医学
接收机工作特性
逻辑回归
曲线下面积
老人忧郁量表
横断面研究
物理疗法
内科学
认知
老年学
精神科
病理
抑郁症状
作者
Baolin Luo,Zebing Luo,Xiaoyun Zhang,Meiwan Xu,Chu-jun Shi
出处
期刊:BMJ Open
[BMJ]
日期:2022-12-01
卷期号:12 (12): e060633-e060633
标识
DOI:10.1136/bmjopen-2021-060633
摘要
To investigate the risk factors of cognitive frailty in elderly patients with chronic kidney disease (CKD), and to establish an artificial neural network (ANN) model.A cross-sectional design.Two tertiary hospitals in southern China.425 elderly patients aged ≥60 years with CKD.Data were collected via questionnaire investigation, anthropometric measurements, laboratory tests and electronic medical records. The 425 samples were randomly divided into a training set, test set and validation set at a ratio of 5:3:2. Variables were screened by univariate and multivariate logistic regression analyses, then an ANN model was constructed. The accuracy, specificity, sensitivity, receiver operating characteristic (ROC) curve and area under the ROC curve (AUC) were used to evaluate the predictive power of the model.Barthel Index (BI) score, albumin, education level, 15-item Geriatric Depression Scale score and Social Support Rating Scale score were the factors influencing the occurrence of cognitive frailty (p<0.05). Among them, BI score was the most important factor determining cognitive frailty, with an importance index of 0.30. The accuracy, specificity and sensitivity of the ANN model were 86.36%, 88.61% and 80.65%, respectively, and the AUC of the constructed ANN model was 0.913.The ANN model constructed in this study has good predictive ability, and can provide a reference tool for clinical nursing staff in the early prediction of cognitive frailty in a high-risk population.
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