Zhou Tong, Zhang Heping, Zhao Jiayu, Ren Zhouting, Ma Yimei, He Linqian, Liu Jiali, Tang Jincheng, Luo Jiaming
Department of Nephrology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Department of Physician, Nanchong Psychosomatic Hospital, Nanchong, China.
Heliyon. 2024 Apr 23;10(9):e30032. doi: 10.1016/j.heliyon.2024.e30032. eCollection 2024 May 15.
Cognitive function impairment (CFI) is common in patients with chronic kidney disease (CKD) and significantly impacts treatment adherence and quality of life. This study aims to create a simplified nomogram for early CFI risk detection.
Data were obtained from the National Health and Nutrition Examination Survey cycles spanning from 1999 to 2002 and again from 2011 to 2014. Stepwise logistic regression was used to select variables and construct a CFI risk prediction model. Furthermore, C-statistic and Brier Score (BS) assessed model performance. Additionally, Kaplan-Meier survival curves were utilised to assess risk group-death prognosis relationships.
Of the 545 participants in the CKD model development cohort, a total of 146 (26.8 %) had CFI. The final model included the variables of age, race, education, annual family income, body mass index, estimated glomerular filtration rate, serum albumin and uric acid. The model had a C-statistic of 0.808 (95 % confidence interval (CI): 0.769-0.847) and a BS of 0.149. Furthermore, the 5-fold cross-validation internal C-statistic was 0.764 (interquartile range: 0.763-0.807) and BS was 0.154. Upon external validation, the model's C-statistic decreased to 0.752 (95 % CI: 0.654-0.850) and its BS increased to 0.182. The Kaplan-Meier survival curves demonstrated that intermediate-to-high-risk participants had shorter overall survival time than low-risk participants (log-rank test: p = 0.00042).
This study established an effective nomogram for predicting CFI in patients with CKD, which can be used for the early detection of CFI and guide the treatment of patients with CKD.
认知功能障碍（CFI）在慢性肾脏病（CKD）患者中很常见，并且显著影响治疗依从性和生活质量。本研究旨在创建一个简化的列线图用于早期CFI风险检测。
数据来自1999年至2002年以及2011年至2014年的国家健康和营养检查调查周期。采用逐步逻辑回归选择变量并构建CFI风险预测模型。此外，使用C统计量和Brier评分（BS）评估模型性能。另外，利用Kaplan-Meier生存曲线评估风险组与死亡预后的关系。
在CKD模型开发队列的545名参与者中，共有146名（26.8%）患有CFI。最终模型纳入了年龄、种族、教育程度、家庭年收入、体重指数、估计肾小球滤过率、血清白蛋白和尿酸等变量。该模型的C统计量为0.808（95%置信区间（CI）：0.769-0.847），BS为0.149。此外，5倍交叉验证的内部C统计量为0.764（四分位间距：0.763-0.807），BS为0.154。在外部验证时，模型的C统计量降至0.752（95%CI：0.654-0.850），其BS升至0.182。Kaplan-Meier生存曲线表明，中高风险参与者的总生存时间比低风险参与者短（对数秩检验：p = 0.00042）。
本研究建立了一种有效的列线图用于预测CKD患者的CFI，可用于CFI的早期检测并指导CKD患者治疗。
