Graduate School of Public Health, St. Luke's International University, Tokyo 104-0044, Japan.
Setagaya Memorial Hospital, Tokyo 158-0092, Japan.
Nutrients. 2021 Nov 10;13(11):4009. doi: 10.3390/nu13114009.
Sarcopenic dysphagia, a swallowing disorder caused by sarcopenia, is prevalent in older patients and can cause malnutrition and aspiration pneumonia. This study aimed to develop a simple screening test using image recognition with a low risk of droplet transmission for sarcopenic dysphagia.
Older patients admitted to a post-acute care hospital were enrolled in this cross-sectional study. As a main variable for the development of a screening test, we photographed the anterior neck to analyze the image features of sarcopenic dysphagia. The studied image features included the pixel values and the number of feature points. We constructed screening models using the image features, age, sex, and body mass index. The prediction performance of each model was investigated.
A total of 308 patients participated, including 175 (56.82%) patients without dysphagia and 133 (43.18%) with sarcopenic dysphagia. The area under the receiver operating characteristic curve (ROC-AUC), sensitivity, specificity, positive predictive value, negative predictive value, and area under the precision-recall curve (PR-AUC) values of the best model were 0.877, 87.50%, 76.67%, 66.67%, 92.00%, and 0.838, respectively. The model with image features alone showed an ROC-AUC of 0.814 and PR-AUC of 0.726.
The screening test for sarcopenic dysphagia using image recognition of neck appearance had high prediction performance.
由肌肉减少症引起的吞咽障碍——肌肉减少性吞咽困难，在老年患者中较为普遍，可导致营养不良和吸入性肺炎。本研究旨在开发一种使用图像识别的简单筛查试验，这种方法具有飞沫传播风险低的特点，可用于肌肉减少性吞咽困难的筛查。
本横断面研究纳入了入住一家康复医院的老年患者。我们拍摄了患者的颈部前位照片，以分析肌肉减少性吞咽困难的图像特征，并将其作为开发筛查试验的主要变量。所研究的图像特征包括像素值和特征点数量。我们使用图像特征、年龄、性别和体重指数构建了筛查模型。并对每个模型的预测性能进行了研究。
共有 308 名患者参与了研究，其中 175 名（56.82%）患者无吞咽困难，133 名（43.18%）患者存在肌肉减少性吞咽困难。最佳模型的受试者工作特征曲线下面积（ROC-AUC）、敏感度、特异度、阳性预测值、阴性预测值和精准度-召回曲线下面积（PR-AUC）分别为 0.877、87.50%、76.67%、66.67%、92.00%和 0.838。仅使用图像特征的模型的 ROC-AUC 为 0.814，PR-AUC 为 0.726。
使用颈部外观的图像识别来筛查肌肉减少性吞咽困难的方法具有较高的预测性能。
