ObjectiveTo observe and analyze the correlation between time within target glucose range (TIR) and hemoglobin A1c (HbA1c) and the risk of diabetic retinopathy (DR). MethodsA retrospective clinical study. From March 2020 to August 2021, 91 patients with type 2 diabetes mellitus (T2DM) who were hospitalized in Department of Endocrinology and Metabolic Diseases, Affiliated Hospital of Weifang Medical University, were included in the study. All patients underwent Oburg's no-dilatation ultra-wide-angle laser scan ophthalmoscopy, HbA1c and continuous glucose monitoring (CGM) examinations. According to the examination results and combined with the clinical diagnostic criteria of DR, the patients were divided into non-DR (NDR) group and DR group, with 50 and 41 cases respectively. The retrospective CGM system was used to monitor the subcutaneous interstitial fluid glucose for 7 to 14 consecutive days, and the TIR was calculated. Binary logistic regression was used to analyze the correlation between TIR, HbAlc and DR in patients with T2DM0. At the same time, a new indicator was generated, the predicted probability value (PRE_1), which was generated to represent the combined indicator of TIR and HbA1c in predicting the occurrence of DR. The receiver operating characteristic curve (ROC curve) was used to analyze the value of TIR, HbAlc and PRE_1 in predicting the occurrence of DR. ResultsThe TIR of patients in the NDR group and DR group were (81.58±15.51)% and (67.27±22.09)%, respectively, and HbA1c were (8.03±2.16)% and (9.01±2.01)%, respectively. The differences in TIR and HbA1c between the two groups of patients were statistically significant (t=3.501,－2.208; P=0.001, 0.030). The results of binary logistic regression analysis showed that TIR, HbA1c and DR were significantly correlated (odds ratio=0.960, 1.254; P=0.002, 0.036). ROC curve analysis results showed that the area under the ROC curve (AUC) of TIR, HbA1c and PRE_1 predicting the risk of DR were 0.704, 0.668, and 0.707, respectively [95% confidence interval (CI) 0.597-0.812, P=0.001; 95%CI 0.558-0.778, P=0.006; 95%CI 0.602-0.798, P=0.001]. There was no statistically significant difference between TIR, HbA1c and PRE_1 predicting the AUC of DR risk (P>0.05). The linear equation between HbAlc and TIR was HbAlc (%) = 11.37－0.04×TIR (%). ConclusionsTIR and HbA1c are both related to DR and can predict the risk of DR. The combined use of the two does not improve the predictive value of DR. There is a linear correlation between TIR and HbAlc.
Blood glucose monitoring has become the weakest point in the overall management of diabetes in China. Long-term monitoring of blood glucose levels in diabetic patients has become an important means of controlling the development of diabetes and its complications, so that technological innovations in blood glucose testing methods have far-reaching implications for accurate blood glucose testing. This article discusses the basic principles of minimally invasive and non-invasive blood glucose testing assays, including urine glucose assays, tear assays, methods of extravasation of tissue fluid, and optical detection methods, etc., focuses on the advantages of minimally invasive and non-invasive blood glucose testing methods and the latest relevant results, and summarizes the current problems of various testing methods and prospects for future development trends.
Objective To investigate the accuracy of continuous glucose monitoring (CGM) system in emergency critically ill patients. Methods Critically ill patients admitted to the Intensive Care Unit of Department of Emergency Medicine, West China Hospital of Sichuan University between August 2022 and February 2023 were continuously enrolled. Blood glucose monitoring was performed using CGM system, while blood glucose in the patient’s fingertips was monitored every 4 hours. The correlation and consistency of blood glucose values between CGM system and fingertip glucose detection were compared. Results A total of 52 patients were included, and 1 504 matching blood glucose pairs were formed with fingertip blood glucose values. The overall correlation coefficient was 0.874 (P<0.001), the mean absolute relative difference was 14.50%, and the highest mean absolute relative difference (31.76%) was observed in the hypoglycemic range (<3.9 mmol/L). The percentage of CGM system blood glucose within ±15%, ±20% and ±30% of fingertip blood glucose was 56.65%, 75.56% and 94.75%, respectively. The intra-group correlation coefficient between CGM system blood glucose and fingertip blood glucose was 0.85 on the consistency test, and the Bland-Altman plot showed acceptable clinical accuracy. Conclusions The overall accuracy of the application of CGM system in critically ill patients is reasonable, but the accuracy in the range of low blood glucose values is poor. Whether the auxiliary use of CGM system can improve the blood glucose management of critically ill patients and reduce medical costs needs to be further studied.