Trajectory of hearing loss in children with unilateral hearing loss
Bibliographic record
Abstract
Introduction: The aim of this study was to quantify the amount of deterioration in hearing and to document the trajectory of hearing loss in early identified children with unilateral hearing loss (UHL). We also examined whether clinical characteristics were associated with the likelihood of having progressive hearing loss. Methods: As part of the Mild and Unilateral Hearing Loss Study, we followed a population-based cohort of 177 children diagnosed with UHL from 2003 to 2018. We applied linear mixed models to examine hearing trends over time including the average amount of change in hearing. Logistic regression models were used to examine the relationship between age and severity at diagnosis, etiology, and the likelihood of progressive loss and amount of deterioration in hearing. Results: The median age of the children at diagnosis was 4.1 months (IQR 2.1, 53.9) and follow-up time was 58.9 months (35.6, 92.0). Average hearing loss in the impaired ear was 58.8 dB HL (SD 28.5). Over the 16-year period, 47.5% (84/177) of children showed deterioration in hearing in one or both ears from their initial diagnostic assessment to most recent assessment including 21 (11.9%) who developed bilateral hearing loss. Average deterioration in the impaired ear ranged from 27 to 31 dB with little variation across frequencies. Deterioration resulted in a change in category of severity for 67.5% (52/77) of the children. Analysis for children who were followed for at least 8 years showed that most lost a significant amount of hearing rapidly in the first 4 years, with the decrease stabilizing and showing a plateau in the last 4 years. Age and severity at diagnosis were not significantly associated with progressive/stable loss after adjusting for time since diagnosis. Etiologic factors (ENT external/middle ear anomalies, inner ear anomalies, syndromic hearing loss, hereditary/genetic) were found to be positively associated with stable hearing loss. Conclusion: Almost half of children with UHL are at risk for deterioration in hearing in one or both ears. Most deterioration occurs within the first 4 years following diagnosis. Most children did not experience sudden "large" drops in hearing but more gradual decrease over time. These results suggest that careful monitoring of UHL especially in the early years is important to ensure optimal benefit from early hearing loss detection.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".