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Record W4395049831 · doi:10.1055/s-0044-1784871

The influence of cochlear implantation in the elderly using preoperative MoCA screening for mild cognitive impairment

2024· article· en· W4395049831 on OpenAlexaboutno aff
Carmen Molenda, Daniel Polterauer, Joachim Müller

Bibliographic record

VenueLaryngo-Rhino-Otologie · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsnot available
Fundersnot available
KeywordsCognitive impairmentCochlear implantationAudiologyMontreal Cognitive AssessmentMedicineCognitionComputer scienceHearing lossPsychiatry

Abstract

fetched live from OpenAlex

In Germany, around 14 million people suffer from presbycusis, according to the WHO; more than a third of people over 65 worldwide are affected. Hearing loss often results in limited social participation, social withdrawal, isolation, and a negative impact on quality of life. The lack of acoustic stimuli and social interaction leads to the brain being under-challenged, resulting in an acceleration of cognitive decline and a drop in intellectual performance. In addition to an increased risk of dementia, an unfavorable influence on existing dementia is also described. To ensure social participation, maintain the ability to communicate, and continue to provide the brain with acoustic input advances in minimally invasive procedures made it possible for older people to be fitted with a cochlear implant (CI). In our study, in addition to the change in speech comprehension (measured using the Freiburg Speech Test pre- and postoperatively), we analyzed the cognitive performance before treatment with CI using the MoCA test. All patients over 65 years of age should be included regardless of their results in the MoCA. We have currently included 27 patients in our study who scored 23.89±5.12 points in the MoCA. Preoperative aided speech understanding in percent was 12.04±16.66 at 65dB SPL resp. 27.50±24.20 at 80dB SPL. Postoperatively 6-12 months after initial activation the speech understanding in percent rose to 39.29±21.35 at 65dB SPL resp. 59.25±18.53 at 80dB SPL. We found a significant correlation (p=0.04; r=0.43; n=25) between the MoCA score and speech understanding preoperatively for 80dB SPL. Additionally, we found a significant improvement in speech understanding by CI at 65dB SPL in the speech test (p<0.01; t=-3.89; n=19) as well as at 80 dB SPL (p<0.01; t=-4.21; n=19).

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)0.003
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score0.556

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.159
GPT teacher head0.475
Teacher spread0.316 · 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 designQualitative
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

Citations0
Published2024
Admission routes1
Has abstractyes

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