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Record W4296630065 · doi:10.3390/jpm12101551

Minimally Traumatic Cochlear Implant Surgery: Expert Opinion in 2010 and 2020

2022· article· en· W4296630065 on OpenAlexaff
Vedat Topsakal, Sumit Agrawal, Marcus D. Atlas, Wolf‐Dieter Baumgartner, Kevin D. Brown, Iain Bruce, Stefan Dazert, Rudolf Hagen, Luis Lassaletta, Robert Mlynski, Christopher Raine, Gunesh P. Rajan, Joachim Schmutzhard, Georg Mathias Sprinzl, Hinrich Staecker, Shin‐ichi Usami, Vincent Van Rompaey, Mario Zernotti, Paul Van de Heyning

Bibliographic record

VenueJournal of Personalized Medicine · 2022
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsMedicineCochlear implantRound windowExpert opinionImplantCochlear implantationAudiologySurgeryDentistryIntensive care medicineCochlea

Abstract

fetched live from OpenAlex

This study aimed to discover expert opinion on the surgical techniques and materials most likely to achieve maximum postoperative residual hearing preservation in cochlear implant (CI) surgery and to determine how these opinions have changed since 2010. A previously published questionnaire used in a study published in 2010 was adapted and expanded. The questionnaire was distributed to an international group of experienced CI surgeons. Present results were compared, via descriptive statistics, to those from the 2010 survey. Eighteen surgeons completed the questionnaire. Respondents clearly favored the following: round window insertion, slow array insertion, and the peri- and postoperative use of systematic antibiotics. Insertion depth was regarded as important, and electrode arrays less likely to induce trauma were preferred. The usefulness of dedicated soft-surgery training was also recognized. A lack of agreement was found on whether the middle ear cavity should be flushed with a non-aminoglycoside antibiotic solution or whether a sheath or insertion tube should be used to avoid contaminating the array with blood or bone dust. In conclusion, this paper demonstrates how beliefs about CI soft surgery have changed since 2010 and shows areas of current consensus and disagreement.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.880
Threshold uncertainty score0.510

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.069
GPT teacher head0.336
Teacher spread0.267 · 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 designBench or experimental
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
Published2022
Admission routes1
Has abstractyes

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