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Li Y, Yang J, Chen Y, Cui W, Wang J, Zhang C, Zhu L, Bian C, Luo T. Prognostic nomogram for the patency of wrist autologous arteriovenous fistula in first year. iScience 2024; 27:110727. [PMID: 39310751 PMCID: PMC11416551 DOI: 10.1016/j.isci.2024.110727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 05/19/2024] [Accepted: 08/09/2024] [Indexed: 09/25/2024] Open
Abstract
Autologous arteriovenous fistula (AVF) is preferred in hemodialysis patients. Maintaining its patency is a critical problem. This study aimed to create a nomogram model for predicting 1-year primary patency of AVF. Consequently, a total of 414 patients were retrospectively enrolled and randomly allocated to training and validation cohorts. Risk factors were identified by multivariable logistic regression and used to create a nomogram model. Performance of the model was evaluated by receiver operating characteristic (ROC) curve, Hosmer-Lemeshow test, and calibration curve. The results suggested that diameter of cephalic vein, low-density lipoprotein, glycosylated hemoglobin (%), and C-reactive protein were risk factors which could predict the patency of AVF. Area under ROC curves for training and validation cohorts were 0.771 and 0.794, respectively. Calibration ability was satisfactory in both cohorts. Therefore, present nomogram model could predict the 1-year primary patency of AVF.
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Affiliation(s)
- Yu Li
- Department of General Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jinming Yang
- Department of Vascular Intervention, Aerospace Center Hospital, Beijing, China
| | - Yue Chen
- Department of General Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Wenhao Cui
- Department of General Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jukun Wang
- Department of General Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Chao Zhang
- Department of General Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Linzhong Zhu
- Department of General Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Chunjing Bian
- Department of General Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Tao Luo
- Department of General Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China
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Milosevic T, Naumovic R, Sopic M, Vekic J, Guzonjic A, Pesic S, Miljkovic-Trailovic M, Kotur-Stevuljevic J. COVID-19 increases mortality in hemodialysis patients: exploring links with inflammation and telomere attrition. Mol Biol Rep 2024; 51:938. [PMID: 39190187 DOI: 10.1007/s11033-024-09879-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2024] [Accepted: 08/21/2024] [Indexed: 08/28/2024]
Abstract
BACKGROUND AND OBJECTIVE An increased risk of mortality and hospitalization was consistently demonstrated in hemodialysis (HD) patients affected by pandemic coronavirus infection (COVID-19). In this study, we analyzed parameters that may impact mortality in COVID-19 HD patients, including neutrophil-to-lymphocyte ratio (NLR), lactate dehydrogenase (LDH), C-reactive protein (CRP), COVID-19 disease status and telomere length in peripheral blood cells (TL). MATERIALS AND METHODS A total of 130 chronic hemodialysis patients were enrolled and followed up for 18 months. Patients were categorized into groups based on their COVID-19 disease history and subsequent data about their survival status at the end of the study. Routine laboratory parameters were assessed using standard automated methods and TL was determined using the modified Cawthon method. Survival predictors were analyzed using Kaplan-Meier analysis. RESULTS Deceased patients (30%) were older with higher body mass index (BMI), higher levels of LDH, NLR index, CRP and lower TL and lymphocytes count compared to survivors. Kaplan-Meier survival analysis showed six parameters were significant mortality predictors in the following order of significance: COVID-19 history, 2-years cardiovascular mortality risk score, NLR, TL, CRP, LDH. Using binary logistic regression analysis Summary risk score, a combination of these six parameters revealed as the best predictor of patient's survival in this group of parameters (log rank 25.4, p < 0.001). CONCLUSION Compared to the general population, the mortality rate among HD patients persists at a higher level despite advancements in HD technology and patient care. The situation has been exacerbated by COVID-19, by significant increase in mortality rate among these patients.
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Grants
- 451-03-47/2023 01/ 200161 Ministry of Education, Science, and Technological Development, Republic of Serbia, through Grant Agreement with the University of Belgrade-Faculty of Pharmacy
- 451-03-47/2023 01/ 200161 Ministry of Education, Science, and Technological Development, Republic of Serbia, through Grant Agreement with the University of Belgrade-Faculty of Pharmacy
- 451-03-47/2023 01/ 200161 Ministry of Education, Science, and Technological Development, Republic of Serbia, through Grant Agreement with the University of Belgrade-Faculty of Pharmacy
- 451-03-47/2023 01/ 200161 Ministry of Education, Science, and Technological Development, Republic of Serbia, through Grant Agreement with the University of Belgrade-Faculty of Pharmacy
- 451-03-47/2023 01/ 200161 Ministry of Education, Science, and Technological Development, Republic of Serbia, through Grant Agreement with the University of Belgrade-Faculty of Pharmacy
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Affiliation(s)
- Tamara Milosevic
- Laboratory Diagnostics Service, Zvezdara Clinical Hospital Center, Dimitrija Tucovica 161, Belgrade, 11120, Serbia.
- Department of Hematology and Cytological Diagnostics of Fluids Laboratory Diagnostics Service Zvezdara Clinical Hospital Center, Dimitrija Tucovica 161, Belgrade, 11120, Serbia.
| | - Radomir Naumovic
- Clinical Department of Nephrology and Metabolic Disorders with Dialysis "Prof. Dr. Vasilije Jovanovic", Zvezdara Clinical Hospital Center, Dimitrija Tucovica 161, Belgrade, 11120, Serbia
- Faculty of Medicine, University of Belgrade, dr Subotica 8, Belgrade, 11000, Serbia
| | - Miron Sopic
- Faculty of Pharmacy, Department for Medical Biochemistry, University of Belgrade, Vojvode Stepe 450, Belgrade, 11221, Serbia
| | - Jelena Vekic
- Faculty of Pharmacy, Department for Medical Biochemistry, University of Belgrade, Vojvode Stepe 450, Belgrade, 11221, Serbia
| | - Azra Guzonjic
- Faculty of Pharmacy, Department for Medical Biochemistry, University of Belgrade, Vojvode Stepe 450, Belgrade, 11221, Serbia
| | - Snezana Pesic
- Clinical Department of Nephrology and Metabolic Disorders with Dialysis "Prof. Dr. Vasilije Jovanovic", Zvezdara Clinical Hospital Center, Dimitrija Tucovica 161, Belgrade, 11120, Serbia
| | - Milica Miljkovic-Trailovic
- Faculty of Pharmacy, Department for Medical Biochemistry, University of Belgrade, Vojvode Stepe 450, Belgrade, 11221, Serbia
| | - Jelena Kotur-Stevuljevic
- Faculty of Pharmacy, Department for Medical Biochemistry, University of Belgrade, Vojvode Stepe 450, Belgrade, 11221, Serbia
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Tian D, Xu Y, Wang Y, Zhu X, Huang C, Liu M, Li P, Li X. Causal factors of cardiovascular disease in end-stage renal disease with maintenance hemodialysis: a longitudinal and Mendelian randomization study. Front Cardiovasc Med 2024; 11:1306159. [PMID: 39091361 PMCID: PMC11291196 DOI: 10.3389/fcvm.2024.1306159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Accepted: 07/08/2024] [Indexed: 08/04/2024] Open
Abstract
Background The risk factors of cardiovascular disease (CVD) in end-stage renal disease (ESRD) with hemodialysis remain not fully understood. In this study, we developed and validated a clinical-longitudinal model for predicting CVD in patients with hemodialysis, and employed Mendelian randomization to evaluate the causal 6study included 468 hemodialysis patients, and biochemical parameters were evaluated every three months. A generalized linear mixed (GLM) predictive model was applied to longitudinal clinical data. Calibration curves and area under the receiver operating characteristic curves (AUCs) were used to evaluate the performance of the model. Kaplan-Meier curves were applied to verify the effect of selected risk factors on the probability of CVD. Genome-wide association study (GWAS) data for CVD (n = 218,792,101,866 cases), end-stage renal disease (ESRD, n = 16,405, 326 cases), diabetes (n = 202,046, 9,889 cases), creatinine (n = 7,810), and uric acid (UA, n = 109,029) were obtained from the large-open GWAS project. The inverse-variance weighted MR was used as the main analysis to estimate the causal associations, and several sensitivity analyses were performed to assess pleiotropy and exclude variants with potential pleiotropic effects. Results The AUCs of the GLM model was 0.93 (with accuracy rates of 93.9% and 93.1% for the training set and validation set, sensitivity of 0.95 and 0.94, specificity of 0.87 and 0.86). The final clinical-longitudinal model consisted of 5 risk factors, including age, diabetes, ipth, creatinine, and UA. Furthermore, the predicted CVD response also allowed for significant (p < 0.05) discrimination between the Kaplan-Meier curves of each age, diabetes, ipth, and creatinine subclassification. MR analysis indicated that diabetes had a causal role in risk of CVD (β = 0.088, p < 0.0001) and ESRD (β = 0.26, p = 0.007). In turn, ESRD was found to have a causal role in risk of diabetes (β = 0.027, p = 0.013). Additionally, creatinine exhibited a causal role in the risk of ESRD (β = 4.42, p = 0.01). Conclusions The results showed that old age, diabetes, and low level of ipth, creatinine, and UA were important risk factors for CVD in hemodialysis patients, and diabetes played an important bridging role in the link between ESRD and CVD.
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Affiliation(s)
- Dandan Tian
- Department of Hypertension, Henan Provincial People’s Hospital & Zhengzhou University People’s Hospital, Zhengzhou, China
| | - You Xu
- Department of Clinical Laboratory, The Third Affifiliated Hospital, Southern Medical University, Guangzhou, China
| | - Ying Wang
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Xirui Zhu
- Department of Medical Imaging, Henan Provincial People’s Hospital & Zhengzhou University People’s Hospital, Zhengzhou, China
| | - Chun Huang
- Department of Medical Imaging, Henan Provincial People’s Hospital & Zhengzhou University People’s Hospital, Zhengzhou, China
| | - Min Liu
- Department of Hypertension, Henan Provincial People’s Hospital & Zhengzhou University People’s Hospital, Zhengzhou, China
| | - Panlong Li
- Department of Medical Imaging, Henan Provincial People’s Hospital & Zhengzhou University People’s Hospital, Zhengzhou, China
- The School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, China
| | - Xiangyong Li
- Department of Infectious Disease, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
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Cai G, Ying J, Pan M, Lang X, Yu W, Zhang Q. Development of a risk prediction nomogram for sarcopenia in hemodialysis patients. BMC Nephrol 2022; 23:319. [PMID: 36138351 PMCID: PMC9502581 DOI: 10.1186/s12882-022-02942-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Accepted: 09/14/2022] [Indexed: 12/02/2022] Open
Abstract
Background Sarcopenia is associated with various adverse outcomes in hemodialysis patients. However, current tools for assessing and diagnosing sarcopenia have limited applicability. In this study, we aimed to develop a simple and reliable nomogram to predict the risk of sarcopenia in hemodialysis patients that could assist physicians identify high-risk patients early. Methods A total of 615 patients undergoing hemodialysis at the First Affiliated Hospital College of Medicine Zhejiang University between March to June 2021 were included. They were randomly divided into either the development cohort (n = 369) or the validation cohort (n = 246). Multivariable logistic regression analysis was used to screen statistically significant variables for constructing the risk prediction nomogram for Sarcopenia. The line plots were drawn to evaluate the effectiveness of the nomogram in three aspects, namely differentiation, calibration, and clinical net benefit, and were further validated by the Bootstrap method. Results The study finally included five clinical factors to construct the nomogram, including age, C-reactive protein, serum phosphorus, body mass index, and mid-upper arm muscle circumference, and constructed a nomogram. The area under the ROC curve of the line chart model was 0.869, with a sensitivity and specificity of 77% sensitivity and 83%, the Youden index was 0.60, and the internal verification C-statistic was 0.783. Conclusions This study developed and validated a nomogram model to predict the risk of sarcopenia in hemodialysis patients, which can be used for early identification and timely intervention in high-risk groups.
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Affiliation(s)
- Genlian Cai
- Kidney Disease Center, The First Affiliated Hospital, Zhejiang University School of Medicine, #1367 Wenyixi Road, Hangzhou, 311121, China
| | - Jinping Ying
- Kidney Disease Center, The First Affiliated Hospital, Zhejiang University School of Medicine, #1367 Wenyixi Road, Hangzhou, 311121, China.
| | - Mengyan Pan
- Kidney Disease Center, The First Affiliated Hospital, Zhejiang University School of Medicine, #1367 Wenyixi Road, Hangzhou, 311121, China
| | - Xiabing Lang
- Kidney Disease Center, The First Affiliated Hospital, Zhejiang University School of Medicine, #1367 Wenyixi Road, Hangzhou, 311121, China
| | - Weiping Yu
- Kidney Disease Center, The First Affiliated Hospital, Zhejiang University School of Medicine, #1367 Wenyixi Road, Hangzhou, 311121, China
| | - Qinqin Zhang
- Kidney Disease Center, The First Affiliated Hospital, Zhejiang University School of Medicine, #1367 Wenyixi Road, Hangzhou, 311121, China
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Li G, Jiang L, Li J, Shen H, Jiang S, Ouyang H, Song K. Development and validation of a nomogram for predicting the 6-months survival rate of patients undergoing incident hemodialysis in China. BMC Nephrol 2022; 23:234. [PMID: 35778681 PMCID: PMC9248113 DOI: 10.1186/s12882-022-02864-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 06/07/2022] [Indexed: 11/12/2022] Open
Abstract
Background The all-cause mortality of patients undergoing hemodialysis (HD) is higher than in the general population. The first 6 months after dialysis are important for new patients. The aim of this study was to develop and validate a nomogram for predicting the 6-month survival rate of HD patients. Methods A prediction model was constructed using a training cohort of 679 HD patients. Multivariate Cox regression analyses were performed to identify predictive factors. The identified factors were used to establish a nomogram. The performance of the nomogram was assessed using the C-index and calibration plots. The nomogram was validated by performing discrimination and calibration tests on an additional cohort of 173 HD patients. Results During a follow-up period of six months, 47 and 16 deaths occurred in the training cohort and validation cohort, respectively, representing a mortality rate of 7.3% and 9.2%, respectively. The nomogram comprised five commonly available predictors: age, temporary dialysis catheter, intradialytic hypotension, use of ACEi or ARB, and use of loop diuretics. The nomogram showed good discrimination in the training cohort [C-index 0.775(0.693–0.857)] and validation cohort [C-index 0.758(0.677–0.836)], as well as good calibration, indicating that the performance of the nomogram was good. The total score point was then divided into two risk classifications: low risk (0–90 points) and high risk (≥ 91 points). Further analysis showed that all-cause mortality was significantly different between the high-risk group and the low-risk group. Conclusions The constructed nomogram accurately predicted the 6-month survival rate of HD patients, and thus it can be used in clinical decision-making.
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Affiliation(s)
- Guode Li
- Department of Cardiology, Maoming People's Hospital, Maoming, Guangdong, China
| | - Linsen Jiang
- Department of Nephrology, The Second Affiliated Hospital of Soochow University, 1055San-Xiang Road, Suzhou, 215004, Jiangsu Province, China
| | - Jiangpeng Li
- Department of Nephrology, The Second Affiliated Hospital of Soochow University, 1055San-Xiang Road, Suzhou, 215004, Jiangsu Province, China
| | - Huaying Shen
- Department of Nephrology, The Second Affiliated Hospital of Soochow University, 1055San-Xiang Road, Suzhou, 215004, Jiangsu Province, China
| | - Shan Jiang
- Department of Nephrology, The Second Affiliated Hospital of Soochow University, 1055San-Xiang Road, Suzhou, 215004, Jiangsu Province, China.
| | - Han Ouyang
- Department of Nephrology, The Second Affiliated Hospital of Soochow University, 1055San-Xiang Road, Suzhou, 215004, Jiangsu Province, China.
| | - Kai Song
- Department of Nephrology, The Second Affiliated Hospital of Soochow University, 1055San-Xiang Road, Suzhou, 215004, Jiangsu Province, China.
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Li N, Zhou G, Zheng Y, Zhou E, He W, Sun W, Zhang L. Development and validation of a novel nomogram to predict overall survival of patients with moderate to severe chronic kidney disease. Ren Fail 2022; 44:241-249. [PMID: 35166166 PMCID: PMC8856074 DOI: 10.1080/0886022x.2022.2032744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
Introduction The risk of death significantly increased from stage 3 chronic kidney disease (CKD) onward. We aimed to construct a novel nomogram to predict the overall survival (OS) of patients afflicted with CKD from stage 3–5. Methods A total of 882 patients with stage 3–5 CKD were enrolled from the NHANES 2001–2004 survey. Data sets from the 2003–2004 survey population were used to develop a nomogram that would predict the risk of OS. The 2001–2002 survey population was used to validate the nomogram. Least absolute shrinkage and selection operator (Lasso) regression was conducted to screen the significant predictors relative to all-cause death. The multivariate Cox regression based on the screened factors was applied to effectively construct the nomogram. The performance of the nomogram was evaluated according to the C-index, the area under the receiver operating characteristic curve (AUC), and the calibration curve with 1000 bootstraps resample. Kaplan–Meier’s curves were used for testing the discrimination of the prediction model. Results Five variables (age, urinary albumin-to-creatinine ratio (UACR), potassium, cystatin C (Cys C), and homocysteine) were screened by the Lasso regression. The nomogram was constructed using these factors, as well as the CKD stage. The included factors (age, CKD stage, UACR, potassium, Cys C, and homocysteine) were all significantly related to the death of CKD patients, according to the multivariate Cox regression analysis. The internal validation showed that this nomogram demonstrates good discrimination and calibration (adjusted C-index: 0.70; AUC of 3-, 5-, and 10-year OS were 0.75, 0.78, and 0.77, respectively). External validation also demonstrated exceedingly similar results (C-index: 0.72, 95% CI: 0.69–0.76; AUC of 3-, 5-, and 10-year OS were 0.76, 0.79, and 0.80, respectively). Conclusions This study effectively constructed a novel nomogram that incorporates CKD stage, age, UACR, potassium, Cys C, and homocysteine, which can be conveniently used to facilitate the individualized prediction of survival probability in patients with stage 3–5 CKD. It displays valuable potential for clinical application.
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Affiliation(s)
- Ning Li
- Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, PR China
| | - Guowei Zhou
- Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, PR China
| | - Yawei Zheng
- Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, PR China
| | - Enchao Zhou
- Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, PR China
| | - Weiming He
- Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, PR China
| | - Wei Sun
- Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, PR China
| | - Lu Zhang
- Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, PR China
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