Cardiovascular

[Analysis of influencing factors and construction of a predictive model for cardiovascular autonomic neuropathy in type 2 diabetes mellitus].

TL;DR

DR, longer diabetes duration, advanced age, elevated HbA1c, increased NLR and elevated PLR are risk factors for CAN in patients with T2DM, and a nomogram prediction model based on these variables can intuitively and individually assess the risk of CAN.

Key Findings

CAN patients with T2DM had significantly higher levels of inflammatory and immune markers compared to non-CAN patients.

  • CAN group presented higher neutrophil count, platelet count, NLR, PLR, monocyte-to-lymphocyte ratio, systemic immune-inflammation index (SII), and systemic inflammatory response index compared with the non-CAN group (all P<0.05).
  • CAN group also had higher age, diabetes duration, and HbA1c than the non-CAN group (all P<0.05).
  • 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).
  • Study included 831 T2DM patients; training set had 307 non-CAN and 274 CAN patients.

CAN patients had higher rates of diabetic complications and comorbidities than non-CAN patients.

  • 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 all higher in the CAN group than in the non-CAN group (all P<0.05).
  • These differences were identified in the training set of 581 patients.

LASSO regression identified seven variables associated with CAN in T2DM patients.

  • The seven variables selected were: DR, age, diabetes duration, HbA1c, NLR, PLR, and SII.
  • LASSO regression was applied to the training set of 581 patients to reduce dimensionality prior to multivariate logistic regression.

Multivariate logistic regression identified six independent risk factors for CAN in T2DM patients.

  • DR was an independent risk factor (OR=2.29, 95%CI: 1.48-3.56).
  • Longer diabetes duration (OR=1.04, 95%CI: 1.01-1.08) and advancing age (OR=1.06, 95%CI: 1.04-1.09) were independent risk factors.
  • 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 also independent risk factors.
  • SII was not retained in the final multivariate model despite being selected by LASSO.

The nomogram prediction model demonstrated good discriminative ability in both training and validation sets.

  • AUC was 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.
  • Sensitivity was 81.4% in the training set and 71.3% in the validation set.
  • Specificity was 71.7% in the training set and 73.3% in the validation set.
  • The model was constructed using 6 variables: DR, age, diabetes duration, HbA1c, NLR, and PLR.

Calibration curves demonstrated good agreement between predicted and observed CAN outcomes in both training and validation sets.

  • Hosmer-Lemeshow test showed satisfactory calibration for the training set (χ²=6.701, P=0.461).
  • Hosmer-Lemeshow test also showed satisfactory calibration for the validation set (χ²=12.139, P=0.096).
  • Both P-values exceed 0.05, indicating no significant deviation between predicted and observed outcomes.

Decision curve analysis demonstrated favorable clinical applicability of the nomogram model across a wide range of threshold probabilities.

  • The model exhibits favorable clinical applicability when the threshold probability of the training set ranges from 1% to 88%.
  • For the validation set, favorable clinical applicability was found when threshold probability ranges from 3% to 80%.
  • This indicates the model provides net benefit over a broad range of clinical decision thresholds.

What This Means

This research investigated which factors increase the risk of cardiovascular autonomic neuropathy (CAN) — a serious complication that affects the nerves controlling heart and blood vessel function — in people with type 2 diabetes. The study analyzed clinical data from 831 hospitalized patients and found that those who developed CAN tended to be older, have had diabetes longer, have worse blood sugar control (higher HbA1c), have signs of greater inflammation in the blood (higher NLR and PLR, which are ratios of different immune cells), and were more likely to also have diabetic eye disease (retinopathy). Conversely, CAN patients had lower levels of markers related to liver function, body size, and insulin production. Using statistical methods to identify the strongest predictors, the researchers built a visual scoring tool called a nomogram that combines six factors — diabetic retinopathy, age, diabetes duration, HbA1c, neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) — to estimate an individual patient's risk of having CAN. The model performed well, correctly identifying CAN in about 81% of cases in the development group and 71% in a separate validation group, with AUC values of 0.839 and 0.787 respectively, indicating good overall accuracy. This research suggests that inflammatory markers routinely measured in blood tests — specifically NLR and PLR — may be useful alongside traditional risk factors like age and blood sugar control for identifying type 2 diabetes patients at higher risk of cardiovascular autonomic neuropathy. The presence of other diabetes complications, especially retinopathy, was also strongly associated with CAN risk. Such a predictive tool could help clinicians prioritize monitoring and care for patients most likely to develop this complication.

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Citation

Jiang Y, Wu H, Zhu G, Wang W, Wu L, Wu Y, et al.. (2026). [Analysis of influencing factors and construction of a predictive model for cardiovascular autonomic neuropathy in type 2 diabetes mellitus].. Zhonghua yi xue za zhi. https://doi.org/10.3760/cma.j.cn112137-20260410-00979