| Objective In this study,patients with type 2 diabetes mellitus（T2DM）were used as the research objects,time in range（TIR）and other relevant blood glucose indicators of diabetic patients were calculated by self-monitoring data of blood glucose,and whether TIR was correlated with diabetic kidney disease（DKD）was analyzed,while exploring the influencing factors of DKD.Methods A total of 221 patients with type 2 diabetes who were admitted to the Special Needs Internal Medicine Department of Lanzhou University Second Hospital from October 2019 to December 2021 were selected as the research subjects.Baseline clinical data were collected:age,gender,duration of diabetes,body mass index（BMI）,systolic blood pressure（SBP）,diastolic blood pressure（DBP）,glycated hemoglobin（HbA1c）,biochemical indicators,24 h urinary protein（UTP）,urinary albumin/creatinine ratio（UACR）,diabetic retinopathy,diabetic peripheral neuropathy,etc.The 7-point fingertip blood glucose monitoring data of the patients within 2 months before admission（monitoring 1 day per month）and 3 consecutive days after admission were collected,and the mean blood glucose（MBG）,standard deviation of blood glucose（SDBG）,glucose variability（GV）,largest amplitude of glycemic excursion（LAGE）,TIR,Time above range（TAR）and Time below range（TBR）.According to the results of the random urine albumin/creatinine ratio detected on the day of admission,the patients were divided into:normal albuminuria group（97 cases）,microalbuminuria group（72 cases）and macroalbuminuria group（52 cases）.The characteristics of the above three groups of clinical data were compared;Spearman correlation analysis was performed on the clinical indicators of T2DM related to UACR,and then multiple linear regression analysis was performed on the significant variables in the correlation analysis;According to the UACR results,they were divided into:normal albuminuria group and diabetic kidney disease group.The DKD group included microalbuminuria group and macroalbuminuria group.According to the TIR level,they were divided into TIR≤40%（29 cases）,41-70%（114 cases）,TIR≥70%（78 cases）.Binary Logistic regression analysis was performed between TIR and diabetic kidney disease to analyze the changing trend of the risk of DKD in three different TIR grade groups;Spearman correlation was used to analyze the correlation between TIR and HbA1c.Finally,binary logistic regression analysis was performed on the risk factors that may affect the occurrence of DKD.SPSS 25.0 statistical software was used for statistical analysis of the above data,and P<0.05 indicated that the difference was statistically significant.Results（1）Basic information:A total of 221 patients were enrolled,including 97 patients with urinary albumin normal diabetes,72 patients with microalbuminuria diabetes and 52 patients with macroalbuminuria diabetes.Normal albuminuria group（97 cases）:mean age 55.96±7.22 years old,males accounted for 68.0%（66 cases）,females 32.0%（31 cases）;microalbuminuria group（72 cases）:average age 57.51±7.62years old,males accounted for 70.8%（51 cases）,females accounted for 29.2%（21cases）;macroalbuminuria group（52 cases）:mean age was 58.94±12.63 years old,males accounted for 78.8%（41 cases）,females accounted for 21.2%（11 cases）.（2）Comparison of clinical data among normal albuminuria group, microalbuminuria group and macroalbuminuria group:normal albuminuria group TIR68.01±20.19,TAR 31.78±20.16,TBR 0.21±0.85,microalbuminuria TIR 59.13±19.96,TAR 40.75±19.94,TBR 0.12±0.57,macroalbuminuria group TIR 51.26±20.75,TAR48.57±20.86,TBR 0.16±0.88.The levels of systolic blood pressure（SBP）,serum creatinine（SCr）,triglycerides（TG）,24h urine protein quantification（UTP）,estimated glomerular filtration rate（eGFR）,MBG,SDBG,LAGE,TIR,and TAR between the three groups were statistically significant（P<0.05）.（3）There were significant differences in TIR and TAR among the three groups （P<0.05）.There were significant differences in MBG and SDBG between urinary albumin normal group and microalbuminuria group,urinary albumin normal group and macroalbuminuria group（P<0.05）,but no difference between microalbuminuria group and macroalbuminuria group statistical difference.There was a significant difference in LAGE between urinary albumin normal group and the macroalbuminuria group（P<0.05）,but there was no statistical difference between the urinary albumin normal group and the microalbuminuria group,the microalbuminuria group and the macroalbuminuria group learning differences.（4）The correlation analysis between UACR and various evaluation parameters showed that:in all patients,UACR was associated with disease duration,SBP,TG,UTP,MBG,SDBG,LAGE,TAR（rs=0.156,0.229,0.239,0.682,0.342,0.244,0.183,0.332,P<0.05）was positively correlated,and negatively correlated with eGFR and TIR（rs=-0.217,-0.331,P<0.05）.（5）Multiple linear regression indicated that TG（β=0.190,P<0.05）,UTP （β=0.438,P<0.05）,eGFR（β=-1.398,P<0.05）were the influencing factors of UACR,among which TG and UTP had positive effects factor.（6）The changing trend of DKD occurrence risk grouped by different TIR grades:grouped according to TIR≤40%（29 cases）,41-70%（114 cases）,TIR≥70%（78cases）,and carried out binary TIR and DKD Logistic regression analysis,adjusted for confounding factors（sex,age,course of disease,smoking,BMI,SBP,blood lipids,BUN,SCr,HbA1c,LAGE）,found that with the increase of TIR level,the risk of DKD decreased（trend P<0.05）.Compared with the TIR≥70%group,the risk of DKD increased by 2.869 times（OR=2.869,P=0.043）,2.529 times（OR=2.529,P=0.011）.（7）The correlation analysis between TIR and HbA1c showed that:TIR was significantly negatively correlated with HbA1c（rs=-0.414,P<0.05）.（8）Binary Logistic regression analysis showed that SBP（OR=1.041,P<0.05）, TG（OR=1.682,P<0.05）and TIR（OR=0.975,P<0.05）were risk factors for diabetic kidney disease.Conclusion（1）TIR in patients with T2DM correlates with the severity of proteinuria.（2）Poor glycemic control is a risk factor for diabetic kidney disease,and the risk of proteinuria in T2DM patients tends to decrease with increasing TIR. |
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