Zhonghua Yi Xue Za Zhi. 2026 Sep 22;106(35):3754-3763. doi: 10.3760/cma.j.cn112137-20260410-00979.
ABSTRACT
Objective: To investigate the influencing factors for cardiovascular autonomic neuropathy (CAN) in patients with type 2 diabetes mellitus (T2DM) and to develop a predictive model. Methods: A retrospective analysis was performed on clinical data of 831 patients with T2DM hospitalized in the Suqian Hospital Affiliated to Xuzhou Medical University from September 2024 to December 2025. Patients were divided into a training set (n=581) and a validation set (n=250) at a 7∶3 ratio using a random number table method. According to the presence of CAN, patients in the training set were further classified into the non-CAN group (n=307) and the CAN group (n=274). Compare the differences in various indicators between the two groups. Least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression models were used to analyze influencing factors for CAN in patients with T2DM, and a nomogram prediction model was constructed. The area under the receiver operating characteristic curve (AUC), calibration curve and decision curve analysis were adopted to evaluate the predictive performance, accuracy and clinical applicability of the model. Results: In the training set, patients in the CAN group presented higher age, diabetes duration, glycated hemoglobin (HbA), neutrophil count, platelet count, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio, systemic immune-inflammation index (SII), and systemic inflammatory response index compared with the non-CAN group. By contrast, height, body weight, total bilirubin, direct bilirubin, alanine aminotransferase, aspartate aminotransferase, fasting C-peptide and fasting insulin were lower in the CAN group (all P<0.05). The proportions of diabetic nephropathy, diabetic retinopathy (DR), diabetic peripheral neuropathy, history of hypertension, history of cardiovascular disease, history of stroke, anti-platelet agent use and insulin use were higher in the CAN group than in the non-CAN group (all P<0.05). Seven variables were screened out via LASSO regression analysis, including DR, age, diabetes duration, HbA1c, NLR, PLR and SII. Multivariate logistic regression analysis revealed that DR (OR=2.29, 95%CI: 1.48-3.56), longer diabetes duration (OR=1.04, 95%CI: 1.01-1.08), advancing age (OR=1.06, 95%CI: 1.04-1.09), elevated HbA (OR=1.23, 95%CI: 1.13-1.36), increased NLR (OR=2.23, 95%CI: 1.36-3.69) and elevated PLR (OR=1.01, 95%CI: 1.00-1.02) were influencing factors for CAN in patients with T2DM. The nomogram prediction model constructed with the above 6 variables yielded AUC values of 0.839 (95%CI: 0.807-0.871) and 0.787 (95%CI: 0.732-0.843) for predicting CAN among T2DM patients in the training set and validation set, respectively. The corresponding sensitivity was 81.4% and 71.3%, and the specificity was 71.7% and 73.3%. Calibration curves demonstrated good agreement between predicted and observed CAN outcomes in both the training and validation sets. The Hosmer-Lemeshow test showed satisfactory calibration for the training set (χ²=6.701, P=0.461) and validation set (χ²=12.139, P=0.096). The decision curve analysis demonstrated that the model exhibits favorable clinical applicability when the threshold probability of the training set ranges from 1% to 88%, and that of the validation set ranges from 3% to 80%. Conclusions: DR, longer diabetes duration, advanced age, elevated HbA, increased NLR and elevated PLR are risk factors for CAN in patients with T2DM. The nomogram prediction model established based on these variables can intuitively and individually assess the risk of CAN in patients with T2DM.
PMID:42763210 | DOI:10.3760/cma.j.cn112137-20260410-00979