| Objective To explore the correlation between the parameters of ultramicrovascular imaging (SMI) and neuroelectrophysiological parameters of type 2 diabetes mellitus (T2DM), and to analyze the diagnostic value of ultramicrovascular imaging parameters in peripheral neuropathy (DPN). Methods A total of 143 T2DM patients admitted to the hospital from January 2021 to June 2023 were included in the T2DM group. In the same period, 40 healthy subjects were included in the control group. All patients underwent SMI and neuroelectrophysiological examinations. Spearman and Pearson methods were used to analyze the correlation between SMI parameters [blood flow grading and vascular index (VI)] and neuroelectrophysiological parameters [motor conduction velocity (MCV) and sensory conduction velocity (SCV)] in T2DM patients. The clinical data of the patients were collected, and the influencing factors of DPN in T2DM were analyzed by multivariate logistic regression model. Receiver operating characteristic (ROC) curve was used to analyze the diagnostic value of ultramicro angiography parameters in T2DM-DPN. Results There was significant difference in blood flow classification between DPN group and non-DPN group (P<0.05). The proportion of grade 0 in T2DM group was higher than that in control group, and the proportion of grade 3 was lower than that in control group (P<0.05). The VI values of the first dorsal metatarsal artery (DMA) and the first dorsal toe artery in T2DM group were lower than those in control group (P<0.05). The levels of MCV and SCV in T2DM group were lower than those in control group (P<0.05). Sperman and Pearson analysis showed that blood flow classification, DMA and VI values were positively correlated with MCV and SCV (P<0.05). Among the 143 T2DM patients, 98 (68.53%) had DPN and 45 (31.47%) had no DPN. The difference in blood flow classification between DPN group and non-DPN group was statistically significant (P<0.05), the proportion of grade 0 in DPN group was higher than that in non-DPN group, the proportion of grade 2 was lower than that in non-DPN group (P<0.05), and the DMA and first toe dorsal artery VI values in DPN group were lower than those in non-DPN group (P<0.05). The disease course and HbAlc level in DPN group were higher than those in non-DPN group (P<0.05). Logistic regression analysis showed that high level of HbAlc, and blood flow grade 0-1 were risk factors for DPN in T2DM patients, and high level of DMA and VI were protective factors for DPN in T2DM patients (P<0.05, OR>1). ROC analysis results showed: The AUC (95%CI) values for T2DM diagnosed by blood flow grading, DMA and VI alone and combined were 0.718 (0.637~0.791), 0.721 (0.639~0.793), 0.701 (0.619~0.775) and 0.887 (0.823~0.934), respectively. The diagnostic efficiency of the three combined tests was higher than that of each single test (Z=3.445, 3.363, 3.222, P<0.05). Conclusion There is a significant correlation between ultramicrovascular imaging parameters and neuroelectrophysiological parameters in T2DM patients. Among them, blood flow grading, DMA and VI can be used for the diagnosis of T2DM-DPN, and the combination of these three parameters has high diagnostic value for T2DM-DPN. |