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Record W2955636780 · doi:10.1017/cjn.2019.234

Intradural Metastasis from Cutaneous Squamous Cell Carcinoma Causing Cauda Equina Syndrome

2019· article· en· W2955636780 on OpenAlexaffvenue
François Mathieu, Fan Jiang, Jamie Wilson, Phedias Diamandis, David Choi, Peter Vajkoczy, Michael G. Fehlings

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2019
Typearticle
Languageen
FieldMedicine
TopicCancer Diagnosis and Treatment
Canadian institutionsToronto Western HospitalUniversity of TorontoUniversity Health Network
FundersDowager Countess Eleanor Peel Trust
KeywordsBasal cellCauda equinaMedicineMetastasisCauda equina syndromePathologySurgeryInternal medicineCancerSpinal cord

Abstract

fetched live from OpenAlex

BACKGROUND: Spinal leptomeningeal carcinomatosis from a cutaneous squamous cell carcinoma
\n(SCC) origin is exceedingly rare. Herein, we describe the first report of cauda equina syndrome
\nsecondary to drop metastases from a skin SCC. CASE DESCRIPTION: A 69-year-old male with a history of recurrent SCC of the face with known
\ncranial nerve involvement presented with acute onset sphincter and lower extremity
\nsymptoms. Neuroimaging revealed a compressive intradural mass at the lumbosacral junction.
\nThe patient underwent urgent surgical decompression followed by adjuvant fractionated
\nradiotherapy. Substantial improvement in function and quality of life was reported on
\npostoperative follow-up. CONCLUSION: Cauda equina syndrome manifestations in a patient with a history of cutaneous SCC with perineural spread should raise suspicion for drop metastases. In this case, a relatively
\nstraight forward surgical procedure resulted in significant improvement in the quality of life.
\nTherefore, operative intervention should be considered to prevent permanent neurological
\ndeficits depending on the patient’s goals of care and overall clinical status.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.374
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.032
GPT teacher head0.261
Teacher spread0.229 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences NeurologiquesSame topicCancer Diagnosis and TreatmentFrench-language works237,207