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Record W4415507170 · doi:10.1097/aud.0000000000001723

Speech Perception Outcomes in Children With Single-Sided Deafness Receiving Unilateral Cochlear Implantation Compared to Bimodal Device Users

2025· article· en· W4415507170 on OpenAlexaff
Hanne Bartels, Melissa J. Polonenko, Jaina Negandhi, Robel Alemu, Sharon L. Cushing, Blake C. Papsin, Karen A. Gordon

Bibliographic record

VenueEar and Hearing · 2025
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsCochlear implantationSpeech perceptionCochlear implantHearing aidHearing lossPerception

Abstract

fetched live from OpenAlex

OBJECTIVES: This study aimed to (1) assess the effects of residual hearing in the acoustic hearing (AH) ear on speech perception outcomes with ongoing unilateral cochlear implant (CI) use in children and (2) investigate factors related to hearing history that might affect these outcomes. Children with single-sided deafness (SSD) were compared to peers with hearing loss (HL) in the AH ear contralateral to their CI. DESIGN: In total, 185 children who received a unilateral CI after limited durations of severe to profound HL {median (interquartile range [IQR]) = 1.9 (1.0 to 2.9) years} were included in this study. Of these, 43 (23.2%) had SSD and 142 (76.8%) used a contralateral hearing aid for mild to moderately-severe HL (PTA median [IQR] = 48.8 [42.5 to 63.8] dB HL, n = 39 [21.1%]) or severe to profound HL (PTA median [IQR] = 80.0 [72.1 to 85.5] dB HL, n = 103 [55.7%]) (bimodal device users). Median [IQR] age at implantation was 5.3 [3.1 to 10.6] years. Speech perception was measured in quiet (n = 182 children, average of 2.8 test sessions/child) and in co-located speech-weighted noise (+10 dB SNR) (n = 109 children, average of 2.0 test sessions/child) using word recognition tests. Spatial release of masking was measured to assess spatial separation benefits (n = 78 children, average of 1.6 tests/child). RESULTS: Speech perception in the AH ear was better in children with SSD than bimodal device users in quiet ( p < 0.001), but group differences were smaller in noise, reflecting significantly reduced scores in the SSD group in noise compared to quiet ( p < 0.001, mean [SD] difference = 27.3 [2.6] rationalized arcsine units [RAU]). Speech perception scores when using the CI-alone were similar between the three groups in quiet and noise ( p > 0.05). In quiet, speech perception was asymmetric with better scores for the AH ear for children with SSD (mean [SD] = 30.7 [29.1] RAU) and for the CI ear for bimodal device users (mean [±SD] = -5.25 [±21.7] RAU for mild to moderately-severe and -27.2 [±30.9] RAU for severe to profound HL), and the bilateral benefit was the smallest for children with SSD ( p < 0.01). In noise, however, these group differences were only significant between children with SSD and those with a severe to profound HL in the AH ear ( p = 0.02 for interaural asymmetry, p = 0.03 for bilateral benefit). In addition, asymmetry toward the AH ear decreased and bilateral benefit increased in quiet with shorter durations of deprivation ( p < 0.01) and longer CI experience ( p = 0.01), but these predictors had no effect in noise. Last, aural preference, measured by spatial release of masking, was consistent with interaural asymmetry in speech perception in quiet ( p = 0.01). Aural preference toward the AH ear was larger in the SSD than bimodal devices groups ( p < 0.01) and for children with post-lingual onset of deafness using a left rather than right CI ( p = 0.04). CONCLUSIONS: Benefits of cochlear implantation are evident both for children with SSD and bimodal device users, and scores were not affected by the degree of residual hearing in noise. These benefits of bilateral hearing are most pronounced for children with shorter durations of deprivation in either ear.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.212
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.034
GPT teacher head0.302
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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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