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识别老年听力损失患者中重度耳鸣的心理和临床风险因素:多变量预测模型

Identifying psychological and clinical risk factors for moderate-to-severe tinnitus in older patients with hearing loss: a multivariable prediction model.

作者信息

Zhang Chenguang, Wang Yicong, Zhao Chunlong, Xue Rou, Hu Chenghao, Guo Bin

机构信息

Graduate School of Qinghai University, Xining, China.

Department of Otolaryngology, Affiliated Hospital of Qinghai University, Xining, China.

出版信息

Front Neurol. 2025 Jul 23;16:1647071. doi: 10.3389/fneur.2025.1647071. eCollection 2025.

DOI:10.3389/fneur.2025.1647071
PMID:40771979
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12325010/
Abstract

OBJECTIVE

To develop and validate a clinical prediction model for moderate-to-severe tinnitus (THI ≥ 38) in patients with hearing loss and to identify the key psychological and clinical factors associated with its risk.

METHODS

This retrospective single-centre study included 301 patients with hearing loss who visited Qinghai University Affiliated Hospital between August 2024 and May 2025. The cohort was randomly divided into a training set ( = 210) and a validation set ( = 91) in a 7:3 ratio. Moderate-to-severe tinnitus served as the outcome of interest. Psychological and clinical risk factors were initially screened using univariate logistic regression, and variables with < 0.05 were subsequently included in a multivariable logistic regression model.

RESULTS

The final multivariable model identified five independent psychological and clinical risk factors for moderate-to-severe tinnitus: older age (OR = 2.415), hypertension (OR = 2.120), poor sleep quality (OR = 2.821), anxiety (OR = 1.967), and severe hearing loss (OR = 3.452). The model demonstrated good discriminative performance, with an AUC of 0.734 in the training set and 0.760 in the validation set.

CONCLUSION

In patients with hearing loss, psychological and clinical risk factors-including poor sleep quality, anxiety, hypertension, and severe hearing loss-were significantly associated with moderate-to-severe tinnitus. These findings underscore the need for integrated management strategies that address both psychological and clinical components of tinnitus risk.

摘要

目的

开发并验证一种针对听力损失患者中重度耳鸣(耳鸣 handicap 问卷评分≥38)的临床预测模型,并确定与其风险相关的关键心理和临床因素。

方法

这项回顾性单中心研究纳入了2024年8月至2025年5月期间就诊于青海大学附属医院的301例听力损失患者。该队列以7:3的比例随机分为训练集(n = 210)和验证集(n = 91)。中重度耳鸣作为感兴趣的结局。心理和临床风险因素最初使用单因素逻辑回归进行筛选,随后将P < 0.05的变量纳入多因素逻辑回归模型。

结果

最终的多因素模型确定了中重度耳鸣的五个独立心理和临床风险因素:年龄较大(OR = 2.415)、高血压(OR = 2.120)、睡眠质量差(OR = 2.821)、焦虑(OR = 1.967)和重度听力损失(OR = 3.452)。该模型表现出良好的区分性能,训练集中的AUC为0.734,验证集中的AUC为0.760。

结论

在听力损失患者中,心理和临床风险因素——包括睡眠质量差、焦虑、高血压和重度听力损失——与中重度耳鸣显著相关。这些发现强调了需要采取综合管理策略来应对耳鸣风险的心理和临床因素。

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本文引用的文献

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Exploring How Blood Cell Levels Influence Subjective Tinnitus: A Cross-Sectional Case-Control Study.探索血细胞水平如何影响主观性耳鸣:一项横断面病例对照研究。
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When the Mind Meets the Ear: A Scoping Review on Tinnitus and Clinically Measured Psychiatric Comorbidities.当心灵与耳朵相遇:耳鸣与临床测量的精神共病的范围综述
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用于管理耳鸣、恐声症和恐音症的认知行为疗法(CBT):2025年通多夫讲座
Brain Sci. 2025 May 19;15(5):526. doi: 10.3390/brainsci15050526.
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Tinnitus risk factors and its evolution over time.耳鸣的风险因素及其随时间的演变。
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Machine Learning Models Can Predict Tinnitus and Noise-Induced Hearing Loss.机器学习模型能够预测耳鸣和噪声性听力损失。
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The Influence of Carotid and Vertebral Doppler Ultrasonography and Brain MRI Abnormalities on Hearing Levels, Tinnitus Intensities and Frequencies.颈动脉和椎动脉多普勒超声检查及脑磁共振成像异常对听力水平、耳鸣强度和频率的影响
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Tinnitus and Its Comorbidities: A Comprehensive Analysis of Their Relationships.耳鸣及其合并症:对它们之间关系的综合分析
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