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.

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Aim. To investigate the clinical features and prognosis in patients of hyperlipidemic acute pancreatitis with or without diabetes. Methods. 157 patients with hypertriglyceridemic pancreatitis (HTGP) were included in this study. Patients with a previous history of diabetes were identified in the group of HTGP with diabetes (HTGPD), while patients without a history of diabetes were identified in the group of HTGP. The clinical characteristics and prognosis data of these patients in the two groups were analyzed. Results. Multivariate Cox regression analysis showed that age, body mass index, glycated serum protein (GSP), and Acute Physiology and Chronic Health Evaluation (APACHE) II score were significantly associated with mortality in patients with HTGP. The mortality was significantly higher in the HTGPD group than in the HTGP group ( p < 0.001 ). Compared to patients of HTGP, those of HTGPD had older age of onset, higher blood glucose levels, and higher GSP levels on admission. Electrocardiograms showed that patients of HTGPD had a significantly higher risk of heart ischemia than those of HTGP ( p < 0.05 ). Patients of HTGPD had higher APACHE II scores than those of HTGP ( p < 0.001 ). Single-factor analysis showed that higher triglyceride levels, GSP, LDL, and previous history of diabetes were associated with HTGP recurrence. Conclusions. Clinicians should be alert to patients of HTGP with diabetes. Diabetes is an important risk factor for HTGP and hyperglycemia may affect the development and prognosis of HTGP.