Relationship between 24-h venous blood glucose variation and mortality among patients with acute respiratory failure

Endothelial Dysfunction and Platelet Hyperactivation in Diabetic Complications Induced by Glycemic Variability

The development and progression of the complications of chronic diabetes mellitus are attributed not only to increased blood glucose levels but also to glycemic variability. Therefore, a deeper understanding of the role of glycemic variability in the development of diabetic complications may provide more insight into targeted clinical treatment strategies in the future. Previously, the mechanisms implicated in glycemic variability-induced diabetic complications have been comprehensively discussed. However, endothelial dysfunction and platelet hyperactivation, which are two newly recognized critical pathogenic factors, have not been fully elucidated yet. In this review, we first evaluate the assessment of glycemic variability and then summarise the roles of endothelial dysfunction and platelet hyperactivation in glycemic variability-induced complications of diabetes, highlighting the molecular mechanisms involved and their interconnections.

Glycemic Variability Is Independently Associated With Poor Prognosis in Five Pediatric ICU Centers in Southwest China

Background

Glucose variability (GV) is a common complication of dysglycemia in critically ill patients. However, there are few studies on the role of GV in the prognosis of pediatric patients, and there is no consensus on the appropriate method for GV measurement. The objective of this study was to determine the “optimal” index of GV in non-diabetic critically ill children in a prospective multicenter cohort observational study. Also, we aimed to confirm the potential association between GV and unfavorable outcomes and whether this association persists after controlling for hypoglycemia or hyperglycemia.

Materials and Methods

Blood glucose values were recorded for the first 72 h and were used to calculate the GV for each participant. Four different metrics [SD, glycemic lability index (GLI), mean absolute glucose (MAG), and absolute change of percentage (ACACP)] were considered and compared to identify the “best” GV index associated with poor prognosis in non-diabetic critically ill children. Among the four metrics, the SD was most commonly used in previous studies, while GLI- and MAG-integrated temporal information, that is the rate and magnitude of change and the time interval between glucose measurements. The fourth metric, the average consecutive ACACP, was introduced in our study, which can be used in real-time clinical decisions. The primary outcome of this study was the 28-day mortality. The receiver operating characteristic (ROC) curve analysis was conducted to compare the predictive power of different metrics of GV for the primary outcome. The GV index with the largest area under ROC curve (AUC) was chosen for subsequent multivariate analyses. Multivariate Cox regression analysis was performed to identify the potential predictors of the outcome. To compare the contribution in 28-day mortality prognosis between glycemic variability and hyper- or hypoglycemia, performance metrics were calculated, which included AUC, net reclassification improvement (NRI), and integrated discrimination improvement (IDI).

Results

Among 780 participants, 12.4% (n = 97) died within 28 days after admission to the pediatric intensive care unit (PICU). Statistically significant differences were found between survivors and non-survivors in terms of four GV metrics (SD, GLI, MAG, and ACACP), in which MAG (AUC: 0.762, 95% CI: 0.705–0.819, p < 0.001) achieved the largest AUC and showed a strong independent association with ICU mortality. Subsequent addition of MAG to the multivariate Cox model for hyperglycemia resulted in further quantitative evolution of the model statistics (AUC = 0.651–0.681, p = 0.001; IDI: 0.017, p = 0.044; NRI: 0.224, p = 0.186). The impact of hyperglycemia (adjusted hazard ratio [aHR]: 1.419, 95% CI: 0.815–2.471, p = 0.216) on outcome was attenuated and no longer statistically relevant after adjustment for MAG (aHR: 2.455, 95% CI: 1.411–4.270, p = 0.001).

Conclusions

GV is strongly associated with poor prognosis independent of mean glucose level, demonstrating more predictive power compared with hypoglycemia and hyperglycemia after adjusting for confounding factors. GV metrics that contain information, such as time and rate of change, are the focus of future research; thus, the MAG may be a good choice. The findings of this study emphasize the crucial role of GVs in children in the PICU. Clinicians should pay more attention to GV for clinical glucose management.

Age moderates the relationships between obesity, glucose variability, and intensive care unit mortality: a retrospective cohort study

BACKGROUND

Although the associations between obesity, glucose variability (GV), and Intensive Care Unit (ICU) mortality have been studied extensively, whether age moderates these associations is not well understood.

MATERIALS AND METHODS

The medical records of 1062 patients, who were admitted into ICU at Sir Run Run Shaw Hospital (Zhejiang, China), were studied. Logistic regression was used to test the associations between obesity, GV, and ICU mortality. Furthermore, the moderation effect of age was tested.

RESULTS

After controlling for covariates, the underweight group had the highest odds of death (OR 2.38, 95% CI 1.43-3.95, p < 0.001) in comparison with the control group (overweight). However, normal weight (OR 1.29, 95% CI 0.88-1.89, p = 0.185) and obese (OR 1.08, 95% CI 0.61-1.90, p = 0.790) groups had similar odds of death, compared to the overweight group. Age significantly moderated the association between obesity and mortality, where being overweight was more advantageous than being normal weight in older adults (B = 0.03, SE = 0.01, OR 1.03, 95% CI 1.001-1.06, p = 0.045). Meanwhile, higher GV predicted greater mortality in adjusted models (OR 1.23, 95% CI 1.06-1.42, p = 0.005). We also found an interaction between age and GV (B = - 0.01, SE = 0.01, OR 0.99, 95% CI 0.98-0.999, p = 0.025), which suggested that the association between GV and mortality becomes weaker with increasing age.

CONCLUSIONS

With increasing age, the association between BMI and mortality becomes stronger and the association between glucose variability and mortality becomes weaker. Future studies should investigate the underlying mechanisms of such phenomenon and the causal relationship between obesity, GV, and ICU mortality.