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

Abstract

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.