Auditory, visual and cognitive abilities in relation to cochlear implant outcome in elderly
Notice bibliographique
Résumé
Introduction: Cochlear implantation (CI) is the standard-of-care for individuals with severe to profound hearing loss. Nowadays, there is an increase in the number of older patients among the post-lingual hearing-impaired candidates for CI. Within this elderly population, a large variation in the degree of CI benefit has been reported, especially pertaining to speech understanding. It is suggested that the variation in speech understanding may not solely be due to peripheral auditory factors. Speech understanding is considered a multisensory process, whereby visual information (e.g. from mouth movements) is integrated with auditory information in order to increase intelligibility [1]. Besides visual information, also cognitive functions (i.e. top-down processes) are involved in speech processing. More specific, working memory, processing speed, selective attention, as well as cognitive flexibility and inhibition are required for speech processing [2], especially in unfavorable listening conditions (e.g. background noise, hearing impairment or listening through a CI). Therefore, the aim of the current study was to identify various factors, including auditory, visual and cognitive factors, predicting CI outcome in elderly CI users. Methods: Five elderly CI users with a severe to profound post-lingually acquired hearing loss were included in this study. Age ranged from 71 to 79 years (mean 76.0 years, standard deviation 3.60). For all participants, auditory, visual and cognitive abilities were investigated behaviorally and subjectively. The auditory test battery consisted of pure-tone audiometry, speech audiometry in quiet and in noise. The visual speech processing abilities were evaluated using the Test for (Audio-)Visual Speech Perception (TAUVIS) [3]. For evaluating the cognitive abilities, all participants were first screened for mild cognitive impairment using the Montreal Cognitive Assessment (MoCA) [4]. Besides, the subtest ‘Repeating Digits and Letters’ from the WAIS IV-NL [5] was used to measure working memory capacity and processing speed. Selective attention, and cognitive flexibility and inhibition, were investigated using the subtest ‘Letter Detection’ from the Cognitive Test Battery for Seniors [6] and an auditory Stroop test [7], respectively. The subjective impact of hearing loss on quality of life was investigated using the hearing-related quality of life questionnaire for Auditory-VIsual, COgnitive and Psychosocial functioning (hAVICOP) [8]. The contribution of the auditory, visual and cognitive abilities to speech understanding in quiet and in noise will be investigated using linear regression analyses. Results and conclusions: This study aimed to identify the contribution of auditory, visual and cognitive factors, to CI outcome in elderly. It is hypothesized that specifically the contribution of the cognitive abilities could be responsible for the variation in speech understanding outcome in elderly CI users. Currently, data collection is still ongoing, and the results will be presented at the HeAL conference 2022.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| 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 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».