Decreasing complexity of glucose time series derived from continuous glucose monitoring is correlated with deteriorating glucose regulation

The complexity of glucose time series is associated with short- and long-term mortality in critically ill adults: a multi-center, prospective, observational study

BACKGROUND

The wealth of data taken from continuous glucose monitoring (CGM) remains to be fully used. We aimed to evaluate the relationship between a promising new CGM metric, complexity of glucose time series index (CGI), and mortality in critically ill patients.

METHODS

A total of 293 patients admitted to mixed medical/surgical intensive care units from 5 medical centers in Shanghai were prospectively included between May 2020 and November 2021. CGI was assessed using intermittently scanned CGM, with a median monitoring period of 12.0 days. Outcome measures included short- and long-term mortality.

RESULTS

During a median follow-up period of 1.7 years, a total of 139 (47.4%) deaths were identified, of which 73 (24.9%) occurred within the first 30 days after ICU admission, and 103 (35.2%) within 90 days. The multivariable-adjusted HRs for 30-day mortality across ascending tertiles of CGI were 1.00 (reference), 0.68 (95% CI 0.38-1.22) and 0.36 (95% CI 0.19-0.70), respectively. For per 1-SD increase in CGI, the risk of 30-day mortality was decreased by 51% (HR 0.49, 95% CI 0.35-0.69). Further adjustment for HbA1c, mean glucose during hospitalization and glucose variability partially attenuated these associations, although the link between CGI and 30-day mortality remained significant (per 1-SD increase: HR 0.57, 95% CI 0.40-0.83). Similar results were observed when 90-day mortality was considered as the outcome. Furthermore, CGI was also significantly and independently associated with long-term mortality (per 1-SD increase: HR 0.77, 95% CI 0.61-0.97).

CONCLUSIONS

In critically ill patients, CGI is significantly associated with short- and long-term mortality.

Associations between complexity of glucose time series and cognitive function in adults with type 2 diabetes

AIMS

To characterize the comparative contributions of different glycaemic indicators to cognitive dysfunction, and further investigate the associations between the most significant indicator and cognitive function, along with related cerebral alterations.

MATERIALS AND METHODS

We performed a cross-sectional study in 449 subjects with type 2 diabetes who completed continuous glucose monitoring and cognitive assessments. Of these, 139 underwent functional magnetic resonance imaging to evaluate cerebral structure and olfactory neural circuit alterations. Relative weight and Sobol's sensitivity analyses were employed to characterize the comparative contributions of different glycaemic indicators to cognitive dysfunction.

RESULTS

Complexity of glucose time series index (CGI) was found to have a more pronounced association with mild cognitive impairment (MCI) compared to glycated haemoglobin, time in range, and standard deviation. The proportion and multivariable-adjusted odds ratios (ORs) for MCI increased with descending CGI tertile (Tertile 1: reference group [≥4.0]; Tertile 2 [3.6-4.0] OR 1.23, 95% confidence interval [CI] 0.68-2.24; Tertile 3 [<3.6] OR 2.27, 95% CI 1.29-4.00). Decreased CGI was associated with cognitive decline in executive function and attention. Furthermore, individuals with decreased CGI displayed reduced olfactory activation in the left orbitofrontal cortex (OFC) and disrupted functional connectivity between the left OFC and right posterior cingulate gyrus. Mediation analysis demonstrated that the left OFC activation partially mediated the associations between CGI and executive function.

CONCLUSION

Decreased glucose complexity closely relates to cognitive dysfunction and olfactory brain activation abnormalities in diabetes.

Glycemic variability: Measurement, target, impact on complications of diabetes and does it really matter?

Over the past two decades, there has been continuous advancement in the accuracy and complexity of continuous glucose monitoring devices. Continuous glucose monitoring provides valuable insights into blood glucose dynamics, and can record glucose fluctuations accurately and completely. Glycemic variability (GV) is a straightforward measure of the extent to which a patient's blood glucose levels fluctuate between high peaks and low nadirs. Many studies have investigated the relationship between GV and complications, primarily in the context of type 2 diabetes. Nevertheless, the exact contribution of GV to the development of diabetes complications remains unclear. In this literature review, we aimed to summarize the existing evidence regarding the measurement, target level, pathophysiological mechanisms relating GV and tissue damage, and population-based studies of GV and diabetes complications. Additionally, we introduce novel methods for measuring GV, and discuss several unresolved issues of GV. In the future, more longitudinal studies and trials are required to confirm the exact role of GV in the development of diabetes complications.