Establishment of a Nomogram Model for Predicting Cardiovascular and Cerebrovascular Events in Diabetic Nephropathy Patients Receiving Maintenance Hemodialysis

Abstract

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.

Risk prediction models for cardiovascular events in hemodialysis patients: A systematic review

“…After reviewing the titles and abstracts, 3224 articles were excluded, leaving 86 articles to be read in full text. Ultimately, nine articles [14][15][16][17][18][19][20][21][22] containing 12 models were included (Figure 1). indicates not mentioned.…”

“…Three prospective cohort studies 14,17,19 and six retrospective cohort studies 15,16,18,[20][21][22] were included in the nine articles. The total sample size comprised 16,529 patients, with 3651 patients experiencing an outcome event.…”

“…The nine included papers reported 12 prediction models, Cox regression was used in six papers 14,[16][17][18][19]22 to develop the models, while logistic regression was employed in three papers. 15,20,21 For model validation, four papers 15,18-20 conducted internal validation exclusively, one paper 16 focused solely on external validation, one paper 14 employed a combination of internal and external validation, and three papers 17,21,22 did not include any validation. The AUC of the included models ranged from 0.70 to 0.88.…”

“…The 12 models have predictors between 2 and 25, with 19 predictors appearing in more than two models (Figure 2). These predictors can mulas, and two studies 18,21 presented models using a nomogram (Table 3).…”

“…The PROBAST inventory evaluation revealed that all but one 14 of the nine included studies had a high risk of overall bias. The high risk of bias was mainly concentrated in the area of data analysis, particularly in the following five areas: (1) The presence of nonlinear relationships between continuous variables during the transformation process was not tested in five studies 15-17,19,20 ; (2) All participants were not included in the analysis in six studies 15,16,18,[20][21][22] ;…”