as facial anhidrosis, blepharoptosis, and miosis. This sympathetic pathway begins in the hypothalamus and synapses in the intermediolateral gray substance of the spinal cord at C8-T2 levels making it susceptible to disruption via a high thoracic intervertebral disk herniation. We present a rare case of a patient with T1-T2 intervertebral disk herniation and Horner syndrome who was treated surgically. After confirming the diagnosis with MRI, the patient was treated with standard posterior approach with laminoforaminotomy and diskectomy. Although posterior approach surgery is most commonly used for laminectomy and/or foraminotomy, successful anterior approaches to upper thoracic lesions are valid as well. Our patient had resolution of his back pain, paresthesias, and grip weakness at 6 weeks postoperatively, but his Horner syndrome persisted at latest follow-up. Patients with cervical radiculopathy symptoms and physical examination findings consistent with Horner syndrome should be evaluated with a MRI that includes the upper thoracic spine. An accurate diagnosis and timely surgical intervention may provide the patient the best chance for regression of symptoms and a satisfactory outcome.

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 score0.251
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.094
GPT teacher head0.443
Teacher spread0.349 · 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

Citations5
Published2018
Admission routes1
Has abstractyes

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