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Record W4406201205 · doi:10.1002/alz.091882

Hearing Loss and Default‐Mode Network Connectivity in Older Adults with Subjective Cognitive Decline and Mild Cognitive Impairment

2024· article· en· W4406201205 on OpenAlexaff
Nicole Grant, Natalie A. Phillips

Bibliographic record

VenueAlzheimer s & Dementia · 2024
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsConcordia University
Fundersnot available
KeywordsDefault mode networkCognitive declineCognitive impairmentAudiologyCognitionHearing lossPsychologyCognitive psychologyMedicineNeuroscienceDementiaInternal medicineDisease

Abstract

fetched live from OpenAlex

Abstract Background Hearing loss (HL) is a risk factor for dementia that is prevalent in older adults. Altered brain connectivity is present in individuals with HL, individuals with subjective cognitive decline (SCD), and individuals with mild cognitive impairment (MCI). In individuals with HL, altered brain connectivity has been associated with impaired scores on cognitive tests. In individuals with MCI, altered brain connectivity has been associated with degree of cognitive impairment and progression to dementia. Therefore, altered brain connectivity is a potential mechanism by which HL is associated with increased dementia risk. Methods Data are from the Comprehensive Assessment of Neurodegeneration in Dementia study (Data Release 6, May 2023). Participants include cognitively unimpaired (CU, n=78, age=69.5), %female=77%), SCD (n=85, age=70.0, %female=74%), and MCI (n=159, age=72.2), %female=40%) individuals. Independent component analysis was used to identify the default‐mode network (DMN), a resting‐state network that is altered in individuals at risk for dementia. Hearing data include a pure‐tone hearing screening protocol and speech‐in‐noise perception. Based on the pure‐tone hearing screening, participants were classified as having normal hearing (NH) or HL. In each diagnostic group (CU, SCD, MCI), analyses of covariance compared DMN connectivity between the NH and HL participants and linear regressions evaluated the relationship between speech‐in‐noise perception and DMN connectivity. Results Preliminary results are available for 94 older adults with MCI (NH = 60, pure‐tone HL=34). Compared to individuals with MCI and NH, those with MCI and HL had decreased connectivity between the DMN and the caudate and thalamus. There was no relationship between DMN connectivity and speech‐in‐noise perception. The CU and SCI groups are expected to have a greater capacity for compensatory changes in functional connectivity. Therefore, it is expected that in the CU and SCI groups, pure‐tone HL and speech‐in‐noise perception will be associated with increased DMN connectivity. Conclusion Current results suggest that the increased dementia risk associated with HL may be due to decreased DMN connectivity and that pure‐tone HL and speech‐in‐noise perception are differentially related to DMN connectivity. Future research will determine whether the relationship between hearing and DMN connectivity differs between older adults with varying risk of cognitive impairment.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.000

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 head0.017
GPT teacher head0.313
Teacher spread0.296 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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