Two-week continuous glucose monitoring-derived metrics and degree of hepatic steatosis: a cross-sectional study among Chinese middle-aged and elderly participants.

BACKGROUND: Continuous glucose monitoring (CGM) devices provide detailed information on daily glucose control and glycemic variability. Yet limited population-based studies have explored the association between CGM metrics and fatty liver. We aimed to investigate the associations of CGM metrics with the degree of hepatic steatosis. METHODS: This cross-sectional study included 1180 participants from the Guangzhou Nutrition and Health Study. CGM metrics, covering mean glucose level, glycemic variability, and in-range measures, were separately processed for all-day, nighttime, and daytime periods. Hepatic steatosis degree (healthy: n = 698; mild steatosis: n = 242; moderate/severe steatosis: n = 240) was determined by magnetic resonance imaging proton density fat fraction. Multivariate ordinal logistic regression models were conducted to estimate the associations between CGM metrics and steatosis degree. Machine learning models were employed to evaluate the predictive performance of CGM metrics for steatosis degree. RESULTS: Mean blood glucose, coefficient of variation (CV) of glucose, mean amplitude of glucose excursions (MAGE), and mean of daily differences (MODD) were positively associated with steatosis degree, with corresponding odds ratios (ORs) and 95% confidence intervals (CIs) of 1.35 (1.17, 1.56), 1.21 (1.06, 1.39), 1.37 (1.19, 1.57), and 1.35 (1.17, 1.56) during all-day period. Notably, lower daytime time in range (TIR) and higher nighttime TIR were associated with higher steatosis degree, with ORs (95% CIs) of 0.83 (0.73, 0.95) and 1.16 (1.00, 1.33), respectively. For moderate/severe steatosis (vs. healthy) prediction, the average area under the receiver operating characteristic curves were higher for the nighttime (0.69) and daytime (0.66) metrics than that of all-day metrics (0.63, P < 0.001 for all comparisons). The model combining both nighttime and daytime metrics achieved the highest predictive capacity (0.73), with nighttime MODD emerging as the most important predictor. CONCLUSIONS: Higher CGM-derived mean glucose and glycemic variability were linked with higher steatosis degree. CGM-derived metrics during nighttime and daytime provided distinct and complementary insights into hepatic steatosis.

Glycemic profile and quality of recovery after emergency abdominal surgery-A prospective explorative cohort study.

Associations between degrees of postoperative hyperglycemia and morbidity has previously been established. There may be an association between the glycemic profile and patient-reported recovery, and this may be a target for perioperative quality improvements. We aimed to investigate the association between metrics of the 30-day glycemic profile and patient-reported recovery in nondiabetic patients after major abdominal surgery. In a prospective, explorative cohort study, nondiabetic adult patients undergoing acute, major abdominal surgery were included within 24 h after surgery. Interstitial fluid glucose concentration was measured for 30 consecutive days with a continuous glucose measurement device. The validated questionnaire 'Quality of Recovery-15' was used to assess patient-reported quality of recovery on postoperative days 10, 20, and 30. Follow-up time was divided into five-day postoperative intervals using days 26-30 as a reference. Linear mixed models were applied to investigate temporal changes in mean p-glucose, coefficient of variation, time within 70-140 mg/dl, and time above 200 mg/dl in relation to patient-reported recovery. Twenty-seven patients completed the study per protocol. A hyperglycemic event (>200 mg/dl) occurred in 18 of 27 patients (67%) within the first three postoperative days. Compared to the reference period, the coefficient of variation was significantly increased during all time intervals, indicating prolonged postoperative insulin resistance. During 30 days of follow-up, patient-reported recovery was associated with the coefficient of variation measured for 3 and 5 days before the corresponding recovery score assessment (recovery score estimate -1.52 [p < .001] and -0.92 [p = .006], respectively). We did not find an association between the remaining metrics and patient-reported recovery. Alterations in the glycemic profile are frequent and prolonged during the first postoperative month after major surgery probably due to peripheral insulin resistance. Our findings indicate that high-glycemic variation is associated with poorer patient-reported recovery and might represent a proxy for care improvements in the postoperative period.

Continuous glucose monitoring adds information beyond HbA1c in well-controlled diabetes patients with early cardiovascular autonomic neuropathy.

AIMS: Hyperglycemia as evaluated by HbA1c is a risk factor for the development of cardiovascular autonomic neuropathy (CAN). The aim of the present study was to investigate whether continuous glucose monitoring (CGM) may add information beyond HbA1c in patients with type 2 diabetes and CAN. METHODS: 81 patients with type 2 diabetes (43 men, mean age 58±11year, HbA1c 6.6±0.5%). Patients were tested for CAN using cardiovascular reflex tests (response to standing, deep breathing and Valsalva maneuver) and underwent CGM for three days. CAN was defined as early (one test abnormal), or manifest (two or three tests abnormal). RESULTS: Twenty patients had early CAN and two patients had manifest CAN. Blood pressure, HbA1c, cholesterol levels and smoking habits were comparable in patients with vs. without CAN. Post-breakfast glycemic peak was significantly higher in patients with CAN (peak 207 vs 176mg/dL, P=0.009). Furthermore, the nocturnal glucose drop and dawn glucose was significantly higher in patients with CAN compared with patients without CAN (mean 134 vs. 118mg/dL, P=0.017 and mean 143 vs. 130mg/dL, P=0.045, respectively). Removing the two patients with manifest CAN from the statistical analysis didn't change the results. CONCLUSIONS: These findings emphasize the importance of monitoring glucose patterns over 24-h and not only rely on HbA1c as therapeutic target in patients with type 2 diabetes and CAN.