AIM: To investigate the clinical features of acute exacerbation chronic obstructive pulmonary disease (AECOPD) of complicated with type 2 diabetes mellitus (T2DM), and analyze the related clinical features and risk factors. METHODS: This was a single-center cross-sectional study. From March 2020 to January 2023, 479 hospitalized patients with AECOPD in the department of respiratory and critical care medicine, Suining Central Hospital were included. There were 215 patients in AECOPD group and 60 patients in AECOPD with T2DM group. The collected variables included demographic data, complications, blood routine, infection index, random blood glucose, blood gas analysis and lung function. The adoption rate and constituent ratio of the basic description classification data were expressed as mean standard deviation for the normal distribution measurement data and median interquartile range for the skew distribution measurement data. T-test was used for normal distribution and non - parameter test was used for non-normal distribution. The categorical variables were tested by chi-square test. Rank sum test was used for rank variable data. Binary logistic regression model was used to investigate the independent factors associated with T2DM in patients with AECOPD. Finally, the results of logistic regression were verified and visualized by nomogram, validation curve, ROC curve and DCA curve. P<0.05 was a significant statistical difference. RESULTS: Univariate analysis showed that there were significant differences in body mass index (BMI), essential hypertension, coronary heart disease, atrial fibrillation (AF), pulmonary function (GOLD stage), blood neutrophil (NS), blood lymphocyte (LYM), arterial blood gas PaCO2, Alanine transaminase (ALT) and random blood glucose (RBG) between the two groups (P<0.05). The binary logistic regression model (C-index=0.847) was constructed with the above 10 variables, the results showed that BMI (OR=1.309), Af (OR= 8.188), LYM counts (OR=0.474), PaCO2 (OR=1.082) and RBG (OR=1.434) were independently associated with type 2 diabetes in patients with AECOPD (all P>0.05). The results of logistic regression were verified and visualized by Nomogram and its-associated ccurves. The MAE and AUC curves were 0.021 and 0.847 respectively, indicating that the model had good prediction consistency and accuracy. The DCA curve showed that Nomogram's risk threshold ranged from 0.01 to 0.99, suggesting that nomogram's model had better clinical predictive value. CONCLUSION: Our results showed that increased BMI, PaCO2 and random glucose, decreased blood lymphocyte, and atrial fibrillation is an independent clinical feature of AECOPD with T2DM. These results suggest that the immune function of patients with AECOPD and T2DM are more severely impaired and more likely to be accompanied by atrial fibrillation, which is a potential cause of poor prognosis in these patients. Meanwhile, this conclusion needs to be further verified in multicenter study with large sample size.