Royal Devon University Healthcare NHS Foundation Trust, Exeter, UK.
School of Psychology & Clinical Language Sciences, University of Reading, Reading, UK.
Eur Arch Otorhinolaryngol. 2023 Nov;280(11):5101-5114. doi: 10.1007/s00405-023-08153-z. Epub 2023 Aug 6.
The contributing factors of aspiration pneumonia have been well documented. However, there are gaps in the literature regarding identifying the weight associated with each factor and the relationship between factors.
In this study, 20 potential predictors of aspiration pneumonia (with four additional variables) have been applied to historic Speech and Language Therapy records to greater understand the significance of each contributor of aspiration pneumonia. 152 cases with an oropharyngeal dysphagia, and a Speech and Language Therapy recommendation of eating and drinking with known aspiration and the associated potential risk of developing an aspiration pneumonia, were included in the data. These were inpatients and outpatients, and had various diagnoses but all had had a videofluoroscopy.
Logistic regression analysis found seven factors that were individually significant in predicting the development of aspiration pneumonia with 84.93% sensitivity and 91.03% specificity DISCUSSION: Logistic regression and random forest analyses led to the proposal of a new matrix of predictors of aspiration pneumonia with respective scoring weights for individual and cumulative contributors (a direction for future research).
吸入性肺炎的致病因素已有相关记载。然而，文献中仍存在一些空白，无法确定每个因素的权重以及因素之间的关系。
本研究将 20 个可能导致吸入性肺炎的预测因子（外加 4 个额外变量）应用于历史言语治疗记录中，以更深入地了解吸入性肺炎各致病因素的重要性。共有 152 例口咽吞咽困难的患者，言语治疗师建议进食和饮水，并已知存在吸入风险，且可能发展为吸入性肺炎，将这些患者纳入本研究的数据中。这些患者包括住院患者和门诊患者，他们有各种不同的诊断，但都进行了视频透视检查。
逻辑回归分析发现，有 7 个因素可单独显著预测吸入性肺炎的发生，其敏感性为 84.93%，特异性为 91.03%。
逻辑回归和随机森林分析提出了一种新的吸入性肺炎预测因子矩阵，以及针对个体和累积因素的评分权重（未来研究方向）。
