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Record W2995561042 · doi:10.14740/jmc3392

Multilevel Lumbar Stenosis Caused by Large Tophi Involving Both Spinal Canal and Posterior Spinal Elements: A Rare Case Report and Literature Review

2019· article· en· W2995561042 on OpenAlexvenueno aff
Yang Liu, Xueshi Li, Genlong Jiao, Pan Zhou, Zhizhong Li

Bibliographic record

VenueJournal of Medical Cases · 2019
Typearticle
Languageen
FieldMedicine
TopicGout, Hyperuricemia, Uric Acid
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTophusGoutLumbarPathologicalSpinal canalSpinal stenosisRadiologySurgeryLumbar spinal stenosisPathologySpinal cordHyperuricemiaUric acidInternal medicine

Abstract

fetched live from OpenAlex

Tophus is a characteristic manifestation of gout entering the chronic phase, which usually deposits in the joints of the extremities, skin mucosa, etc. A gout tophus that involves the spine causing spinal stenosis is rare and it can be misdiagnosed as a spinal tumor preoperatively. We report the case of a 35-year-old man who presented with lumbar stenosis symptoms, and suffered multiple-site gout tophi involvement throughout his body. Radiographic examinations showed that the large tophi infiltrated the posterior elements of the spine and encroached the lumbar spinal canal, resulting in neurologic compression from the second to the fifth lumbar level. Urate could be observed on a dual-energy computed tomography. A posterior-based procedure was performed to eradicate the tophi and stabilize the spine. Finally, urate crystal was confirmed by postoperative pathological examination. Here, the clinical manifestations, radiological, pathological and surgical features for this case are reported.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.005
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.021
GPT teacher head0.321
Teacher spread0.300 · 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 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

Citations3
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Medical CasesSame topicGout, Hyperuricemia, Uric AcidFrench-language works237,207