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Record W2098576646 · doi:10.1002/lary.24387

Ten‐year health‐related quality of life in cochlear implant recipients

2013· article· en· W2098576646 on OpenAlexaff
Christoph Arnoldner, Vincent Lin, Clemens Honeder, David Shipp, Julian M. Nedzelski, Joseph Chen

Bibliographic record

VenueThe Laryngoscope · 2013
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsCochlear implantationQuality of life (healthcare)MedicineCohortQuality-adjusted life yearCochlear implantSF-36AudiologyHealth related quality of lifeCost effectivenessInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES/HYPOTHESIS: To evaluate the long-term impact of cochlear implantation on quality of life measured by the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36). Scores were also converted to the SF-6D to derive health utility scores. STUDY DESIGN: Prospective cohort study. METHODS: Thirty-two patients undergoing cochlear implantation completed the SF-36 preoperatively, 1 year, and 10 years after cochlear implantation. RESULTS: SF-36 results showed improvements in seven of the eight attributes when preoperative scores where compared with 1- and 10-year results. Between 1 and 10 years postoperatively, six of eight domains deteriorated in scores. When converted to the SF-6D, the mean preoperative utility scores were 0.592 for standard gamble, 0.636 using the ordinal health state paradigm, and 0.579 using the Bayesian technique. Ten years postoperatively, health utility scores were 0.643 (standard gamble), 0.684 (ordinal health state), and 0.6 (Bayesian). Between preoperatively and 10-year postoperatively, improvements were therefore 0.051, 0.048, and 0.021 for standard gamble, ordinal health state, and Bayesian paradigm, respectively. CONCLUSIONS: This study establishes the long-term sustained benefits of cochlear implantation on quality of life. Nevertheless, both the SF-36 and SF-6D seem to underestimate the benefit accrued through this intervention. Our data are consistent with others regarding the unsuitability of the SF-36 in benefit assessment, notwithstanding that conversion to the SF-6D is feasible, and the SF-6D seemed to better depict possible benefits from cochlear implantation as compared to the SF-36.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.768
Threshold uncertainty score0.890

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 head0.052
GPT teacher head0.320
Teacher spread0.268 · 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 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

Citations32
Published2013
Admission routes1
Has abstractyes

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