Cao Wei, Zou Jing, Gao Ming, Huang Jianv, Li Yangyang, Li Na, Qian Li, Zhang Ying, Ji Minjun, Liu Yu
Department of Endocrinology, Sir Run Run Hospital, Nanjing Medical University, Nanjing, PR China.
Department of Pathogen Biology, Jiangsu Province Key Laboratory of Modern Pathogen Biology, Center for global health, Nanjing Medical University, Nanjing, PR China..
J Diabetes Complications. 2024 Oct;38(10):108831. doi: 10.1016/j.jdiacomp.2024.108831. Epub 2024 Aug 6.
To compare the time in range (TIR) obtained from self-monitoring of blood glucose (SMBG) with that obtained from continuous glucose monitoring (CGM), and explore the relationship of TIR with microalbuminuria outcome, HOMA-IR and HOMA-β test.
We recruited 400 patients with type 2 diabetes to carry out blood glucose monitoring by both SMBG and CGM for 3 consecutive days. TIR, TAR, TBR and other blood glucose variation indices were calculated respectively through the glucose data achieved from SMBG and CGM. The HOMA-IR and HOMA-β test was evaluated by an oral glucose tolerance test. Urinary microalbumin-to-creatinine ratio completed in the laboratory.
The median (25 %, 75 % quartile) of TIR and TIR were 74.94(44.90, 88.04) and 70.83(46.88, 87.50) respectively, and there was no significant difference, p = 0.489; For every 1 % increase in TIR, the risk of microalbuminuria decreased by 1.6 % (95%CI:0.973, 0.995, p = 0.006) and for every 1 % increase in TIR, the risk of microalbuminuria decreased by 1.3 % (95%CI:0.975, 0.999, p = 0.033). Stepwise multiple linear regression analysis showed an independent positive correlation between TIR (including TIR and TIR) and LnDI30 and LnDI120 levels (p = 0.000).
The TIR calculated by SMBG was highly consistent with that reported by CGM and was significantly associated with the risk of microalbuminuria and the HOMA-β. Higher TIR quartiles were associated with lower incidence of microalbuminuria as well as higher lever of HOMA-β. For patients with limited CGM application, SMBG-derived TIR may be an alternative to CGM-derived TIR, to assess blood glucose control.
比较自我血糖监测（SMBG）和持续葡萄糖监测（CGM）获得的血糖达标时间（TIR），并探讨TIR与微量白蛋白尿结局、稳态模型评估胰岛素抵抗（HOMA-IR）及稳态模型评估β细胞功能（HOMA-β）检测之间的关系。
招募400例2型糖尿病患者，采用SMBG和CGM连续3天进行血糖监测。分别通过SMBG和CGM获得的血糖数据计算TIR、血糖高于目标范围时间（TAR）、血糖低于目标范围时间（TBR）及其他血糖变异指标。通过口服葡萄糖耐量试验评估HOMA-IR和HOMA-β检测。在实验室完成尿微量白蛋白与肌酐比值检测。
SMBG和CGM计算的TIR中位数（第25%，第75%四分位数）分别为74.94（44.90，88.04）和70.83（46.88，87.50），差异无统计学意义，p = 0.489；TIR每增加1%，微量白蛋白尿风险降低1.6%（95%置信区间：0.973，0.995，p = 0.006），TIR每增加1%，微量白蛋白尿风险降低1.3%（95%置信区间：0.975，0.999，p = 0.033）。逐步多元线性回归分析显示TIR（包括SMBG和CGM计算的TIR）与日间血糖平均绝对差（LnDI30）及日内血糖平均绝对差（LnDI120）水平呈独立正相关（p = 0.000）。
SMBG计算的TIR与CGM报告的结果高度一致，且与微量白蛋白尿风险及HOMA-β显著相关。TIR四分位数越高，微量白蛋白尿发生率越低，HOMA-β水平越高。对于CGM应用受限的患者，SMBG计算的TIR可替代CGM计算的TIR用于评估血糖控制情况。
