Guo Tongtong, Zhao Xiaoqing, Zhang Xinyi, Xing Yang, Dong Zhiwei, Li Haiyan, Gao Runguo, Huang Zhiping, Bai Xue, Zheng Wengui, Jing Qi, Chen Shanquan
School of Management, Shandong Second Medical University, Weifang, China.
Health Shandong Collaborative Innovation Center for Severe Social Risk Prediction and Governance, Weifang, China.
BMC Geriatr. 2025 Feb 25;25(1):127. doi: 10.1186/s12877-025-05758-3.
Cognitive impairment is a common issue among older adults, with denture use identified as a potential, easily recognizable clinical risk factor. However, the link between denture wear and cognitive decline in older Chinese adults remains understudied. This study aimed to develop and validate a dynamic nomogram to predict the risk of cognitive impairment in community-dwelling older adults who wear dentures.
We selected 2066 elderly people with dentures from CHARLS2018 data as the development and internal validation group and 3840 people from CLHLS2018 as the external validation group. Develop and treat the concentrated unbalanced data with the synthetic minority oversampling technique, select the best predictors with the LASSO regression ten-fold cross-validation method, analyze the influencing factors of cognitive impairment in the elderly with dentures using Logistic regression, and construct a nomogram. Subject operating characteristic curves, sensitivity, specificity, accuracy, precision, F1 score, calibration curve, and decision curve were used to evaluate the validity of the model in terms of identification, calibration, and clinical validity.
We identified five factors (age, residence, education, instrumental activities of daily living, and depression) to construct the nomogram. The area under the curve of the prediction model was 0.854 (95%CI 0.839-0.870) in the development set, 0.841 (95%CI 0.805-0.877) in the internal validation set, and 0.856 (95%CI 0.838-0.873) in the external validation set. Calibration curves indicated significant agreement between predicted and actual values, and decision curve analysis demonstrated valuable clinical application.
Five risk factors, including age, place of residence, education, instrumental activities of daily living, and depression level, were selected as the final nomogram to predict the risk of cognitive impairment in elderly denture wearers. The nomogram has acceptable discrimination and can be used by healthcare professionals and community health workers to plan preventive interventions for cognitive impairment among older denture-wearing populations.
认知障碍是老年人中的常见问题,佩戴假牙被认为是一个潜在的、易于识别的临床风险因素。然而,中国老年人群中佩戴假牙与认知功能下降之间的联系仍未得到充分研究。本研究旨在开发并验证一种动态列线图,以预测社区居住的佩戴假牙老年人认知障碍的风险。
我们从CHARLS2018数据中选取2066名佩戴假牙的老年人作为开发和内部验证组,并从CLHLS2018中选取3840人作为外部验证组。采用合成少数过采样技术对集中不平衡数据进行开发和处理,使用LASSO回归十折交叉验证法选择最佳预测因素,采用Logistic回归分析佩戴假牙老年人认知障碍的影响因素,并构建列线图。使用受试者工作特征曲线、灵敏度、特异度、准确度、精确率、F1分数、校准曲线和决策曲线,从识别、校准和临床有效性方面评估模型的有效性。
我们确定了五个因素(年龄、居住地、教育程度、日常生活工具性活动和抑郁)来构建列线图。预测模型在开发集中的曲线下面积为0.854(95%CI 0.839 - 0.870),在内部验证集中为0.841(95%CI 0.805 - 0.877),在外部验证集中为0.856(95%CI 0.838 - 0.873)。校准曲线表明预测值与实际值之间具有显著一致性,决策曲线分析显示出有价值的临床应用。
年龄、居住地、教育程度、日常生活工具性活动和抑郁水平这五个风险因素被选为最终列线图,以预测佩戴假牙老年人认知障碍的风险。该列线图具有可接受的区分度,医疗保健专业人员和社区卫生工作者可利用它为佩戴假牙的老年人群规划认知障碍的预防干预措施。