Severe dawn phenomenon predicts long-term risk of all-cause mortality in patients with type 2 diabetes.

AIMS: The dawn phenomenon (DP) is an abnormal early morning blood glucose rise without nocturnal hypoglycaemia, which can be more easily and precisely assessed with continuous glucose monitoring (CGM). This prospective study aimed to explore the association between DP and the risk of all-cause mortality in patients with type 2 diabetes. MATERIALS AND METHODS: A total of 5542 adult inpatients with type 2 diabetes in a single centre were analysed. The magnitude of DP (ΔG) was defined as the increment in the CGM-determined glucose value from nocturnal nadir (after 24:00) to prebreakfast. Participants were stratified into four groups by ΔG: ≤1.11, 1.12-3.33, 3.34-5.55, and >5.55 mmol/L. Cox proportional hazard regression models were used to evaluate the impact of DP on all-cause mortality risk. RESULTS: During a median follow-up of 9.4 years, 1083 deaths were identified. The restricted cubic spline revealed a nonlinear (p for nonlinearity = 0.002) relationship between ΔG and the risk of all-cause mortality. A multivariate-adjusted Cox regression model including glycated haemoglobin A1c (HbA1c) showed that ΔG > 5.55 mmol/L was associated with 30% (95% CI, 1.01-1.66) higher risk of all-cause mortality, as compared with ΔG 1.12-3.33 mmol/L. CONCLUSIONS: Higher ΔG is significantly related to an increased risk of all-cause mortality in type 2 diabetes, suggesting that severe DP should be given more attention as a part of glucose management to reduce the risk of long-term adverse outcomes.

Continuous glucose monitoring profile in COVID-19 patients with and without diabetes receiving methylprednisolone.

PURPOSE: Methylprednisolone is widely used during the COVID-19 epidemic. We aimed to evaluate the glucose profile of COVID-19 patients with and without diabetes receiving methylprednisolone. METHODS: 36 patients with COVID-19 admitted to hospital were included: 17 with and 19 without diabetes. Methylprednisolone 40 mg was administered at about 9:00 a.m. Glucose levels were assessed by blinded intermittently scanned continuous glucose monitoring (isCGM) for an average of 6.8 ± 2.4 days. Excess hyperglycemia was defined as time above range (TAR) > 10.0 mmol/L (TAR>10.0) ≥ 25%, or TAR > 13.9 mmol/L (TAR>13.9) ≥ 10%. RESULTS: Glucose management indicator (GMI) was significantly higher than the admission glycated hemoglobin A1c (HbA1c) level in patients without diabetes [6.7 (6.1-7.0) % vs. 5.9 (5.9-6.1) %, P < 0.001], while no significant difference was found in patients with diabetes [9.0 (7.5-9.5) % vs. 8.9 (7.5-10.2) %, P > 0.05]. The difference between GMI and HbA1c (∆GMI-HbA1c) in patients without diabetes was significantly higher than in patients with diabetes [0.7 (0.2-1.0) % vs. -0.2 (-1.5-0.5) %, P = 0.005]. The circadian patterns of glucose were similar in the two groups. In patients without diabetes, excess hyperglycemia occurred in 31.6% (6/19) of participants, with 31.6% (6/19) having a TAR>10.0 ≥ 25%, while 21.1% (4/19) had a TAR>13.9 ≥ 10%. CONCLUSION: The impact of methylprednisolone on glycemia was more pronounced in COVID-19 patients without diabetes, compared to those with diabetes. A significant burden of methylprednisolone-induced hyperglycemia was observed in patients without diabetes.

Impact of the Complexity of Glucose Time Series on All-Cause Mortality in Patients With Type 2 Diabetes.

CONTEXT: Previous studies suggest that the complexity of glucose time series may serve as a novel marker of glucose homeostasis. OBJECTIVE: We aimed to investigate the relationship between the complexity of glucose time series and all-cause mortality in patients with type 2 diabetes. METHODS: Prospective data of 6000 adult inpatients with type 2 diabetes from a single center were analyzed. The complexity of glucose time series index (CGI) based on continuous glucose monitoring (CGM) was measured at baseline with refined composite multiscale entropy. Participants were stratified by CGI tertiles of: < 2.15, 2.15 to 2.99, and ≥ 3.00. Cox proportional hazards regression models were used to assess the relationship between CGI and all-cause mortality. RESULTS: During a median follow-up of 9.4 years, 1217 deaths were identified. A significant interaction between glycated hemoglobin A1c (HbA1c) and CGI in relation to all-cause mortality was noted (P for interaction = 0.016). The multivariable-adjusted hazard ratios for all-cause mortality at different CGI levels (≥ 3.00 [reference group], 2.15-2.99, and < 2.15) were 1.00, 0.76 (95% CI, 0.52-1.12), and 1.47 (95% CI, 1.03-2.09) in patients with HbA1c < 7.0%, while the association was nonsignificant in those with HbA1c ≥ 7.0%. The restricted cubic spline regression revealed a nonlinear (P for nonlinearity = 0.041) relationship between CGI and all-cause mortality in subjects with HbA1c < 7.0% only. CONCLUSION: Lower CGI is associated with an increased risk of all-cause mortality among patients with type 2 diabetes achieving the HbA1c target. CGI may be a new indicator for the identification of residual risk of death in well-controlled type 2 diabetes.

Time in Range in Relation to All-Cause and Cardiovascular Mortality in Patients With Type 2 Diabetes: A Prospective Cohort Study.

OBJECTIVE: There is growing evidence linking time in range (TIR), an emerging metric for assessing glycemic control, to diabetes-related outcomes. We aimed to investigate the association between TIR and mortality in patients with type 2 diabetes. RESEARCH DESIGN AND METHODS: A total of 6,225 adult patients with type 2 diabetes were included from January 2005 to December 2015 from a single center in Shanghai, China. TIR was measured with continuous glucose monitoring at baseline, and the participants were stratified into four groups by TIR: >85%, 71-85%, 51-70%, and ≤50%. Cox proportional hazards regression models were used to estimate the association between different levels of TIR and the risks of all-cause and cardiovascular disease (CVD) mortality. RESULTS: The mean age of the participants was 61.7 years at baseline. During a median follow-up of 6.9 years, 838 deaths were identified, 287 of which were due to CVD. The multivariable-adjusted hazard ratios associated with different levels of TIR (>85% [reference group], 71-85%, 51-70%, and ≤50%) were 1.00, 1.23 (95% CI 0.98-1.55), 1.30 (95% CI 1.04-1.63), and 1.83 (95% CI 1.48-2.28) for all-cause mortality (P for trend <0.001) and 1.00, 1.35 (95% CI 0.90-2.04), 1.47 (95% CI 0.99-2.19), and 1.85 (95% CI 1.25-2.72) for CVD mortality (P for trend = 0.015), respectively. CONCLUSIONS: The current study indicated an association of lower TIR with an increased risk of all-cause and CVD mortality among patients with type 2 diabetes, supporting the validity of TIR as a surrogate marker of long-term adverse clinical outcomes.

Association of HbA1c With All-cause Mortality Across Varying Degrees of Glycemic Variability in Type 2 Diabetes.

CONTEXT: The interaction of glycated hemoglobin A1c (HbA1c) and glycemic variability in relation to diabetes-related outcomes remains unknown. OBJECTIVE: To evaluate the relationship between HbA1c and all-cause mortality across varying degrees of glycemic variability in patients with type 2 diabetes. DESIGN, SETTING, AND PATIENTS: This was a prospective study conducted in a single referral center. Data of 6090 hospitalized patients with type 2 diabetes was analyzed. Glucose coefficient of variation [coefficient of variation (CV)] was obtained as the measure of glycemic variability by using continuous glucose monitoring for 3 days. Cox proportional hazards regression models were used to estimate hazard ratios and 95% CIs for all-cause mortality. RESULTS: During a median follow-up of 6.8 years, 815 patients died. In patients with the lowest and middle tertiles of glucose CV, HbA1c ≥ 8.0% was associated with 136% (95% CI 1.46-3.81) and 92% (95% CI 1.22-3.03) higher risks of all-cause mortality, respectively, as compared with HbA1c 6.0%-6.9%, after adjusting for confounders. However, a null association of HbA1c with mortality was found in patients with the highest tertile of glucose CV. CONCLUSIONS: HbA1c may not be a robust marker of all-cause mortality in patients with high degree of glycemic variability. New metrics of glycemic control may be needed in these individuals to achieve better diabetes management.