Prediction of the risk of 3-year chronic kidney disease among elderly people: a community-based cohort study
AbstractObjective We conducted a community-based cohort study to predict the 3-year occurrence of chronic kidney disease (CKD) among population aged ≥60 years.Method Participants were selected from two communities through randomized cluster sampling in Jiading District of Shanghai, China. The two co...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | Renal Failure |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/0886022X.2024.2303205 |
| _version_ | 1797316674478669824 |
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| author | Tao Wang Zhitong Zhou Longbing Ren Zhiping Shen Jue Li Lijuan Zhang |
| author_facet | Tao Wang Zhitong Zhou Longbing Ren Zhiping Shen Jue Li Lijuan Zhang |
| author_sort | Tao Wang |
| collection | DOAJ |
| description | AbstractObjective We conducted a community-based cohort study to predict the 3-year occurrence of chronic kidney disease (CKD) among population aged ≥60 years.Method Participants were selected from two communities through randomized cluster sampling in Jiading District of Shanghai, China. The two communities were randomly divided into a development cohort (n = 12012) and a validation cohort (n = 6248) with a 3-year follow-up. Logistic regression analysis was used to determine the independent predictors. A nomogram was established to predict the occurrence of CKD within 3 years. The area under the curve (AUC), the calibration curve and decision curve analysis (DCA) curve were used to evaluate the model.Result At baseline, participants in development cohort and validation cohort were with the mean age of 68.24 ± 5.87 and 67.68 ± 5.26 years old, respectively. During 3 years, 1516 (12.6%) and 544 (8.9%) new cases developed CKD in the development and validation cohorts, respectively. Nine variables (age, systolic blood pressure, body mass index, exercise, previous hypertension, triglycerides, fasting plasma glucose, glycated hemoglobin and serum creatinine) were included in the prediction model. The AUC value was 0.742 [95% confidence interval (CI), 0.728–0.756] in the development cohort and 0.881(95%CI, 0.867–0.895) in the validation cohort, respectively. The calibration curves and DCA curves demonstrate an effective predictive model.Conclusion Our nomogram model is a simple, reasonable and reliable tool for predicting the risk of 3-year CKD in community-dwelling elderly people, which is helpful for timely intervention and reducing the incidence of CKD. |
| first_indexed | 2024-03-08T03:22:44Z |
| format | Article |
| id | doaj.art-96509047a27e41c6b540b26b97f3a011 |
| institution | Directory Open Access Journal |
| issn | 0886-022X 1525-6049 |
| language | English |
| last_indexed | 2024-03-08T03:22:44Z |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Renal Failure |
| spelling | doaj.art-96509047a27e41c6b540b26b97f3a0112024-02-12T08:09:41ZengTaylor & Francis GroupRenal Failure0886-022X1525-60492024-12-0146110.1080/0886022X.2024.2303205Prediction of the risk of 3-year chronic kidney disease among elderly people: a community-based cohort studyTao Wang0Zhitong Zhou1Longbing Ren2Zhiping Shen3Jue Li4Lijuan Zhang5Clinical Center for Intelligent Rehabilitation Research, Shanghai YangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), Tongji University School of Medicine, Tongji University, Shanghai, ChinaClinical Center for Intelligent Rehabilitation Research, Shanghai YangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), Tongji University School of Medicine, Tongji University, Shanghai, ChinaClinical Center for Intelligent Rehabilitation Research, Shanghai YangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), Tongji University School of Medicine, Tongji University, Shanghai, ChinaCommunity Health Service Center of Anting Town Affiliated to Tongji University School of Medicine, Tongji University, Shanghai, ChinaClinical Center for Intelligent Rehabilitation Research, Shanghai YangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), Tongji University School of Medicine, Tongji University, Shanghai, ChinaClinical Center for Intelligent Rehabilitation Research, Shanghai YangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), Tongji University School of Medicine, Tongji University, Shanghai, ChinaAbstractObjective We conducted a community-based cohort study to predict the 3-year occurrence of chronic kidney disease (CKD) among population aged ≥60 years.Method Participants were selected from two communities through randomized cluster sampling in Jiading District of Shanghai, China. The two communities were randomly divided into a development cohort (n = 12012) and a validation cohort (n = 6248) with a 3-year follow-up. Logistic regression analysis was used to determine the independent predictors. A nomogram was established to predict the occurrence of CKD within 3 years. The area under the curve (AUC), the calibration curve and decision curve analysis (DCA) curve were used to evaluate the model.Result At baseline, participants in development cohort and validation cohort were with the mean age of 68.24 ± 5.87 and 67.68 ± 5.26 years old, respectively. During 3 years, 1516 (12.6%) and 544 (8.9%) new cases developed CKD in the development and validation cohorts, respectively. Nine variables (age, systolic blood pressure, body mass index, exercise, previous hypertension, triglycerides, fasting plasma glucose, glycated hemoglobin and serum creatinine) were included in the prediction model. The AUC value was 0.742 [95% confidence interval (CI), 0.728–0.756] in the development cohort and 0.881(95%CI, 0.867–0.895) in the validation cohort, respectively. The calibration curves and DCA curves demonstrate an effective predictive model.Conclusion Our nomogram model is a simple, reasonable and reliable tool for predicting the risk of 3-year CKD in community-dwelling elderly people, which is helpful for timely intervention and reducing the incidence of CKD.https://www.tandfonline.com/doi/10.1080/0886022X.2024.2303205Chronic kidney diseaserisk prediction modelnomogramelderly peoplecommunity-based cohort study |
| spellingShingle | Tao Wang Zhitong Zhou Longbing Ren Zhiping Shen Jue Li Lijuan Zhang Prediction of the risk of 3-year chronic kidney disease among elderly people: a community-based cohort study Renal Failure Chronic kidney disease risk prediction model nomogram elderly people community-based cohort study |
| title | Prediction of the risk of 3-year chronic kidney disease among elderly people: a community-based cohort study |
| title_full | Prediction of the risk of 3-year chronic kidney disease among elderly people: a community-based cohort study |
| title_fullStr | Prediction of the risk of 3-year chronic kidney disease among elderly people: a community-based cohort study |
| title_full_unstemmed | Prediction of the risk of 3-year chronic kidney disease among elderly people: a community-based cohort study |
| title_short | Prediction of the risk of 3-year chronic kidney disease among elderly people: a community-based cohort study |
| title_sort | prediction of the risk of 3 year chronic kidney disease among elderly people a community based cohort study |
| topic | Chronic kidney disease risk prediction model nomogram elderly people community-based cohort study |
| url | https://www.tandfonline.com/doi/10.1080/0886022X.2024.2303205 |
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