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Giant Cauda Equina Schwannoma

2000· review· it· W2022504578 on OpenAlexaff
Hitoshi Kagaya, Eiji Abe, Kôzô Satô, Yoichi Shimada, Atsushi Kimura

Bibliographic record

VenueSpine · 2000
Typereview
Languageit
FieldMedicine
TopicNeurofibromatosis and Schwannoma Cases
Canadian institutionsMinnow Environmental (Canada)
Fundersnot available
KeywordsMedicineCauda equinaSchwannomaCauda equina syndromeSpinal NeoplasmsSurgeryAnatomySpinal cord

Abstract

fetched live from OpenAlex

STUDY DESIGN: Case report. OBJECTIVES: To present a rare case of a giant schwannoma of the cauda equina. SUMMARY OF BACKGROUND DATA: Giant spinal schwannoma of the cauda equina, which involves many nerve roots, is rare and there is usually no ossification in the schwannoma. It is unknown whether or not complete excision is preferable if the tumor is located in the lumbar lesion. METHODS: A 57-year-old woman had a 10-year history of low back pain. Scalloping of the posterior surface of the vertebral bodies from L3 to the sacrum was found. Magnetic resonance imaging disclosed a giant cauda equina tumor with multiple cysts. Central ossification revealed by computed tomography and an unusual myelogram made the preoperative diagnosis difficult. RESULTS: The patient underwent incomplete removal of the tumor, decompression of cysts, and spinal reconstruction. The tumor was proved to be a schwannoma. The postoperative course was uneventful and she has been almost free from low back pain for 3 years and 4 months. CONCLUSIONS: Giant schwannoma in the lumbar spine region is usually excised incompletely, because complete removal had the risk of sacrificing many nerve roots. In spite of the incomplete removal of the tumor, the risk of recurrence is low.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.921
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0180.015

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 head0.044
GPT teacher head0.317
Teacher spread0.272 · 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 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

Citations76
Published2000
Admission routes1
Has abstractyes

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