Voss Patrice, Martinez-Moreno Zaida Escila, Prévost Francois, Zeitouni Anthony, Lopez Valdes Alejandro, de Villers-Sidani Etienne
Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada.
Département of Audiology and Speech-Language Pathology McGill University Health Center, Montreal, QC, Canada.
Front Aging Neurosci. 2025 Feb 20;17:1548526. doi: 10.3389/fnagi.2025.1548526. eCollection 2025.
Although the phenomena underlying cognitive decline and dementia are complex, there is growing evidence suggesting that degraded sensory inputs caused by age-related hearing loss may play a central role in accelerating cognitive decline in older individuals. Further supporting this notion is evidence that hearing augmentation with hearing aids can mitigate hearing loss-related cognitive impairments. Despite this evidence, few studies have attempted to investigate hearing aid efficacy with a focus on cognitive outcome measures. In this preliminary study, we sought to determine if certain demographic and audiological factors are linked to individual differences regarding observed cognitive changes following hearing aid use. We show that several factors can explain large portions of the variance observed in cognitive score changes following short-term hearing aid use in first-time users, suggesting that it might be possible to develop predictive algorithms to determine individualized estimates of the cognitive benefit of hearing aid use. Future studies with larger sample sizes are warranted, in particular, to explore a wider array of cognitive functions, investigate a greater range of potential predictors, and better quantify their relative contribution to outcome measure estimates.
尽管认知能力下降和痴呆背后的现象很复杂，但越来越多的证据表明，与年龄相关的听力损失导致的感官输入退化可能在加速老年人认知能力下降方面起着核心作用。进一步支持这一观点的证据是，使用助听器增强听力可以减轻与听力损失相关的认知障碍。尽管有这些证据，但很少有研究试图以认知结果指标为重点来研究助听器的疗效。在这项初步研究中，我们试图确定某些人口统计学和听力学因素是否与首次使用助听器后观察到的认知变化的个体差异有关。我们表明，几个因素可以解释首次使用者短期使用助听器后认知分数变化中观察到的大部分方差，这表明有可能开发预测算法来确定助听器使用认知益处的个性化估计。有必要进行更大样本量的未来研究，特别是要探索更广泛的认知功能，研究更多潜在的预测因素，并更好地量化它们对结果指标估计的相对贡献。
