MétaCan
Menu
Back to cohort
Record W4367302009 · doi:10.3791/65061

Endolymphatic Duct Blockage as a Surgical Treatment Option for Ménière's Disease

2023· article· en· W4367302009 on OpenAlexaff
Annejet Alida Schenck, Issam Saliba, Josephina Maria Kruyt, Peter Paul G. van Benthem, Hendrikus Maria Blom

Bibliographic record

VenueJournal of Visualized Experiments · 2023
Typearticle
Languageen
FieldNeuroscience
TopicVestibular and auditory disorders
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsEndolymphatic sacMedicinePosterior Semicircular CanalSemicircular canalVertigoMeniere's diseaseDuct (anatomy)DecompressionSurgeryAnatomyInner earRadiologyBenign paroxysmal positional vertigoVestibular system

Abstract

fetched live from OpenAlex

Endolymphatic duct blockage is a relatively new treatment option for Ménière's disease, aiming to reduce vertigo attacks while sparing hearing and equilibrium. After a regular mastoidectomy, the posterior semicircular canal is identified, and Donaldson's line is determined. This is a line through the horizontal semicircular canal, crossing the posterior semicircular canal. The endolymphatic sac is usually found at this site under the posterior semicircular canal. The bone of the endolymphatic sac and the dura are thinned until the sac is skeletonized, after which the endolymphatic duct is identified. The duct is then blocked with a titanium clip. Using a computerized tomography (CT) scan, the position is confirmed. Follow-up visits take place 1 week, 6 weeks and 1 year after surgery. To this day, only one prospective trial assessing this method has been conducted, comparing this new method to endolymphatic sac decompression. Results of the duct blockage are promising, with 96.5% of the patients free of vertigo after 2 years. However, further research is required.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

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)0.0030.001

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 head0.110
GPT teacher head0.475
Teacher spread0.365 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Visualized ExperimentsSame topicVestibular and auditory disordersFrench-language works237,207