With the advances in blood glucose monitoring technologies, a flash glucose monitoring system (FGMS) has recently been used to panoramically observe the blood glucose level in patients with type 2 diabetes mellitus (T2DM). Evaluating the relationship of blood glucose metrics monitored by the FGMS with T2DM complications will facilitate the clinical application of FGMS but relevant studies are rare.

To assess the correlation of time in range (TIR) and other markers with urine albumin-to-creatinine ratio (UACR) in patients with T2DM using a FGMS.

T2DM patients (n=79) using a FGMS were selected from Department of Geriatrics, Peking University People's Hospital from January 2019 to October 2021, including 29 with UACR greater than 30 mg/g (albuminuria group) and 50 with UACR less than 30 mg/g (non-albuminuria group). The clinical characteristics, laboratory test markers, and blood glucose metrics monitored by the FGMS of the two groups were compared. Pearson correlation and Spearman correlation analyses were used to explore the correlation of TIR and time above range (TAR) with glycated hemoglobin (HbA_1c). Pearson correlation, Spearman correlation and partial correlation analyses were used to explore the correlations of FGMS markers with natural logarithm-transformed UACR, respectively. Multivariate Logistic regression analysis was used to explore the factors influencing the development of albuminuria in T2DM. The predictive value of TIR for albuminuria was assessed using the receiver operating characteristic (ROC) curve.

Compared with the non-albuminuria group, albuminuria group had longer duration of T2DM (P<0.05). Moreover, albuminuria group had higher triacylglycerol, HbA_1c, mean blood glucose (MBG), TAR, the standard deviation of mean blood glucose (SDBG), the largest amplitude of glycemic excursions (LAGE), mean amplitude of glycemic excursions (MAGE), and 2 h continuous overlapping net glycemic action (CONGA₂), as well as lower TIR (P<0.05). Pearson correlation and Spearman correlation analyses showed that HbA_1c was negatively correlated with TIR (P<0.001), and was positively correlated with TAR (P<0.001). Pearson correlation, Spearman correlation and partial correlation analyses revealed that the natural logarithm-transformed UACR was negatively correlated with TIR (P<0.001), and was positively correlated with MBG, TAR, SDBG, LAGE, MAGE, and CONGA₂ (P<0.001). Multivariable Logistic regression analysis showed that TIR>70%〔OR=0.038, 95%CI (0.003, 0.467) 〕 was associated with decreased risk of albuminuria in T2DM (P<0.05), while elevated TAR〔OR=1.046, 95%CI (1.000, 1.094) 〕 was associated with increased risk of albuminuria in T2DM (P<0.05). The area under the ROC curve of TIR for predicting the presence of albuminuria in T2DM was 0.784 〔95%CI (0.674, 0.894) 〕 (P=0.003), with a sensitivity of 78%, and a specificity of 83% when the optimal cutoff point was chosen as 69.71%.

The risk of albuminuria decreased with TIR>70% but increased with elevated TAR in T2DM. UACR was closely related with SDBG, LAGE, MAGE, CONGA₂ and other markers reflecting blood glucose fluctuations. Early screening and identifying T2DM patients with a low TIR level, and a high TAR, SDBG, LAGE, MAGE, and CONGA₂ will help to prevent the development of albuminuria.