Trajectory of hearing loss in children with unilateral hearing loss
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».