ObjectiveTo explore the risk factors affecting occurrence of arteriosclerosis obliterans (ASO) for patients with type 2 diabetes mellitus (T2DM) and to develop a nomogram predictive model using these risk factors. MethodsA case-control study was conducted. The patients with T2DM accompanied with ASO and those with T2DM alone, admitted to the First Affiliated Hospital of Xinjiang Medical University from January 2017 to December 2022, were retrospectively collected according to the inclusion and exclusion criteria. The basic characteristics, blood, thyroid hormones, and other relevant indicators of the paitents in two groups were compared. The multivariate logistic regression analysis was used to identify the risk factors for the occurrence of ASO in the patients with T2DM, and then a nomogram predictive model was developed. ResultsThere were 119 patients with T2DM alone and 114 patients with T2DM accompanied with lower extremity ASO in this study. The significant differences were observed between the two groups in terms of smoking history, white blood cell count, neutrophil count, lymphocyte count, platelet count, systemic immune-inflammation index, systemic inflammatory response index (SIRI), high-density lipoprotein cholesterol, apolipoprotein A1 (ApoA1), apolipoprotein α (Apoα), serum cystatin C, free-triiodothyronine (FT3), total triiodothyronine, FT3/total triiodothyronine ratio, fibrinogen (Fib), fibrinogen degradation products, and plasma D-dimer (P<0.05). Further the results of the multivariate logistic regression analysis revealed that the history of smoking, increased Fib level and SIRI value increased the probabilities of ASO occurrence in the patients with T2DM [OR (95%CI)=2.921 (1.023, 4.227), P=0.003; OR (95%CI)=2.641 (1.810, 4.327), P<0.001; OR (95%CI)=1.020 (1.004, 1.044), P=0.018], whereas higher levels of ApoA1 and FT3 were associated with reduced probabilities of ASO occurrence in the patients with T2DM [OR (95%CI)=0.231 (0.054, 0.782), P=0.021; OR (95%CI)=0.503 (0.352, 0.809), P=0.002]. The nomogram predictive model based on these factors demonstrated a good discrimination for predicting the ASO occurrence in the T2DM patients [area under the receiver operating characteristic curve (95%CI)=0.788 (0.730, 0.846)]. The predicted curve closely matched the ideal curve (Hosmer-Lemeshow goodness-of-fit test, χ2=5.952, P=0.653). The clinical decision analysis curve showed that the clinical net benefit of intervention based on the nomogram model was higher within a threshold probability range of 0.18 to 0.80 compared to no intervention or universal intervention. ConclusionsThe analysis results indicate that T2DM patients with a smoking history, elevated Fib level and SIRI value, as well as decreased ApoA1 and FT3 levels should be closely monitored for ASO risk. The nomogram predictive model based on these features has a good discriminatory power for ASO occurrence in T2DM patients, though its value warrants further investigation.