Status of cognitive frailty in elderly patients with chronic kidney disease and construction of a risk prediction model: a cross-sectional study
Objective 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.Design A cross-sectional design.Setting Two tertiary hospitals in southern China.Participants 425 elderly patients aged ≥60...
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| Format: | Article |
| Language: | English |
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BMJ Publishing Group
2022-12-01
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| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/12/12/e060633.full |
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| author | Xiaoyun Zhang Baolin Luo Zebing Luo Meiwan Xu Chujun Shi |
| author_facet | Xiaoyun Zhang Baolin Luo Zebing Luo Meiwan Xu Chujun Shi |
| author_sort | Xiaoyun Zhang |
| collection | DOAJ |
| description | Objective 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.Design A cross-sectional design.Setting Two tertiary hospitals in southern China.Participants 425 elderly patients aged ≥60 years with CKD.Methods 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.Results 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.Conclusion 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. |
| format | Article |
| id | doaj-art-0b43f313762c423797fea7d3dd176f69 |
| institution | Kabale University |
| issn | 2044-6055 |
| language | English |
| publishDate | 2022-12-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Open |
| spelling | doaj-art-0b43f313762c423797fea7d3dd176f692025-08-20T03:52:32ZengBMJ Publishing GroupBMJ Open2044-60552022-12-01121210.1136/bmjopen-2021-060633Status of cognitive frailty in elderly patients with chronic kidney disease and construction of a risk prediction model: a cross-sectional studyXiaoyun Zhang0Baolin Luo1Zebing Luo2Meiwan Xu3Chujun Shi4Department of Endocrinology, Sun Yat-Sen Memorial Hospital, Guangzhou, China1 Department of Cardiac Surgery Nursing, Fujian Medical University Union Hospital, Fuzhou, China1 School of Nursing, Shantou University Medical College, Shantou, Guangdong, China5 Nephrology Department, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China1 School of Nursing, Shantou University Medical College, Shantou, Guangdong, ChinaObjective 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.Design A cross-sectional design.Setting Two tertiary hospitals in southern China.Participants 425 elderly patients aged ≥60 years with CKD.Methods 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.Results 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.Conclusion 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.https://bmjopen.bmj.com/content/12/12/e060633.full |
| spellingShingle | Xiaoyun Zhang Baolin Luo Zebing Luo Meiwan Xu Chujun Shi Status of cognitive frailty in elderly patients with chronic kidney disease and construction of a risk prediction model: a cross-sectional study BMJ Open |
| title | Status of cognitive frailty in elderly patients with chronic kidney disease and construction of a risk prediction model: a cross-sectional study |
| title_full | Status of cognitive frailty in elderly patients with chronic kidney disease and construction of a risk prediction model: a cross-sectional study |
| title_fullStr | Status of cognitive frailty in elderly patients with chronic kidney disease and construction of a risk prediction model: a cross-sectional study |
| title_full_unstemmed | Status of cognitive frailty in elderly patients with chronic kidney disease and construction of a risk prediction model: a cross-sectional study |
| title_short | Status of cognitive frailty in elderly patients with chronic kidney disease and construction of a risk prediction model: a cross-sectional study |
| title_sort | status of cognitive frailty in elderly patients with chronic kidney disease and construction of a risk prediction model a cross sectional study |
| url | https://bmjopen.bmj.com/content/12/12/e060633.full |
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