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Record W2061672484 · doi:10.1055/s-0031-1275253

Endoscopic Endonasal Management of Recurrent Petrous Apex Cholesterol Granuloma

2011· article· en· W2061672484 on OpenAlexaff
Nancy McLaughlin, Daniel F. Kelly, Daniel M. Prevedello, Kiarash Shahlaie, Ricardo Carrau, Amin Kassam

Bibliographic record

VenueSkull Base Reports · 2011
Typearticle
Languageen
FieldMedicine
TopicOcular Diseases and Behçet’s Syndrome
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineSurgeryTranssphenoidal surgeryCystEndoscopyEndoscopic endonasal surgeryAbducens nervePalsySkullPituitary adenomaAdenomaPathology

Abstract

fetched live from OpenAlex

Petrous apex cholesterol granulomas (PACG) are uncommon lesions. Recurrence following transcranial or endonasal approaches to aerate the cyst occurs in up to 60% of cases. We describe the technical nuances pertinent to the endonasal endoscopic management of a recurrent symptomatic PACG and review the literature. A 19-year-old woman presented with a recurrent right abducens nerve paresis. Four months prior, she underwent an endonasal transsphenoidal surgery (TSS) for drainage of a symptomatic PACG. Current imaging documented recurrence of the right PACG. Transsphenoidal and infrapetrous approaches were performed to obtain a wider bony opening along the petrous apex and drain the cyst. A Doyle splint was inserted into the cyst's cavity and extended out into the sphenoid, maintaining patency during the healing process. Three months after surgery, the splint was removed endoscopically, allowing visualization of a patent cylindrical communication between both aerated cavities. The patient remains symptom- and recurrence-free. Endoscopic endonasal surgery must be adapted to manage recurrent PACG. A TSS may not be sufficient. An infrapetrous approach with wider bony opening, extensive removal of the cyst's anterior wall, and use of a stent are indicated for the treatment of recurrent PACG and to prevent recurrences.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
Threshold uncertainty score0.970

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.255
Teacher spread0.228 · 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 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

Citations9
Published2011
Admission routes1
Has abstractyes

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