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已发表论文
基于中国多中心研究的老年人中医体质与认知衰弱：预测模型及睡眠质量的中介作用路径
Authors Qiao M , Yang S, Ma Y, Chen C, Xu M, Gan H, Wu W
Received 1 August 2025
Accepted for publication 11 December 2025
Published 16 December 2025 Volume 2025:20 Pages 2607—2625
DOI https://doi.org/10.2147/CIA.S548401
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Maddalena Illario
Mengyuan Qiao,1 Sixiang Yang,1 Yuping Ma,2 Chongli Chen,1 Manru Xu,1 Hanyue Gan,1 Wenbin Wu1
1Department of Geriatrics, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People’s Republic of China; 2Department of Nephropathy Medicine, Affiliated Hospital of Panzhihua University, Panzhihua, Sichuan, People’s Republic of China
Correspondence: Wenbin Wu, Department of Geriatrics, Hospital of Chengdu University of Traditional Chinese Medicine, No. 39 Shi-er-qiao Road, Chengdu, Sichuan, 610072, People’s Republic of China, Email wwb1201@vip.sina.com
Purpose: To investigate the predictive value of Traditional Chinese Medicine Constitution (TCMC) in cognitive frailty (CF) among older adults and explore its potential influencing pathways.
Patients and Methods: From 2021 to 2023, a total of 905 older participants were recruited from three geographic regions in China: Southwest (Sichuan), East (Shanghai), and North (Beijing). A multidimensional survey (including TCMC assessment) was conducted. Prediction models were developed using nomogram and C5.0 decision tree algorithms. Internal and external validations were performed. The KHB method was applied for mediation analysis.
Results: Logistic regression identified Qi-stagnation constitution (QSC) and Qi-deficiency constitution (QDC) as important risk factors for CF (P < 0.01). Both the C5.0 decision tree model and Nomogram model based on TCMC demonstrated strong predictive performance (AUC=0.824 and 0.812, respectively). External validation indicated superior extrapolability of the C5.0 model (AUC=0.810 vs 0.772). Mediation analysis revealed that sleep quality partially mediated the association between QSC and CF (P < 0.05), with a mediation proportion of 22.7%.
Conclusion: QSC and QDC were identified as modifiable risk factors for CF. Prediction models based on TCMC demonstrated strong predictive performance and generalizability. Furthermore, QSC may worsen CF progression through its detrimental effects on sleep quality, identifying its clinical applicability as both a risk stratification factor and a prevention focus for CF.
Keywords: cognitive frailty, Traditional Chinese Medicine Constitution, prediction model, mediation effects analysis
1Department of Geriatrics, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People’s Republic of China; 2Department of Nephropathy Medicine, Affiliated Hospital of Panzhihua University, Panzhihua, Sichuan, People’s Republic of China
Correspondence: Wenbin Wu, Department of Geriatrics, Hospital of Chengdu University of Traditional Chinese Medicine, No. 39 Shi-er-qiao Road, Chengdu, Sichuan, 610072, People’s Republic of China, Email wwb1201@vip.sina.com
Purpose: To investigate the predictive value of Traditional Chinese Medicine Constitution (TCMC) in cognitive frailty (CF) among older adults and explore its potential influencing pathways.
Patients and Methods: From 2021 to 2023, a total of 905 older participants were recruited from three geographic regions in China: Southwest (Sichuan), East (Shanghai), and North (Beijing). A multidimensional survey (including TCMC assessment) was conducted. Prediction models were developed using nomogram and C5.0 decision tree algorithms. Internal and external validations were performed. The KHB method was applied for mediation analysis.
Results: Logistic regression identified Qi-stagnation constitution (QSC) and Qi-deficiency constitution (QDC) as important risk factors for CF (P < 0.01). Both the C5.0 decision tree model and Nomogram model based on TCMC demonstrated strong predictive performance (AUC=0.824 and 0.812, respectively). External validation indicated superior extrapolability of the C5.0 model (AUC=0.810 vs 0.772). Mediation analysis revealed that sleep quality partially mediated the association between QSC and CF (P < 0.05), with a mediation proportion of 22.7%.
Conclusion: QSC and QDC were identified as modifiable risk factors for CF. Prediction models based on TCMC demonstrated strong predictive performance and generalizability. Furthermore, QSC may worsen CF progression through its detrimental effects on sleep quality, identifying its clinical applicability as both a risk stratification factor and a prevention focus for CF.
Keywords: cognitive frailty, Traditional Chinese Medicine Constitution, prediction model, mediation effects analysis