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Record W2007598642 · doi:10.1097/brs.0b013e31805c0ab7

Pyogenic Intradural Abscess

2007· article· en· W2007598642 on OpenAlexaff
Arvind G. Kulkarni, Gordon Chu, Michael G. Fehlings

Bibliographic record

VenueSpine · 2007
Typearticle
Languageen
FieldMedicine
TopicInfectious Diseases and Tuberculosis
Canadian institutionsToronto Western Hospital
Fundersnot available
KeywordsMedicineSpondylodiscitisSurgeryPresentation (obstetrics)AbscessEpidural abscessDecompressionLumbarRadiology

Abstract

fetched live from OpenAlex

In Brief Study Design. A case report of pyogenic intradural abscess is described. Objectives. The rarity of the presentation and its successful management are discussed. Summary of Background Data. Intradural abscesses are exceptionally rare. Method. The abscess was drained by performing a posterior midline lumbar durotomy, and intravenous antibiotics were initiated. Result. At the 1 year follow-up, the patient has made significant neurologic recovery. Conclusion. Intradural pyogenic abscess secondary to chronic pyogenic spondylodiscitis is a rare manifestation. MRI is a vital component in diagnosis, which revealed key pathologic features within the dural sac as well as in the vertebral column. An emergency decompression and appropriate antibiotic regimen is the solution for a favorable outcome. A rare and interesting case of paraparesis due to pyogenic spinal intradural abscess secondary to L2–L3 pyogenic spondylodiscitis is presented. The successful management of this case is described and the relevant literature is briefly reviewed.

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: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.002

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 head0.008
GPT teacher head0.289
Teacher spread0.281 · 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

Citations19
Published2007
Admission routes1
Has abstractyes

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