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Record W4414340208 · doi:10.1097/aud.0000000000001728

Assessment of Balance Deficits in at Risk Pediatric Populations

2025· article· en· W4414340208 on OpenAlexaff
Sharon L. Cushing, Karen A. Gordon

Bibliographic record

VenueEar and Hearing · 2025
Typearticle
Languageen
FieldNeuroscience
TopicVestibular and auditory disorders
Canadian institutionsSickKids FoundationMental Health Research CanadaHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsBalance (ability)Hearing lossBalance problemsVestibular systemBalance disordersRisk assessment

Abstract

fetched live from OpenAlex

OBJECTIVES: This study aimed to assess balance deficits in children at risk due to hearing loss or dizziness. The specific objectives were to: (1) measure the prevalence of poor balance in children presenting with these risks; (2) determine whether vestibular test results can predict balance deficits in these children. BACKGROUND: While vestibular impairment is a known predictor of poor balance, poor balance may also occur for reasons unrelated to vestibular impairment. Poor balance in some children with hearing loss relates directly to the risks to the vestibular system due to its shared anatomical and physiological characteristics with the cochlea. Balance and/or vestibular problems may also be present in children with normal hearing who report dizziness or in children with hearing loss who have intact vestibular systems. Variability in the impact of risk factors for poor balance can lead to gaps and delays in identification as well as access to appropriate treatment. DESIGN: A retrospective analysis of vestibular and balance function from two sources, the SickKids Vertigo Clinic and the SickKids Cochlear Implant Vestibular database, was conducted. The average age of children with hearing loss (n = 107) was 11.56 years (SD = 3.94), while the average age of children without hearing loss (n = 227) was 11.52 years (SD = 3.74). Both groups included children who had available vestibular and balance testing. Balance function was measured using the Bruininks-Oseretsky Test of Motor Proficiency. Vestibular assessments included tests of vestibulo-collic reflex (VCR) (cervical vestibular evoked myogenic potentials [cVEMP]) and the vestibulo-ocular reflex (VOR) (caloric testing and the video head impulse test [vHIT]). Mixed model regression was used to compare balance results between groups and evaluate the effects of vestibular findings (vestibular impairment versus normal vestibular), degree of vestibular loss, and site of vestibular impairment (VCR versus VOR) on balance. RESULTS: Results revealed a higher prevalence of abnormal balance in children with hearing loss compared to children presenting with dizziness complaints and normal hearing [38% versus 17%, t (198.37) = -4.90, p < 0.01]. Abnormal balance function was more frequent in children with hearing loss, where VOR tests were abnormal (27.38% versus 14.52%, χ² = 3.95, p < 0.05). Children with hearing loss had significantly higher odds of having abnormal balance if they had >75% abnormal VOR test results (odds ratio of 13.71 [95% confidence interval: 2.88, 65.36]). Abnormal vestibular findings were most common in children whose hearing loss was associated with congenital cytomegalovirus, infections, or genetic syndromes. There was no consistent pattern of vestibular test abnormalities linked to balance issues in the dizzy normal hearing group. CONCLUSIONS: Balance problems are prevalent in children at risk, occurring more often in children with hearing loss than in children reporting dizziness, and are more clearly associated with VOR than VCR impairments. Balance function should be assessed in children with hearing loss who are old enough to do the test. Vestibular testing, particularly assessment of the VOR, can be used in younger children to highlight the present as well as the potential for future balance problems.

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 score0.005
Threshold uncertainty score0.150

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 head0.031
GPT teacher head0.318
Teacher spread0.286 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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