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Record W2921979178 · doi:10.12659/ajcr.913964

Complete Recovery of Sensorineural Hearing Loss Following Endoscopic Transsphenoidal Surgery for a Petrous Apex Cholesterol Granuloma: Case Report

2019· article· en· W2921979178 on OpenAlexaff
Aleksandar Radonjic, Ioana Moldovan, Shaun Kilty, David Schramm, Fahad Alkherayf

Bibliographic record

VenueAmerican Journal of Case Reports · 2019
Typearticle
Languageen
FieldMedicine
TopicEar and Head Tumors
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineSensorineural hearing lossSurgeryTranssphenoidal surgeryGranulomaPetrous boneHearing lossAudiologyPathologyPituitary adenoma

Abstract

fetched live from OpenAlex

BACKGROUND Cholesterol granulomas of the petrous apex may impinge surrounding cranial nerves, leading to neurological impairments such as hearing loss. Less invasive endoscopic techniques are gaining popularity as the mainstay of therapy for this lesion. CASE REPORT We present a case of petrous apex cholesterol granuloma causing mild sensorineural hearing loss. An endoscopic endonasal transsphenoidal approach was successfully performed to partially resect and aerate the lesion. The auditory function on the affected side was completely restored after surgery. The patient experienced no post-operative complications. CONCLUSIONS This case report highlights the advantages of using an endoscopic transsphenoidal surgical approach in cases of petrous apex cholesterol granuloma, including the potential for this less invasive technique to restore sensorineural hearing loss.

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)0.002
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 score0.005
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.023
GPT teacher head0.289
Teacher spread0.266 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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