Urinary orosomucoid and retinol binding protein levels as early diagnostic markers for diabetic kidney Disease

There were no significant differences in age and gender among the three groups (P > 0.05). There were no significant differences in DBP, BMI, CHOL, TG, and LDL levels among the three groups (P > 0.05) (Table 1).

Table 1 Comparison of general clinical data among the three groups

There were significant differences in SBP, HbA1c, FBG between the NC and the other two groups (P < 0.05). However, there was no significant difference in the general clinical data between the T2DM and T2DKD groups (P > 0.05). As renal damage increased in patients, urine orosomucoid levels gradually increased as well (P < 0.05) (Table 1).

Urine RBP and MAL levels in the T2DKD group were significantly higher than those in the NC and T2DKD groups (P < 0.001). The eGFR levels in the T2DKD group were significantly lower than those in the NC and T2DM groups (P < 0.001). There were no significant differences in RBP, eGFR, and MAL levels between the NC and T2DM groups (P > 0.05) (Table 2).

Table 2 Comparison of urinary orosomucoid, RBP, MAL, and eGFR levels among the three groups

For the NC group and T2DM group, the dependent variable was whether T2DM had occurred (Yes = 1, No = 0) and the independent variables were the four variables (SBP, HbA1c, FBG, and orosomucoid) with differences between the two groups, as shown in Tables 1 and 2. A binary logistic regression model was established and used to determine the influence of these four variables on T2DM (Table 3), and all were shown to be risk factors (all OR > 1, p < 0.05).

Table 3 Classification of clinical, biochemical parameters and biomarkers (RBP, Orosomucoid) in T2DKD as per micro albumin tertiles

For the T2DM group and T2DKD group, the dependent variable was whether T2DKD had occurred (Yes = 1, No = 0) and the independent variables were the five variables with differences between the two groups, as shown in Tables 1 and 2. A binary logistic regression model was established for analysis (Table 4).

Table 4 Binary logistic regression analysis of the factors associated with Type 2 diabetic kidney disease

Of the five factors that were included in the regression model (p < 0.05), SBP, orosomucoid, RBP, and MAL were all determined to be risk factors (OR > 1), and eGFR was shown to be a protective factor (OR = 0.948 > 1). Correlation analysis showed that in the T2DKD group, the urinary orosomucoid level was significantly positively correlated with RBP (r = 0.489) and MAL (r = 0.513). RBP and MAL were significantly positively correlated with a correlation coefficient of 0.468. eGFR and urine orosomucoid, RBP, and MAL were significantly negatively correlated (r = -0.577, -0.474, and − 0.466, respectively).

ROC curve analysis was used to assess the diagnostic points and diagnostic value of orosomucoid and that of RBP to predict DKD. Figure 1; Table 5 show the areas under the ROC curves for orosomucoid and RBP with the respective standard error values.

Fig. 1figure 1

ROC curve analysis was used to assess the diagnostic points and diagnostic value of orosomucoid and that of RBP to predict DKD.

Table 5 Areas under the two ROC curves for predicting diabetic kidney disease

The diagnostic value of DKD had improved; however, no significance was observed (Z = 0.598, P = 0.550 > 0.05). The diagnostic point of orosomucoid was 22.43, sensitivity was 0.941, specificity was 0.842, and Youden’s index was 0.783. The diagnostic point of RBP was 0.53, sensitivity was 0.942, specificity was 1.000, and Youden’s index was 0.941.

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