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Correlation between glycated hemoglobin A1c, urinary microalbumin, urinary creatinine, β2 microglobulin, retinol
Jia-Jia Song1, Xiao-Fang Han2, Jian-Feng Chen2
1Department of Endocrinology, The Second People's Hospital of Hefei, Hefei Hospital Affiliated to Anhui Medical University, Hefei 230011, Anhui Province, China. sjj1832613@126.com.
Background:
Retinopathy is the most common microvascular disease of type 2 diabetes, and seriously threatens the life, health and quality of life of patients. It is worth noting that the development of diabetic retinopathy (DR) can be hidden, with few symptoms. Therefore, the preliminary screening of diabetic patients should identify DR as soon as possible, delay disease progression, and play a vital role in its diagnosis and treatment.
Aim:
To investigate the correlation between glycated hemoglobin A1c (HbA1c), urinary microalbumin (U-mALB), urinary creatinine (U-CR), mALB/U-CR ratio, β2 microglobulin (β2MG), retinol binding protein (RBP) and DR.
Methods:
A total of 180 patients with type 2 diabetes mellitus attending the Second People's Hospital of Hefei from January 2022 to August 2022 were retrospectively enrolled by ophthalmologists. Based on whether they had combined retinopathy and its degree, 68 patients with diabetes mellitus without retinopathy (NDR) were assigned to the NDR group, 54 patients with non-proliferative DR (NPDR) to the NPDR group, and 58 patients with proliferative DR to the PDR group. General data, and HbA1c, mALB, β2MG, RBP, mALB/U-CR and U-CR results were collected from the patients and compared among the groups. Pearson's correlation method was used to analyze the correlation between HbA1c, mALB, β2MG, RBP, mALB/U-CR and U-CR indices, and multiple linear regression was applied to identify the risk factors for DR. Receiver operator characteristic (ROC) curves were also drawn.
Results:
The differences in age, gender, systolic and diastolic blood pressure between the groups were not statistically significantly (P > 0.05), but the difference in disease duration was statistically significant (P < 0.05). The differences in fasting blood glucose, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, total cholesterol, and triglyceride between the groups were not statistically significant (P > 0.05). HbA1c in the PDR group was higher than that in the NPDR and NDR groups (P < 0.05). The levels of mALB, β2MG, RBP, mALB/U-CR and U-CR in the PDR group were higher than those in the NPDR and NDR groups (P < 0.05). Multiple linear regression analysis showed that disease duration, HbA1c, mALB, β2MG, RBP, mALB/U-CR and U-CR were risk factors for the development of DR. The ROC curve showed that the area under the curve (AUC) for the combination of indices (HbA1c + mALB + mALB/U-CR + U-CR + β2MG + RBP) was 0.958, with a sensitivity of 94.83% and specificity of 96.72%, which was higher than the AUC for single index prediction (P < 0.05).
Conclusion:
HbA1c, mALB, mALB/U-CR, U-CR, β2MG and RBP can reflect the development of DR and are risk factors affecting PDR, and the combination of these six indices has predictive value for PDR.
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