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Establishment of a Nomogram Model for Predicting Cardiovascular and Cerebrovascular Events in Diabetic Nephropathy Patients Receiving Maintenance Hemodialysis
OBJECTIVE: The objective of this study is to explore the risk factors of cardiovascular and cerebrovascular events (CCE) in patients with diabetic nephropathy (DN) receiving maintenance hemodialysis, and to establish a nomogram model on this basis. METHOD: 144 patients with DN receiving maintenance...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9283080/ https://www.ncbi.nlm.nih.gov/pubmed/35847623 http://dx.doi.org/10.1155/2022/2909726 |
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author | Liu, Xiaobing Yan, Caili Niu, Xiuxiu Zeng, Jiechun |
author_facet | Liu, Xiaobing Yan, Caili Niu, Xiuxiu Zeng, Jiechun |
author_sort | Liu, Xiaobing |
collection | PubMed |
description | OBJECTIVE: The objective of this study is to explore the risk factors of cardiovascular and cerebrovascular events (CCE) in patients with diabetic nephropathy (DN) receiving maintenance hemodialysis, and to establish a nomogram model on this basis. METHOD: 144 patients with DN receiving maintenance hemodialysis from February 2020 to February 2021 were selected and followed up for 12 months. They were divided into the occurrence and nonoccurrence groups according to whether CCE occurred. The multivariate logistic regression analysis was used to analyze the influencing factors of CCE, and a predictive nomogram model was established. The receiver operating characteristic (ROC) curve was drawn to evaluate the predictive effect of the nomogram model. The Hosmer-Lemeshow method was used to test the calibration degree. RESULTS: Among the patients, 63 patients (43.75%) encountered CCE. Multivariate logistic regression analysis showed that age >60 years old, history of CCE, dialysis age >12 months, systolic blood pressure >140 mmHg, blood phosphorus level >1.5 mmol/L, triglyceride (TG) level >2.30 mmol/l, adiponectin (ADPN) level <5 mg/L, high-sensitivity-C-reactive protein (hs-CRP) level >10 mg/L, hemoglobin (Hb) level <120 g/L, serum creatinine (SCr) level >720 μmol/L, and albumin (ALB) level <40 g/L were independent risk factors for CCE. Based on the above independent risk factors, a nomogram model of CCE was created. ROC curve analysis showed that the area under curve for predicting CCE was 0.881 (95% CI: 0.833~0.919), indicating that the nomogram model had great predictive effect. The Hosmer-Lemeshow method showed that the calibration curve was in good agreement with the standard curve. CONCLUSION: Age, history of CCE, dialysis age, systolic blood pressure and serum phosphorus, and TG, ADPN, hs-CRP, Hb, SCr, and ALB levels are all influencing factors for the occurrence of CCE in patients with DN receiving maintenance hemodialysis, and the nomogram model has a great predictive effect on CCE. |
format | Online Article Text |
id | pubmed-9283080 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-92830802022-07-15 Establishment of a Nomogram Model for Predicting Cardiovascular and Cerebrovascular Events in Diabetic Nephropathy Patients Receiving Maintenance Hemodialysis Liu, Xiaobing Yan, Caili Niu, Xiuxiu Zeng, Jiechun Appl Bionics Biomech Research Article OBJECTIVE: The objective of this study is to explore the risk factors of cardiovascular and cerebrovascular events (CCE) in patients with diabetic nephropathy (DN) receiving maintenance hemodialysis, and to establish a nomogram model on this basis. METHOD: 144 patients with DN receiving maintenance hemodialysis from February 2020 to February 2021 were selected and followed up for 12 months. They were divided into the occurrence and nonoccurrence groups according to whether CCE occurred. The multivariate logistic regression analysis was used to analyze the influencing factors of CCE, and a predictive nomogram model was established. The receiver operating characteristic (ROC) curve was drawn to evaluate the predictive effect of the nomogram model. The Hosmer-Lemeshow method was used to test the calibration degree. RESULTS: Among the patients, 63 patients (43.75%) encountered CCE. Multivariate logistic regression analysis showed that age >60 years old, history of CCE, dialysis age >12 months, systolic blood pressure >140 mmHg, blood phosphorus level >1.5 mmol/L, triglyceride (TG) level >2.30 mmol/l, adiponectin (ADPN) level <5 mg/L, high-sensitivity-C-reactive protein (hs-CRP) level >10 mg/L, hemoglobin (Hb) level <120 g/L, serum creatinine (SCr) level >720 μmol/L, and albumin (ALB) level <40 g/L were independent risk factors for CCE. Based on the above independent risk factors, a nomogram model of CCE was created. ROC curve analysis showed that the area under curve for predicting CCE was 0.881 (95% CI: 0.833~0.919), indicating that the nomogram model had great predictive effect. The Hosmer-Lemeshow method showed that the calibration curve was in good agreement with the standard curve. CONCLUSION: Age, history of CCE, dialysis age, systolic blood pressure and serum phosphorus, and TG, ADPN, hs-CRP, Hb, SCr, and ALB levels are all influencing factors for the occurrence of CCE in patients with DN receiving maintenance hemodialysis, and the nomogram model has a great predictive effect on CCE. Hindawi 2022-07-07 /pmc/articles/PMC9283080/ /pubmed/35847623 http://dx.doi.org/10.1155/2022/2909726 Text en Copyright © 2022 Xiaobing Liu et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Liu, Xiaobing Yan, Caili Niu, Xiuxiu Zeng, Jiechun Establishment of a Nomogram Model for Predicting Cardiovascular and Cerebrovascular Events in Diabetic Nephropathy Patients Receiving Maintenance Hemodialysis |
title | Establishment of a Nomogram Model for Predicting Cardiovascular and Cerebrovascular Events in Diabetic Nephropathy Patients Receiving Maintenance Hemodialysis |
title_full | Establishment of a Nomogram Model for Predicting Cardiovascular and Cerebrovascular Events in Diabetic Nephropathy Patients Receiving Maintenance Hemodialysis |
title_fullStr | Establishment of a Nomogram Model for Predicting Cardiovascular and Cerebrovascular Events in Diabetic Nephropathy Patients Receiving Maintenance Hemodialysis |
title_full_unstemmed | Establishment of a Nomogram Model for Predicting Cardiovascular and Cerebrovascular Events in Diabetic Nephropathy Patients Receiving Maintenance Hemodialysis |
title_short | Establishment of a Nomogram Model for Predicting Cardiovascular and Cerebrovascular Events in Diabetic Nephropathy Patients Receiving Maintenance Hemodialysis |
title_sort | establishment of a nomogram model for predicting cardiovascular and cerebrovascular events in diabetic nephropathy patients receiving maintenance hemodialysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9283080/ https://www.ncbi.nlm.nih.gov/pubmed/35847623 http://dx.doi.org/10.1155/2022/2909726 |
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