Nasal Glucagon Reverses Insulin-induced Hypoglycemia With Less Rebound Hyperglycemia: Pooled Analysis of Clinical Trials

Background

Rebound hyperglycemia may occur following glucagon treatment for severe hypoglycemia. We assessed rebound hyperglycemia occurrence after nasal glucagon (NG) or injectable glucagon (IG) administration in patients with type 1 diabetes (T1D) and type 2 diabetes (T2D).

Methods

This was a pooled analysis of 3 multicenter, randomized, open-label studies (NCT03339453, NCT03421379, NCT01994746) in patients ≥18 years with T1D or T2D with induced hypoglycemia. Proportions of patients achieving treatment success [blood glucose (BG) increase to ≥70 mg/dL or increase of ≥20 mg/dL from nadir within 15 and 30 minutes]; BG ≥70 mg/dL within 15 minutes; in-range BG (70-180 mg/dL) 1 to 2 and 1 to 4 hours postdose; and BG >180 mg/dL 1 to 2 and 1 to 4 hours postdose were compared. Incremental area under curve (iAUC) of BG >180 mg/dL and area under curve (AUC) of observed BG values postdose were analyzed. Safety was assessed in all studies.

Results

Higher proportions of patients had in-range BG with NG vs IG (1-2 hours: P = .0047; 1-4 hours: P = .0034). Lower proportions of patients had at least 1 BG value >180 mg/dL with NG vs IG (1-2 hours: P = .0034; 1-4 hours: P = .0068). iAUC and AUC were lower with NG vs IG (P = .025 and P < .0001). As expected, similar proportions of patients receiving NG or IG achieved treatment success at 15 and 30 minutes (97-100%). Most patients had BG ≥70 mg/dL within 15 minutes (93-96%). The safety profile was consistent with previous studies.

Conclusion

This study demonstrated lower rebound hyperglycemia risk after NG treatment compared with IG.

Clinical Trial Registration

NCT03421379, NCT03339453, NCT01994746.

Rebound Hypoglycemia and Hyperglycemia in Type 1 Diabetes

AIMS

The aim was to investigate rebound hypoglycemic and hyperglycemic events, and describe their relation to other glycemic metrics.

METHODS

Data from intermittently scanned continuous glucose monitoring were downloaded for 90 days for 159 persons with type 1 diabetes. A hypoglycemic event was defined as glucose <3.9 mmol/l for at least two 15-minute periods. Rebound hypoglycemia (Rhypo) was a hypoglycemic event preceded by glucose >10.0 mmol/l within 120 minutes and rebound hyperglycemia (Rhyper) was hypoglycemia followed by glucose >10.0 mmol/l within 120 minutes.

RESULTS

A total of 10 977 hypoglycemic events were identified of which 3232 (29%) were Rhypo and 3653 (33%) were Rhyper, corresponding to a median frequency of 10.1, 2.5, and 3.0 events per person/14 days. For 1267 (12%) of the cases, Rhypo and Rhyper coexisted. The mean peak glucose was 13.0 ± 1.6 mmol/l before Rhypo; 12.8 ± 1.1 mmol/l in Rhyper. The frequency of Rhyper was significantly (P < .001) correlated with Rhypo (Spearman's rho 0.84), glucose coefficient of variation (0.78), and time below range (0.69) but not with time above range (0.12, P = .13).

CONCLUSIONS

The strong correlation between Rhyper and Rhypo suggests an individual behavioral characteristic toward intensive correction of glucose excursions.

Mitigation of Rebound Hyperglycemia With Real-Time Continuous Glucose Monitoring Data and Predictive Alerts

BACKGROUND

Excess carbohydrate intake during hypoglycemia can lead to rebound hyperglycemia (RH). We investigated associations between RH and use of real-time continuous glucose monitoring (rtCGM) and an rtCGM system's predictive alert.

METHODS

RH events were series of sensor glucose values (SGVs) >180 mg/dL starting within two hours of an antecedent SGV <70 mg/dL. Events were characterized by their frequency, duration (consecutive SGVs >180 mg/dL × five minutes), and severity (area under the glucose concentration-time curve). To assess the impact of rtCGM, data gathered during the four-week baseline phase (without rtCGM) and four-week follow-up phase (with rtCGM) from 75 participants in the HypoDE clinical trial (NCT02671968) of hypoglycemia-unaware individuals were compared. To assess the impact of predictive alerts, we identified a convenience sample of 24 518 users of an rtCGM system without predictive alerts who transitioned to a system whose predictive alert signals an SGV ≤55 mg/dL within 20 minutes (Dexcom G5 and G6, respectively). RH events from periods of blinded versus unblinded rtCGM wear and from periods of G5 and G6 wear were compared with paired t tests.

RESULTS

Compared to RH events in the HypoDE baseline phase, the mean frequency, duration, and severity of events fell by 14%, 12%, and 23%, respectively, in the follow-up phase (all P < .05). Compared to RH events during G5 use, the mean frequency, duration, and severity of events fell by 7%, 8%, and 13%, respectively, during G6 use (all P < .001).

CONCLUSIONS

Rebound hypreglycemia can be objectively quantified and mitigated with rtCGM and rtCGM-based predictive alerts.