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Tinnitus risk factors and its evolution over time
Medicine and HealthNature Communications

Tinnitus risk factors and its evolution over time

L. Hobeika, M. Fillingim, et al.

Using UK Biobank data, two machine-learning models separately predict tinnitus presence and severity, showing hearing health as the primary risk factor while mood, neuroticism and sleep predict severity. The severity model forecasts nine-year progression (Cohen’s d = 1.3, ROC = 0.78) and is validated externally; a six-item questionnaire flags those at risk of severe tinnitus. This research was conducted by Authors present in <Authors> tag.... show more
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.
Publisher
Nature Communications
Published On
May 07, 2025
Authors
Lise Hobeika, Matt Fillingim, Christophe Tanguay-Sabourin, Mathieu Roy, Alain Londero, Séverine Samson, Etienne Vachon-Presseau
Tags
subjective tinnitusmachine learning predictionUK Biobankhearing healthtinnitus severityclinical questionnaire
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