Development and Validation of a Dynamic Nomogram for Predicting Cognitive Impairment Risk in Older Adults with Dentures: Analysis from CHARLS and CLHLS Data

Overview

Journal BMC Geriatr

Publisher Biomed Central

Specialty Geriatrics

Date 2025 Feb 25

PMID 40000983

Authors

Tongtong Guo

Xiaoqing Zhao

Xinyi Zhang

Yang Xing

Zhiwei Dong

Haiyan Li

Runguo Gao

Zhiping Huang

Xue Bai

Wengui Zheng

Qi Jing

Shanquan Chen

Affiliations

Soon will be listed here.

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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