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首页> 外文期刊>BMC Geriatrics >A parsimonious approach for screening moderate-to-profound hearing loss in a community-dwelling geriatric population based on a decision tree analysis
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A parsimonious approach for screening moderate-to-profound hearing loss in a community-dwelling geriatric population based on a decision tree analysis

机译：一种基于决策树分析的筛查社区老年人口中重度至重度听力损失的简约方法

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Hearing loss is one of the most common modifiable factors associated with cognitive and functional decline in geriatric populations. An accurate, easy-to-apply, and inexpensive hearing screening method is needed to detect hearing loss in community-dwelling elderly people, intervene early and reduce the negative consequences and burden of untreated hearing loss on individuals, families and society. However, available hearing screening tools do not adequately meet the need for large-scale geriatric hearing detection due to several barriers, including time, personnel training and equipment costs. This study aimed to propose an efficient method that could potentially satisfy this need. In total, 1793 participants (≥60?years) were recruited to undertake a standard audiometric air conduction pure tone test at 4 frequencies (0.5–4?kHz). Audiometric data from one community were used to train the decision tree model and generate a pure tone screening rule to classify people with or without moderate or more serious hearing impairment. Audiometric data from another community were used to validate the tree model. In the decision tree analysis, 2?kHz and 0.5?kHz were found to be the most important frequencies for hearing severity classification. The tree model suggested a simple two-step screening procedure in which a 42?dB HL tone at 2?kHz is presented first, followed by a 47?dB HL tone at 0.5?kHz, depending on the individual’s response to the first tone. This approach achieved an accuracy of 91.20% (91.92%), a sensitivity of 95.35% (93.50%) and a specificity of 86.85% (90.56%) in the training dataset (testing dataset). A simple two-step screening procedure using the two tones (2?kHz and 0.5?kHz) selected by the decision tree analysis can be applied to screen moderate-to-profound hearing loss in a community-based geriatric population in Shanghai. The decision tree analysis is useful in determining the optimal hearing screening criteria for local elderly populations. Implanting the pair of tones into a well-calibrated sound generator may create a simple, practical and time-efficient screening tool with high accuracy that is readily available at healthcare centers of all levels, thereby facilitating the initiation of extensive nationwide hearing screening in older adults.
机译：听力损失是与老年人口认知和功能下降相关的最常见可修正因素之一。需要一种准确，易于应用且廉价的听力筛查方法，以检测社区老人的听力损失，及早干预并减少对个人，家庭和社会的不良后果和未得到治疗的听力损失的负担。但是，由于时间，人员培训和设备成本等诸多障碍，现有的听力筛查工具无法充分满足大规模老年听力检测的需求。这项研究旨在提出一种可能满足这一需求的有效方法。总共招募了1793名参与者（≥60岁）在4个频率（0.5–4？kHz）上进行标准听力测听空气传导纯音测试。来自一个社区的测听数据用于训练决策树模型，并生成纯音调筛选规则，以对有或没有中度或更严重的听力障碍的人进行分类。来自另一个社区的测听数据用于验证树模型。在决策树分析中，发现2？kHz和0.5？kHz是听力严重度分类的最重要频率。树模型建议了一个简单的两步筛选程序，首先显示2？kHz的42？dB HL音，然后根据0.5？kHz的47？dB HL音，具体取决于个人对第一个音的反应。该方法在训练数据集（测试数据集）中实现了91.20％（91.92％）的准确性，95.35％（93.50％）的灵敏度和86.85％（90.56％）的特异性。通过决策树分析选择的两个音（2？kHz和0.5？kHz）进行的简单两步筛查程序可用于筛查上海市社区老年人口中度至重度的听力损失。决策树分析对于确定当地老年人群的最佳听力筛查标准很有用。将一对音调植入经过良好校准的声音发生器中，可以创建简单，实用且省时的高精度筛查工具，该工具可以在各个级别的医疗中心轻松使用，从而有助于开始对老年人进行广泛的全国性听力筛查。

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