OBJECTIVE The current standard for hospital glucose management is point-of-care (POC) testing. We conducted a randomized controlled trial of real-time continuous glucose monitoring (RT-CGM) compared with POC in a non–intensive care unit (ICU) hospital setting. RESEARCH DESIGN AND METHODS A total of 110 adults with type 2 diabetes on a non-ICU floor received RT-CGM with Dexcom G6 versus usual care (UC). RT-CGM data were wirelessly transmitted from the bedside. Hospital telemetry monitored RT-CGM data and notified bedside nursing of glucose alerts and trends. Standardized protocols were used for interventions. RESULTS The RT-CGM group demonstrated significantly lower mean glucose (M∆ = −18.5 mg/dL) and percentage of time in hyperglycemia >250 mg/dL (−11.41%) and higher time in range 70–250 mg/dL (+11.26%) compared with UC ( P values <0.05). Percentage of time in hypoglycemia was very low. CONCLUSIONS RT-CGM can be used successfully in community-based hospital non-ICU settings to improve glucose management. Continuously streaming glucose readings may truly be the fifth vital sign.

Alcohol use disorder (AUD) and anxiety disorders are frequently comorbid and share mechanisms that could be therapeutic targets. To facilitate mechanistic studies, we adapted an inhibitory avoidance-based “2-hit” rat model of posttraumatic stress disorder (PTSD) and identified predictors and biomarkers of comorbid alcohol (ethanol)/PTSD-like symptoms in these animals. Stressed Wistar rats received a single footshock on two occasions. The first footshock occurred when rats crossed into the dark chamber of a shuttle box. Forty-eight hours later, rats received the second footshock in a familiar (FAM) or novel context (NOV). Rats then received 4 weeks of two-bottle choice (2BC) ethanol access. During subsequent abstinence, PTSD-like behavior responses, GABAergic synaptic transmission in the central amygdala (CeA), and circulating cytokine levels were measured. FAM and NOV stress more effectively increased 2BC drinking in males and females, respectively. Stressed male rats, especially drinking-Vulnerable individuals (≥0.8g/kg average 2-hr ethanol intake with >50% ethanol preference), showed higher fear overgeneralization in novel contexts, increased GABAergic transmission in the CeA, and a profile of increased G-CSF, GM-CSF, IL-13, IL-6, IL-17a, leptin and IL-4 that discriminated between stress context (NOV>FAM>Control). However, drinking-resilient males showed the highest G-CSF, IL-13, and leptin levels. Stressed females showed increased acoustic startle and decreased sleep maintenance, indicative of hyperarousal, with increased CeA GABAergic transmission in NOV females. This paradigm promotes key features of PTSD, including hyperarousal, fear generalization, avoidance, and sleep disturbance, with comorbid ethanol intake, in a sex-specific fashion that approximates clinical comorbidities better than existing models, and identifies increased CeA GABAergic signaling and a distinct pro-hematopoietic, proinflammatory, and pro-atopic cytokine profile that may aid in treatment.

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Aim: This study investigates the association between ABO blood phenotype and COVID-19 severity, measured by intensive care unit admission, need for intubation, hospitalization length and death. It further explores clinical predictors of COVID-19 severity within a primarily Hispanic demographic in San Diego County. Materials & methods: We retrospectively reviewed 942 total patients, 473 with available blood type, hospitalized at five Scripps Health hospitals with COVID-19. Results: No significant association was found between ABO phenotype and COVID-19 severity on multivariate analysis, while a diagnosis of anemia and male sex was associated with all severity outcomes on exploratory analysis. Conclusion: Our results provide relevant clinical correlates of COVID-19 severity and help better elucidate the association between ABO phenotype and COVID-19.

Continuous Glucose Monitors (CGM) automatically capture interstitial glucose levels every 5 minutes, 24 hours/day, allowing users to view their glucose levels in real-time and make informed decisions about how to manage diet, exercise, and medications. While CGMs are a central component in the glucose management of type 1 diabetes and insulin-dependent type 2 diabetes, less is known about the potential value of CGMs for diabetes prevention. The original Diabetes Prevention Program (DPP) demonstrated that 5-7% weight loss - an outcome reliant upon healthful eating and exercise - was more effective than medication in preventing or delaying the onset of T2D; however, subsequent DPP translations have not consistently achieved the same weight loss outcomes. CGM may represent a way to reinforce and incentivize hard-to-make health behavior changes in real-time that are crucial to the more distal (and often elusive) weight loss outcome. This small (n=7) feasibility pilot examined the preliminary effectiveness and acceptability of integrating CGM in a DPP at Scripps Health, a large, non-profit, private insurance-based health system in San Diego, CA. Following a brief introduction to the CGM and target glucose ranges, DPP participants self-inserted and wore the CGM for 2 weeks. Mean time-in-range (70-140 mg/dL) improved from 70.4% to 76.4%, and time &gt; 140 mg/dL decreased from 29.4% to 23.1% during this period. Individual change in time-in-range ranged from -9.7% to + 38.8% (M ∆ = +6.0%). Participants reported high satisfaction with the CGM, but expressed a desire for more education on blood glucose management. Given these findings, a longer-term, randomized controlled trial is planned to investigate whether a CGM-enhanced DPP leads to greater weight loss than DPP alone. This research will also further our understanding of the potential benefit of improved glycemic control for diabetes prevention even among the subset of cases who do not ultimately achieve the targeted weight loss goal. Disclosure A.L. Fortmann: None. A. Bastian: None. S.R.S. Bagsic: None. I. Loupasi: None. K. Luu: None. A.R. Hottinger: None. K.A. Barry: None. M. Ruiz: None. C. Walker: None. A. Philis-Tsimikas: Advisory Panel; Self; Lilly Diabetes, Medtronic, Novo Nordisk A/S, Sanofi. Employee; Spouse/Partner; Ionis Pharmaceuticals, Inc. Research Support; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Dexcom, Inc., Lilly Diabetes, Medtronic, Novo Nordisk A/S, Sanofi. Funding Confidence Foundation; Dexcom, Inc.

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