Exploring the Prevalence of Tinnitus and Ear-Related Symptoms in China After the COVID-19 Pandemic: Online Cross-Sectional Survey
Notice bibliographique
Résumé
BACKGROUND: Tinnitus is a complex and heterogeneous disease that has been identified as a common manifestation of COVID-19. To gain a comprehensive understanding of tinnitus symptoms in individuals following COVID-19 infection, we conducted an online survey called the China Ear Nose and Throat Symptom Survey in the COVID-19 Pandemic (CENTSS) among the Chinese population. OBJECTIVE: Our objective was to investigate tinnitus and ear-related symptoms after COVID-19 infection in the Chinese population, with the aim of providing a solid empirical foundation for improved health care. The findings from CENTSS can contribute to the development of enhanced management strategies for tinnitus in the context of long COVID. By gaining a better understanding of the factors contributing to tinnitus in individuals with COVID-19, health care providers can tailor interventions to address the specific needs of affected patients. Furthermore, this study serves as a basis for research on the long-term consequences of COVID-19 infection and its associated tinnitus symptoms. METHODS: A quantitative, online, cross-sectional survey study design was used to explore the impact of the COVID-19 pandemic on experiences with tinnitus in China. Data were collected through an online questionnaire designed to identify the presence of tinnitus and its impacts. Descriptive statistics were used to analyze individuals' demographic characteristics, COVID-19 infection-related ear symptoms, and the cognitive and emotional implications of tinnitus. Univariable and multivariable logistic regression analyses were used to model the cross-sectional baseline associations between demographic characteristics, noise exposure, educational level, health and lifestyle factors, and the occurrence of tinnitus. RESULTS: Between December 19, 2022, and February 1, 2023, we obtained responses from 1262 Chinese participants representing 24 regions, with an average age of 37 years. Among them, 540 patients (42.8%) reported experiencing ear-related symptoms after COVID-19 infection. Only 114 (9%) of these patients sought medical attention specifically for their ear symptoms, while 426 (33.8%) did not seek hospital care. Tinnitus emerged as the most prevalent and impactful symptom among all ear-related symptoms experienced after COVID-19 infection. Of the respondents, female participants (688/888, 77.78%), younger individuals (<30 years), individuals with lower education levels, participants residing in western China, and those with a history of otolaryngology diseases were more likely to develop tinnitus following COVID-19 infection. CONCLUSIONS: In summary, tinnitus was identified as the most common ear-related symptom during COVID-19 infection. Individuals experiencing tinnitus after COVID-19 infection were found to have poorer cognitive and emotional well-being. Different ear-related symptoms in patients post-COVID-19 infection may suggest viral invasion of various parts of the ear. It is therefore crucial to monitor and manage hearing-related changes resulting from COVID-19 as clinical services resume.
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 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 | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».