Author
Listed:
- Lise Hobeika
(IHU reConnect
Hôpital de la Pitié Salpêtrière
McGill University
McGill University)
- Matt Fillingim
(McGill University
McGill University)
- Christophe Tanguay-Sabourin
(McGill University
McGill University
Université de Montréal)
- Mathieu Roy
(McGill University
McGill University
McGill University)
- Alain Londero
(IHU reConnect)
- Séverine Samson
(IHU reConnect
Université de Lille
Pitié-Salpêtrière Hospital)
- Etienne Vachon-Presseau
(McGill University
McGill University
McGill University)
Abstract
Subjective tinnitus is an auditory percept unrelated to external sounds, for which the limited understanding of its risk factors complicates the prevention and management. In this study, we train two distinct machine learning models to predict tinnitus presence (how often individuals perceive tinnitus) and severity separately using socio-demographic, psychological, and health-related predictors with the UK Biobank dataset (192,993 participants, 41,042 with tinnitus). We show that hearing health was the primary risk factor of both presence and severity, while mood, neuroticism, and sleep predicted severity. The severity model accurately predicts tinnitus progression over nine years, with a large effect size for individuals developing severe tinnitus (Cohen’s d = 1.3, ROC = 0.78). This result is validated on 463 individuals from the Tinnitus Research Initiative database. We simplify the severity model to a six-item clinical questionnaire that detects individuals at risk of severe tinnitus, for which early supportive care would be crucial.
Suggested Citation
Lise Hobeika & Matt Fillingim & Christophe Tanguay-Sabourin & Mathieu Roy & Alain Londero & Séverine Samson & Etienne Vachon-Presseau, 2025.
"Tinnitus risk factors and its evolution over time,"
Nature Communications, Nature, vol. 16(1), pages 1-11, December.
Handle:
RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-59445-3
DOI: 10.1038/s41467-025-59445-3
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