Development and validation of a nomogram for predicting depression risk in patients with chronic kidney disease based on NHANES 2005–2018
Abstract Background Depression is common among patients with chronic kidney disease (CKD) and is associated with poor outcomes. This study aims to develop and validate a nomogram for predicting depression risk in patients with CKD. Methods This cross-sectional study utilized data from the 2005–2018...
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BMC
2025-04-01
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| Series: | Journal of Health, Population and Nutrition |
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| Online Access: | https://doi.org/10.1186/s41043-025-00890-7 |
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| author | Qiqi Yan Guiling Liu Ruifeng Wang Dandan Li Deguang Wang |
| author_facet | Qiqi Yan Guiling Liu Ruifeng Wang Dandan Li Deguang Wang |
| author_sort | Qiqi Yan |
| collection | DOAJ |
| description | Abstract Background Depression is common among patients with chronic kidney disease (CKD) and is associated with poor outcomes. This study aims to develop and validate a nomogram for predicting depression risk in patients with CKD. Methods This cross-sectional study utilized data from the 2005–2018 National Health and Nutrition Examination Survey (NHANES) database. Participants were randomly divided into training and validation sets (7:3 ratio). A nomogram was developed based on predictors identified using Least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariate logistic regression. Model performance was evaluated using ROC curves, calibration curves, and decision curve analysis. Results A total of 4414 participants were included. Gender, age, race, poverty-to-income ratio, diabetes mellitus, cardiovascular diseases, trouble sleeping, sleep hours, and smoking were included as predictors in the nomogram. The area under the curve (AUC) of the nomogram for predicting depression risk in patients with CKD was 0.785 (95% CI: 0.761–0.809) in the training set and 0.773 (95% CI: 0.737–0.810) in the validation set. The corrected C-index, calculated using bootstrap resampling, was 0.776, indicating good predictive performance. Calibration curves and decision curve analysis showed good calibration and clinical utility. Subgroup and sensitivity analyses further confirmed the robustness of the nomogram. A web-based risk calculator based on the nomogram was developed to enhance clinical applicability. A flowchart demonstrating the application of the nomogram for risk assessment and clinical decision-making in routine practice is provided. Conclusions This nomogram effectively predicts depression risk in patients with CKD and may serve as a user-friendly tool for the early identification of patients with CKD at high risk for depression using key demographic, comorbid, and lifestyle factors. |
| format | Article |
| id | doaj-art-cc963dfb551945d7b01aeefe3ec5d220 |
| institution | OA Journals |
| issn | 2072-1315 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | BMC |
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| series | Journal of Health, Population and Nutrition |
| spelling | doaj-art-cc963dfb551945d7b01aeefe3ec5d2202025-08-20T02:19:58ZengBMCJournal of Health, Population and Nutrition2072-13152025-04-0144111310.1186/s41043-025-00890-7Development and validation of a nomogram for predicting depression risk in patients with chronic kidney disease based on NHANES 2005–2018Qiqi Yan0Guiling Liu1Ruifeng Wang2Dandan Li3Deguang Wang4Department of Nephrology, the Second Affiliated Hospital of Anhui Medical UniversityDepartment of Nephrology, the Second Affiliated Hospital of Anhui Medical UniversityDepartment of Nephrology, the Second Affiliated Hospital of Anhui Medical UniversityDepartment of Nephrology, the Second Affiliated Hospital of Anhui Medical UniversityDepartment of Nephrology, the Second Affiliated Hospital of Anhui Medical UniversityAbstract Background Depression is common among patients with chronic kidney disease (CKD) and is associated with poor outcomes. This study aims to develop and validate a nomogram for predicting depression risk in patients with CKD. Methods This cross-sectional study utilized data from the 2005–2018 National Health and Nutrition Examination Survey (NHANES) database. Participants were randomly divided into training and validation sets (7:3 ratio). A nomogram was developed based on predictors identified using Least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariate logistic regression. Model performance was evaluated using ROC curves, calibration curves, and decision curve analysis. Results A total of 4414 participants were included. Gender, age, race, poverty-to-income ratio, diabetes mellitus, cardiovascular diseases, trouble sleeping, sleep hours, and smoking were included as predictors in the nomogram. The area under the curve (AUC) of the nomogram for predicting depression risk in patients with CKD was 0.785 (95% CI: 0.761–0.809) in the training set and 0.773 (95% CI: 0.737–0.810) in the validation set. The corrected C-index, calculated using bootstrap resampling, was 0.776, indicating good predictive performance. Calibration curves and decision curve analysis showed good calibration and clinical utility. Subgroup and sensitivity analyses further confirmed the robustness of the nomogram. A web-based risk calculator based on the nomogram was developed to enhance clinical applicability. A flowchart demonstrating the application of the nomogram for risk assessment and clinical decision-making in routine practice is provided. Conclusions This nomogram effectively predicts depression risk in patients with CKD and may serve as a user-friendly tool for the early identification of patients with CKD at high risk for depression using key demographic, comorbid, and lifestyle factors.https://doi.org/10.1186/s41043-025-00890-7Cross-sectional studyChronic kidney diseaseDepressionNomogramQuestionnaireSociodemographic characteristics |
| spellingShingle | Qiqi Yan Guiling Liu Ruifeng Wang Dandan Li Deguang Wang Development and validation of a nomogram for predicting depression risk in patients with chronic kidney disease based on NHANES 2005–2018 Journal of Health, Population and Nutrition Cross-sectional study Chronic kidney disease Depression Nomogram Questionnaire Sociodemographic characteristics |
| title | Development and validation of a nomogram for predicting depression risk in patients with chronic kidney disease based on NHANES 2005–2018 |
| title_full | Development and validation of a nomogram for predicting depression risk in patients with chronic kidney disease based on NHANES 2005–2018 |
| title_fullStr | Development and validation of a nomogram for predicting depression risk in patients with chronic kidney disease based on NHANES 2005–2018 |
| title_full_unstemmed | Development and validation of a nomogram for predicting depression risk in patients with chronic kidney disease based on NHANES 2005–2018 |
| title_short | Development and validation of a nomogram for predicting depression risk in patients with chronic kidney disease based on NHANES 2005–2018 |
| title_sort | development and validation of a nomogram for predicting depression risk in patients with chronic kidney disease based on nhanes 2005 2018 |
| topic | Cross-sectional study Chronic kidney disease Depression Nomogram Questionnaire Sociodemographic characteristics |
| url | https://doi.org/10.1186/s41043-025-00890-7 |
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