Body composition as a potential imaging biomarker for predicting the progression risk of chronic kidney disease
Abstract Purpose To investigate whether the body composition parameters can be employed as potential biomarkers for predicting the progression risk of chronic kidney disease (CKD). Materials and methods Four hundred sixteen patients diagnosed with CKD were included in this retrospective study. Patie...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2024-10-01
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| Series: | Insights into Imaging |
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| Online Access: | https://doi.org/10.1186/s13244-024-01826-1 |
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| author | Zhouyan Liao Guanjie Yuan Kangwen He Shichao Li Mengmeng Gao Ping Liang Chuou Xu Qian Chu Min Han Zhen Li |
| author_facet | Zhouyan Liao Guanjie Yuan Kangwen He Shichao Li Mengmeng Gao Ping Liang Chuou Xu Qian Chu Min Han Zhen Li |
| author_sort | Zhouyan Liao |
| collection | DOAJ |
| description | Abstract Purpose To investigate whether the body composition parameters can be employed as potential biomarkers for predicting the progression risk of chronic kidney disease (CKD). Materials and methods Four hundred sixteen patients diagnosed with CKD were included in this retrospective study. Patients with a greater than 50% decline in estimated glomerular filtration rate or progression to end-stage kidney disease were in the high-risk group, otherwise, they were in a low-risk group. Body composition area, the index, and radiodensities in the Hounsfield unit (HU), which reflect the degree of X-ray absorption, were measured on abdominal CT images. Risk factors in body composition and clinical parameters of CKD were identified by Cox regression and utilized to construct the nomogram. The performance of the nomogram was assessed using time receiver operating characteristics curves, calibration curves, and decision curve analysis. Results There were 254 patients in low-risk group and 162 in high-risk group (268 males, 148 females, mean age: 55.89 years). Urea, diabetes, 24 h-urinary protein, mean arterial pressure, and subcutaneous adipose tissue radiodensity (SATd) were valuable indicators for predicting the high-risk group. The area under curve values for the nomogram of training/validation set at 1 year, 2 years, and 3 years were 0.805/0.753, 0.784/0.783, and 0.846/0.754, respectively. For diabetic CKD patients, extra attention needs to be paid to visceral to subcutaneous fat ratio and renal sinus fat radiodensity. Conclusion SATd was the most valuable noninvasive indicator of all body composition parameters for predicting high-risk populations with CKD. The nomogram we constructed has generalization with easily obtainable indicators, good performance, differentiation, and clinical practicability. Critical relevance statement Radiodensity rather than an area of adipose tissue can be used as a new biomarker of prognosis for CKD patients, providing new insights into risk assessment, stratified management, and treatment for CKD patients. Key Points Obesity is an independent risk factor for the development and prognosis of CKD. Adipose tissue radiodensity is more valuable than fat area in prognosticating for kidney disease. Parameters that prognosticate in diabetic CKD patients are different from those in other CKD patients. Graphical Abstract |
| format | Article |
| id | doaj-art-6dca8c71b0f144258e8fdf9feff4d8a3 |
| institution | OA Journals |
| issn | 1869-4101 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Insights into Imaging |
| spelling | doaj-art-6dca8c71b0f144258e8fdf9feff4d8a32025-08-20T02:17:53ZengSpringerOpenInsights into Imaging1869-41012024-10-0115111410.1186/s13244-024-01826-1Body composition as a potential imaging biomarker for predicting the progression risk of chronic kidney diseaseZhouyan Liao0Guanjie Yuan1Kangwen He2Shichao Li3Mengmeng Gao4Ping Liang5Chuou Xu6Qian Chu7Min Han8Zhen Li9Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and TechnologyDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and TechnologyDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and TechnologyDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and TechnologyDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and TechnologyDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and TechnologyDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and TechnologyDepartment of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and TechnologyDepartment of Nephrology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and TechnologyDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and TechnologyAbstract Purpose To investigate whether the body composition parameters can be employed as potential biomarkers for predicting the progression risk of chronic kidney disease (CKD). Materials and methods Four hundred sixteen patients diagnosed with CKD were included in this retrospective study. Patients with a greater than 50% decline in estimated glomerular filtration rate or progression to end-stage kidney disease were in the high-risk group, otherwise, they were in a low-risk group. Body composition area, the index, and radiodensities in the Hounsfield unit (HU), which reflect the degree of X-ray absorption, were measured on abdominal CT images. Risk factors in body composition and clinical parameters of CKD were identified by Cox regression and utilized to construct the nomogram. The performance of the nomogram was assessed using time receiver operating characteristics curves, calibration curves, and decision curve analysis. Results There were 254 patients in low-risk group and 162 in high-risk group (268 males, 148 females, mean age: 55.89 years). Urea, diabetes, 24 h-urinary protein, mean arterial pressure, and subcutaneous adipose tissue radiodensity (SATd) were valuable indicators for predicting the high-risk group. The area under curve values for the nomogram of training/validation set at 1 year, 2 years, and 3 years were 0.805/0.753, 0.784/0.783, and 0.846/0.754, respectively. For diabetic CKD patients, extra attention needs to be paid to visceral to subcutaneous fat ratio and renal sinus fat radiodensity. Conclusion SATd was the most valuable noninvasive indicator of all body composition parameters for predicting high-risk populations with CKD. The nomogram we constructed has generalization with easily obtainable indicators, good performance, differentiation, and clinical practicability. Critical relevance statement Radiodensity rather than an area of adipose tissue can be used as a new biomarker of prognosis for CKD patients, providing new insights into risk assessment, stratified management, and treatment for CKD patients. Key Points Obesity is an independent risk factor for the development and prognosis of CKD. Adipose tissue radiodensity is more valuable than fat area in prognosticating for kidney disease. Parameters that prognosticate in diabetic CKD patients are different from those in other CKD patients. Graphical Abstracthttps://doi.org/10.1186/s13244-024-01826-1Chronic kidney diseaseObesityProgression riskComputed tomographyAdipose tissue radiodensity |
| spellingShingle | Zhouyan Liao Guanjie Yuan Kangwen He Shichao Li Mengmeng Gao Ping Liang Chuou Xu Qian Chu Min Han Zhen Li Body composition as a potential imaging biomarker for predicting the progression risk of chronic kidney disease Insights into Imaging Chronic kidney disease Obesity Progression risk Computed tomography Adipose tissue radiodensity |
| title | Body composition as a potential imaging biomarker for predicting the progression risk of chronic kidney disease |
| title_full | Body composition as a potential imaging biomarker for predicting the progression risk of chronic kidney disease |
| title_fullStr | Body composition as a potential imaging biomarker for predicting the progression risk of chronic kidney disease |
| title_full_unstemmed | Body composition as a potential imaging biomarker for predicting the progression risk of chronic kidney disease |
| title_short | Body composition as a potential imaging biomarker for predicting the progression risk of chronic kidney disease |
| title_sort | body composition as a potential imaging biomarker for predicting the progression risk of chronic kidney disease |
| topic | Chronic kidney disease Obesity Progression risk Computed tomography Adipose tissue radiodensity |
| url | https://doi.org/10.1186/s13244-024-01826-1 |
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