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Enregistrement W4221006852 · doi:10.1002/lary.30108

Hearing Instability in Children with Congenital Cytomegalovirus: Evidence and Neural Consequences

2022· article· en· W4221006852 sur OpenAlexaff
Sharon L. Cushing, Patricia L. Purcell, Vicky Papaiaonnou, Jaina Neghandi, Maya Daien, Susan Blasér, Birgit Ertl‐Wagner, Matthias Wagner, Min Sheng, Adrian L. James, Ari Bitnun, Blake C. Papsin, Karen A. Gordon

Notice bibliographique

RevueThe Laryngoscope · 2022
Typearticle
Langueen
DomaineMedicine
ThématiqueCytomegalovirus and herpesvirus research
Établissements canadiensSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésMedicineAudiologyAudiogramSensorineural hearing lossHearing lossCochlear implantSequelaAuditory neuropathyUnilateral hearing lossMagnetic resonance imagingPediatricsSurgeryRadiology

Résumé

récupéré en direct d'OpenAlex

OBJECTIVE/HYPOTHESIS: Sensorineural hearing loss (SNHL) is a common sequela of congenital cytomegalovirus (cCMV), potentially exacerbating neurocognitive delay. The objectives of this study were to assess: (1) age at which SNHL in children with cCMV; (2) stimulability of the auditory system in children with cCMV following cochlear implantation (CI); and (3) whether features of magnetic resonance imaging (MRI) potentially are predictive of hearing outcomes. METHODS: In this retrospective study of a prospectively acquired cohort, 123 children with cCMV who were referred for hearing loss at a single tertiary referral hospital over 20 years were compared with an unmatched comparative group of 90 children with GJB2-related deafness. Outcome measures were results of newborn hearing screening (NHS), behavioral audiograms, and, in a subgroup of cochlear implant (CI) users, responses from the auditory nerve and brainstem evoked by CI at initial activation, as well as lesional volume of FLAIR-hyperintense signal alterations on MRI. RESULTS: All but 3 of 123 children with cCMV had confirmed and persistent SNHL. At birth, 113 children with cCMV underwent NHS, 31 (27%) passed in both ears and 23 (20%) passed in one ear (no NHS data in 10 children). At the first audiologic assessment, 32 of 123 (26%) had normal hearing bilaterally; 35 of 123 (28%) had unilateral SNHL; and 57 of 123 (46%) had bilateral SNHL. More than half (67 of 123, 54%) experienced hearing deterioration in at least one ear. Survival analyses suggested that 60% of children who developed SNHL did so by 2.5 years and 80% by 5 years. In the children who passed NHS in one or both ears, 50% developed hearing loss by 3.5 years in the ear, which passed unilaterally (n = 23 ears), and 50% by 5 years in bilateral passes (n = 62 ears). Hearing loss was significant enough in all but one child with isolated high-frequency loss for rehabilitation to be indicated. Hearing thresholds in individual ears were in the CI range in 83% (102 of 123), although duration of deafness was sufficient to preclude implantation at our center in 13 children with unilateral SNHL. Hearing aids were indicated in 16% (20 of 123). Responses from the auditory nerve and brainstem to initial CI stimulation were similar in children with cCMV-related SNHL compared with GJB2-related SNHL. Characteristic white matter changes on MRI were seen in all children with cCMV-related SNHL (n = 91), but the lesion volume in each cortical hemisphere did not predict degree of SNHL. CONCLUSIONS: cCMV-related SNHL is often not detected by NHS but occurs with high prevalence in early childhood. Electrophysiological measures suggest equivalent stimulability of the auditory nerve and brainstem with CI in children with cCMV and GJB2-related SNHL. Hyperintense white matter lesions on FLAIR MRI are consistently present in children with cCMV-related SNHL but cannot be used to predict its time course or degree. Combined, the data show early and rapid deterioration of hearing in children with cCMV-related SNHL with potential for good CI outcomes if SNHL is identified and managed without delay. Findings support universal newborn screening for cCMV followed by careful audiological monitoring. LEVEL OF EVIDENCE: 3 Laryngoscope, 132:S1-S24, 2022.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,008
Score d'incertitude au seuil0,699

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,047
Tête enseignante GPT0,312
Écart entre enseignants0,264 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations30
Publié2022
Routes d'admission1
Résumé présentoui

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