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Record W2966926758 · doi:10.21037/ajo.2019.07.01

Endoscopic tympanic neurectomy for otic neuralgia—a case series

2019· article· en· W2966926758 on OpenAlexaffabout
Rithvik Reddy, Nicholas Jufas, Manohar Bance, Nirmal Patel

Bibliographic record

VenueAustralian Journal of Otolaryngology · 2019
Typearticle
Languageen
FieldMedicine
TopicEar Surgery and Otitis Media
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineNeurectomySurgeryEndoscope

Abstract

fetched live from OpenAlex

Abstract: Otic neuralgia (ON) is a diagnostic and therapeutic challenge. ON is often attributed to either direct or referred pain from other structures. The tympanic nerve is the major contributor to sensory supply of the middle ear mucosa. A tympanic neurectomy has previously been described for the management of ON with promising results. This work aims to describe an endoscopic approach to the tympanic neurectomy and assess results in a case series of 8 patients. A multi-center retrospective review was conducted searching for cases of endoscopic tympanic neurectomies performed for ON; the sites included Royal North Shore Hospital; Sydney, Macquarie University Hospital, Sydney and the Victoria General Hospital, Dalhousie University, Halifax. From May 2014 to December 2016 there were a total of eight endoscopic tympanic neurectomies performed for ON. The mean age at presentation was 46.4 years (range, 29–75 years), there were 7 females and 1 male. All patients were pain free after an average of 2.1 months (range, immediate relief to 5 months) with one case of recurrent ON noted that resolved after further treatment. Tympanic neurectomy offers a therapeutic option for ON once alternative causes have been excluded. The endoscope allows improved visualization allowing for a more precise and complete neurectomy.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.579
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.023
GPT teacher head0.286
Teacher spread0.263 · 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.

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

Citations4
Published2019
Admission routes2
Has abstractyes

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