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Cochlear implant rehabilitation for patients with vestibular schwannoma: report of two cases

2011· review· en· W2045394007 on OpenAlexaff
Hosam Amoodi, Fawaz Makki, Jonathan Cavanagh, Heather Maessen, Manohar Bance

Bibliographic record

VenueCochlear Implants International · 2011
Typereview
Languageen
FieldMedicine
TopicMeningioma and schwannoma management
Canadian institutionsNova Scotia Cancer CentreDalhousie University
Fundersnot available
KeywordsMedicineSchwannomaCochlear implantNeurofibromatosis type 2ImplantRadiosurgeryNeurofibromatosisVestibular systemAudiologyRehabilitationRadiologySurgeryRadiation therapyPhysical therapy

Abstract

fetched live from OpenAlex

OBJECTIVE AND IMPORTANCE: The objective of this paper is to highlight two main points. The primary aim is to demonstrate that cochlear implants can function in the presence of retrocochlear pathology, even after stereotactic radiosurgery (SRS), and hence to introduce this as a management option in selected patients with retrocochlear pathology, such as Neurofibromatosis type II (NFII) patients. A secondary aim is to act as a caveat that computed tomography (CT) scanning alone may not be sufficient imaging in subjects undergoing cochlear implantation (CI). CLINICAL PRESENTATION: In this paper we report two patients who underwent cochlear implant despite the presence of a vestibular schwannoma (VS) on the same side. The first case is a 59-year-old male, diagnosed with VS after 9 months of good hearing with a cochlear implant. The second case is 26-year-old female known case of NFII, received a cochlear implant after controlling the tumor growth with a SRS. CONCLUSION: We show the consequences of missing important pre-implant pathology prior to CI in one case. In both cases, we add to the literature showing that cochlear implants can work well in the presence of VS, even in the presence of previous SRS. This adds significantly to the management options available to NFII patients, and the results seem to be better than those expected for auditory brainstem implant (ABI), and with a much simpler and safer intervention.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.906
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.049
GPT teacher head0.356
Teacher spread0.306 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations16
Published2011
Admission routes1
Has abstractyes

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