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Record W2725325283 · doi:10.1080/14670100.2017.1341362

The impact of vestibular status prior to cochlear implantation on postural control: A multiple case study

2017· article· en· W2725325283 on OpenAlexafffund
Maxime Maheu, Sara Pagé, Andréanne Sharp, Audrey Delcenserie, François Champoux

Bibliographic record

VenueCochlear Implants International · 2017
Typearticle
Languageen
FieldNeuroscience
TopicVestibular and auditory disorders
Canadian institutionsUniversité de MontréalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsVestibular systemCochlear implantMedicineAudiologyCochlear implantationRehabilitationPhysical medicine and rehabilitationImplantPhysical therapySurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: The goal of the present study was to investigate the impact of unilateral cochlear implantation on postural control in relation to the vestibular status before CI surgery. METHODS: We recruited 17 participants (four CI candidates and 13 hearing controls) and performed complete vestibular evaluation (cVEMP, oVEMP, vHIT) and postural evaluation using a force platform, prior and following unilateral cochlear implant surgery. RESULTS: Our study suggests that an increase in postural sway following cochlear implant was present only for the participants that received the implant in the ear with the better vestibular function. cVEMP and oVEMP measures in the implanted ear prior to unilateral cochlear implantation may help to predict postural control performance following surgery. DISCUSSION: A thorough evaluation of the vestibular function, as described in the present study, could not only be helpful to make a more accurate prognosis of the risks of fall following cochlear implantation, but also to provide proper vestibular rehabilitation for at-risk patients.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.037
GPT teacher head0.371
Teacher spread0.335 · 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

Citations10
Published2017
Admission routes2
Has abstractyes

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