---
title: "Predicting Cardiovascular Autonomic Neuropathy in Type 2 Diabetes: Risk Factors and Nomogram Model"
id: "pubmed-42763210"
canonical_url: "https://medichelpline.com/clinical-feed/pubmed-42763210"
content_type: "clinical_feed_article"
specialty: "Pharmacology"
source_name: "PubMed / NCBI"
source_url: "https://pubmed.ncbi.nlm.nih.gov/42763210/"
doi: "10.3760/cma.j.cn112137-20260410-00979"
published_at: "2026-09-22T00:00:00.000Z"
evidence_level: "English Abstract"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Predicting Cardiovascular Autonomic Neuropathy in Type 2 Diabetes: Risk Factors and Nomogram Model
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/pubmed-42763210
- **Specialty:** [Pharmacology](https://medichelpline.com/clinical-feed/pharmacology.md)
- **Primary Source:** PubMed / NCBI
- **Source URL:** [Original Journal Publication](https://pubmed.ncbi.nlm.nih.gov/42763210/)
- **DOI:** [10.3760/cma.j.cn112137-20260410-00979](https://doi.org/10.3760%2Fcma.j.cn112137-20260410-00979)
- **Published At:** 2026-09-22T00:00:00.000Z
- **Evidence Rating:** English Abstract
## Executive GIST (TL;DR)
- This retrospective study analyzed clinical data from 831 hospitalized patients with **type 2 diabetes mellitus (T2DM)** to identify factors associated with **cardiovascular autonomic neuropathy (CAN)** and to construct a predictive model. - Patients were split into a training set (n=581) and validation set (n=250); in the training set 307 were non-CAN and 274 had CAN. - Univariate comparisons showed the CAN group had higher age, longer diabetes duration, higher **HbA1c**, higher 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; they had lower height, weight, bilirubin, transaminases, fasting C‑peptide and fasting insulin (all P<0.05). - Comorbidities and medication use (diabetic nephropathy, diabetic retinopathy, diabetic peripheral neuropathy, hypertension history, cardiovascular disease history, stroke history, antiplatelet and insulin use) were more common in the CAN group (all P<0.05). - LASSO regression selected seven candidate predictors: **diabetic retinopathy (DR)**, age, diabetes duration, **HbA1c**, **NLR**, **PLR**, and SII. Multivariable logistic regression identified six independent influencing factors: **DR**, longer diabetes duration, advancing age, elevated **HbA1c**, increased **NLR**, and elevated **PLR** (reported ORs and 95% CIs included in source). - A **nomogram** built from these six variables achieved an **AUC** of 0.839 (95% CI: 0.807–0.871) in the training set and 0.787 (95% CI: 0.732–0.843) in the validation set, with sensitivities 81.4% and 71.3% and specificities 71.7% and 73.3%, respectively. - Calibration curves and Hosmer-Lemeshow tests indicated good agreement between predicted and observed CAN risk in both sets. Decision curve analysis suggested clinical utility across a wide range of threshold probabilities (training set 1%–88%; validation set 3%–80%). - All authors declared no conflicts of interest. The report does not provide external multicenter validation, prospective testing, or details on CAN diagnostic criteria beyond the source abstract.
## Clinical Analysis & Structured Key Points
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Affiliations Expand ### Affiliations * 1 Department of Endocrinology, Suqian Hospital Affiliated to Xuzhou Medical University, Suqian 223800, China. * 2 Chengde Medical University, Chengde 067050, China. * 3 Department of Endocrinology, Nanjing Drum Tower Hospital, Nanjing 210000, China. * PMID: **42763210** * DOI: [ 10.3760/cma.j.cn112137-20260410-00979 ](https://doi.org/10.3760/cma.j.cn112137-20260410-00979) Item in Clipboard # [Analysis of influencing factors and construction of a predictive model for cardiovascular autonomic neuropathy in type 2 diabetes mellitus] [Article in Chinese] Y L Jiang et al. Zhonghua Yi Xue Za Zhi. 2026. Show details Display options Display options Format Abstract PubMed PMID Zhonghua Yi Xue Za Zhi Actions * [ Search in PubMed ](https://pubmed.ncbi.nlm.nih.gov/?term=%22Zhonghua+Yi+Xue+Za+Zhi%22%5Bjour%5D&sort=date&sort_order=desc) * [ Search in NLM Catalog ](https://www.ncbi.nlm.nih.gov/nlmcatalog?term=%22Zhonghua+Yi+Xue+Za+Zhi%22%5BTitle+Abbreviation%5D) * [ Add to Search ](https://pubmed.ncbi.nlm.nih.gov/42763210/) . 2026 Sep 22;106(35):3754-3763. doi: 10.3760/cma.j.cn112137-20260410-00979. ### Authors [Y L Jiang](https://pubmed.ncbi.nlm.nih.gov/?term=Jiang+YL&cauthor_id=42763210)[ 1 ](https://pubmed.ncbi.nlm.nih.gov/42763210/#short-view-affiliation-1 "Department of Endocrinology, Suqian Hospital Affiliated to Xuzhou Medical University, Suqian 223800, China."), [H M Wu](https://pubmed.ncbi.nlm.nih.gov/?term=Wu+HM&cauthor_id=42763210)[ 1 ](https://pubmed.ncbi.nlm.nih.gov/42763210/#short-view-affiliation-1 "Department of Endocrinology, Suqian Hospital Affiliated to Xuzhou Medical University, Suqian 223800, China."), [G Zhu](https://pubmed.ncbi.nlm.nih.gov/?term=Zhu+G&cauthor_id=42763210)[ 1 ](https://pubmed.ncbi.nlm.nih.gov/42763210/#short-view-affiliation-1 "Department of Endocrinology, Suqian Hospital Affiliated to Xuzhou Medical University, Suqian 223800, China."), [W Wang](https://pubmed.ncbi.nlm.nih.gov/?term=Wang+W&cauthor_id=42763210)[ 1 ](https://pubmed.ncbi.nlm.nih.gov/42763210/#short-view-affiliation-1 "Department of Endocrinology, Suqian Hospital Affiliated to Xuzhou Medical University, Suqian 223800, China."), [L Wu](https://pubmed.ncbi.nlm.nih.gov/?term=Wu+L&cauthor_id=42763210)[ 1 ](https://pubmed.ncbi.nlm.nih.gov/42763210/#short-view-affiliation-1 "Department of Endocrinology, Suqian Hospital Affiliated to Xuzhou Medical University, Suqian 223800, China."), [Y Z Wu](https://pubmed.ncbi.nlm.nih.gov/?term=Wu+YZ&cauthor_id=42763210)[ 2 ](https://pubmed.ncbi.nlm.nih.gov/42763210/#short-view-affiliation-2 "Chengde Medical University, Chengde 067050, China."), [D L Zhu](https://pubmed.ncbi.nlm.nih.gov/?term=Zhu+DL&cauthor_id=42763210)[ 3 ](https://pubmed.ncbi.nlm.nih.gov/42763210/#short-view-affiliation-3 "Department of Endocrinology, Nanjing Drum Tower Hospital, Nanjing 210000, China."), [W M Wang](https://pubmed.ncbi.nlm.nih.gov/?term=Wang+WM&cauthor_id=42763210)[ 3 ](https://pubmed.ncbi.nlm.nih.gov/42763210/#short-view-affiliation-3 "Department of Endocrinology, Nanjing Drum Tower Hospital, Nanjing 210000, China."), [H Zhu](https://pubmed.ncbi.nlm.nih.gov/?term=Zhu+H&cauthor_id=42763210)[ 1 ](https://pubmed.ncbi.nlm.nih.gov/42763210/#short-view-affiliation-1 "Department of Endocrinology, Suqian Hospital Affiliated to Xuzhou Medical University, Suqian 223800, China.") ### Affiliations * 1 Department of Endocrinology, Suqian Hospital Affiliated to Xuzhou Medical University, Suqian 223800, China. * 2 Chengde Medical University, Chengde 067050, China. * 3 Department of Endocrinology, Nanjing Drum Tower Hospital, Nanjing 210000, China. * PMID: **42763210** * DOI: [ 10.3760/cma.j.cn112137-20260410-00979 ](https://doi.org/10.3760/cma.j.cn112137-20260410-00979) Item in Clipboard Full text links Cite Display options Display options Format Abstract PubMed PMID ## Abstract in [ English, ](https://pubmed.ncbi.nlm.nih.gov/42763210/#eng-abstract) [ Chinese ](https://pubmed.ncbi.nlm.nih.gov/42763210/#zho-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 (HbA1c), 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 HbA1c (_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 (_χ_ ²=6.701, _P_ =0.461) and validation set (_χ_ ²=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 HbA1c, 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. **目的：** 探讨2型糖尿病（T2DM）患者发生心血管自主神经病变（CAN）的影响因素，并构建预测模型。 **方法：** 回顾性分析2024年9月至2025年12月于徐州医科大学附属宿迁医院住院治疗的831例T2DM患者的临床资料，采用随机数字表法按照7∶3的比例将患者分为训练集（ _n_ =581）和验证集（ _n_ =250），根据是否发生CAN将训练集患者分为非CAN组（ _n_ =307）和CAN组（ _n_ =274）。比较两组间各项指标差异，采用最小绝对收缩和选择算子（LASSO）回归分析及多因素logistic回归模型分析T2DM患者发生CAN的影响因素，并绘制预测模型列线图。分别采用受试者工作特征曲线下面积（AUC）、校准曲线和决策分析曲线对模型的预测能力、准确性和临床适用性进行评估。 **结果：** 训练集中，CAN组患者年龄、糖尿病病程、糖化血红蛋白（HbA1c）、中性粒细胞计数、血小板计数、中性粒细胞与淋巴细胞比值（NLR）、血小板与淋巴细胞比值（PLR）、单核细胞与淋巴细胞比值、全身免疫炎症指数（SII）、全身炎症反应指数均高于非CAN组，而身高、体重、总胆红素、直接胆红素、丙氨酸转氨酶、天冬氨酸转氨酶、空腹C肽、空腹胰岛素均低于非CAN组（均 _P_ <0.05）。CAN组糖尿病肾脏病、糖尿病视网膜病变（DR）、糖尿病周围神经病变、高血压病史、心血管病史、卒中病史、抗血小板聚集药物使用、胰岛素使用比例均高于非CAN组（均 _P_ <0.05）。LASSO回归分析筛选出7个变量，分别为：DR、年龄、糖尿病病程、HbA1c、NLR、PLR和SII。多因素logistic回归模型分析结果显示，DR（ _OR_ =2.29，95%_CI_ ：1.48~3.56）、糖尿病病程增长（ _OR_ =1.04，95%_CI_ ：1.01~1.08）、年龄增长（ _OR_ =1.06，95%_CI_ ：1.04~1.09）、HbA1c升高（ _OR_ =1.23，95%_CI_ ：1.13~1.36）、NLR升高（ _OR_ =2.23，95%_CI_ ：1.36~3.69）及PLR升高（ _OR_ =1.01，95%_CI_ ：1.00~1.02）是T2DM患者发生CAN的影响因素。应用上述6个变量建立的列线图预测模型在训练集和验证集中预测T2DM患者发生CAN的AUC分别为0.839（95%_CI_ ：0.807~0.871）、0.787（95%_CI_ ：0.732~0.843），灵敏度分别为81.4%和71.3%，特异度分别为71.7%和73.3%。校准曲线显示训练集和验证集T2DM患者发生CAN的预测结果和实际结果一致性均较好，Hosmer-Lemeshow检验结果显示，训练集（ _χ_ ²=6.701， _P_ =0.461）及验证集（ _χ_ ²=12.139， _P_ =0.096）校准度良好。决策分析曲线显示，训练集阈值概率为1%~88%时，验证集阈值概率为3%~80%时，模型具有良好临床适用性。 **结论：** DR、糖尿病病程增长、年龄增长、HbA1c升高、NLR升高、PLR升高是T2DM患者发生CAN的危险因素。基于这些变量构建的列线图预测模型可直观、个体化地评估T2DM患者发生CAN的风险。. [PubMed Disclaimer](https://pubmed.ncbi.nlm.nih.gov/disclaimer/) ## Conflict of interest statement 所有作者声明不存在利益冲突 ## Similar articles * [ [Construction of a regional risk prediction model for diabetic retinopathy in patients with type 2 diabetes]. ](https://pubmed.ncbi.nlm.nih.gov/41644448/) Li JX, Hu JY, Ma Y, Li XX, Ren XC, Feng JR, Wang Q, Zhang WF.Li JX, et al.Zhonghua Yan Ke Za Zhi. 2026 Feb 11;62(2):140-150. doi: 10.3760/cma.j.cn112142-20250828-00356.Zhonghua Yan Ke Za Zhi. 2026.PMID: 41644448Chinese. * [ [Construction and validation of a predictive model for the risk of ARDS in severely burned patients]. ](https://pubmed.ncbi.nlm.nih.gov/42373506/) Yao Y, Liu W, Wang SS, Hua TZ, Zhang GL, Jia HR, Ma SJ, Shen ZA.Yao Y, et al.Zhonghua Shao Shang Yu Chuang Mian Xiu Fu Za Zhi. 2026 Jun 20;42(6):552-561. doi: 10.3760/cma.j.cn501225-20260204-00070.Zhonghua Shao Shang Yu Chuang Mian Xiu Fu Za Zhi. 2026.PMID: 42373506Free PMC article.Chinese. * [ [Influencing factors analysis and prediction model establishment of toe-amputation in patients with diabetic foot]. ](https://pubmed.ncbi.nlm.nih.gov/39757110/) Zhu D, Chen Y, Yang CZ, Zhao JY, Sun YC, Wang LC, Chen HM, Xiao L, Li J.Zhu D, et al.Zhonghua Yi Xue Za Zhi. 2025 Jan 7;105(1):63-71. doi: 10.3760/cma.j.cn112137-20240814-01866.Zhonghua Yi Xue Za Zhi. 2025.PMID: 39757110Chinese. * [ [The effect of preoperative inflammatory indicators on the prognosis of patients with T1a renal cell carcinoma undergoing surgery and the construction of a predictiv
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