Development and validation of a dynamic nomogram for predicting cognitive impairment risk in older adults with dentures: analysis from CHARLS and CLHLS data.

IF 3.8 2区 医学 Q2 GERIATRICS & GERONTOLOGY BMC Geriatrics Pub Date : 2025-02-25 DOI:10.1186/s12877-025-05758-3
Tongtong Guo, Xiaoqing Zhao, Xinyi Zhang, Yang Xing, Zhiwei Dong, Haiyan Li, Runguo Gao, Zhiping Huang, Xue Bai, Wengui Zheng, Qi Jing, Shanquan Chen
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Abstract

Background and aims: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

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预测假牙老年人认知障碍风险的动态图的开发和验证:来自CHARLS和CLHLS数据的分析
背景和目的:认知障碍是老年人的一个常见问题,假牙的使用被认为是一个潜在的,容易识别的临床危险因素。然而,假牙佩戴与中国老年人认知能力下降之间的关系仍未得到充分研究。本研究旨在开发和验证一个动态nomogram来预测佩戴假牙的社区老年人认知功能障碍的风险。方法:选取CHARLS2018数据中的2066例老年义齿患者作为开发和内部验证组,CLHLS2018数据中的3840例作为外部验证组。采用合成少数过抽样技术对集中的不平衡数据进行开发和处理,采用LASSO回归十倍交叉验证法筛选最佳预测因子,采用Logistic回归分析老年义齿认知功能障碍的影响因素,构建nomogram。采用受试者工作特征曲线、敏感性、特异性、准确度、精密度、F1评分、校准曲线和决策曲线评价模型在识别、校准和临床效度方面的有效性。结果:我们确定了五个因素(年龄、居住地、教育程度、日常生活工具活动和抑郁)来构建nomogram。预测模型的曲线下面积在开发集为0.854 (95%CI 0.839 ~ 0.870),在内部验证集为0.841 (95%CI 0.805 ~ 0.877),在外部验证集为0.856 (95%CI 0.838 ~ 0.873)。校正曲线预测值与实际值吻合较好,决策曲线分析具有临床应用价值。结论:选择年龄、居住地、受教育程度、日常生活工具活动、抑郁程度等5个危险因素作为预测老年义齿佩戴者认知功能障碍风险的最终nomogram。该图具有可接受的区别,可被卫生保健专业人员和社区卫生工作者用于规划老年假牙佩戴人群认知障碍的预防性干预措施。
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来源期刊
BMC Geriatrics
BMC Geriatrics GERIATRICS & GERONTOLOGY-
CiteScore
5.70
自引率
7.30%
发文量
873
审稿时长
20 weeks
期刊介绍: BMC Geriatrics is an open access journal publishing original peer-reviewed research articles in all aspects of the health and healthcare of older people, including the effects of healthcare systems and policies. The journal also welcomes research focused on the aging process, including cellular, genetic, and physiological processes and cognitive modifications.
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