Hyperglycemia During Acute Pancreatitis and Progression to Early-Onset Diabetes After Recovery: Preliminary Findings From the Diabetes Related to Acute Pancreatitis and Its Mechanisms (DREAM) Study.

Dungan, Kathleen M; Chinchilli, Vernon M; Pichardo-Lowden, Ariana; Raja-Khan, Nazia; Bellin, Melena D; Yadav, Dhiraj; Hart, Phil A; Basina, Marina et al. · Diabetes Care · 2026

prospective_cohort · Level II

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Abstract

Hyperglycemia during acute pancreatitis (HDAP) likely reflects both stress hormone responses and pancreatic islet injury, distinguishing it from typical stress-induced hyperglycemia. The aim of this study was to determine the prevalence of HDAP and its prognostic significance for early-onset diabetes following acute pancreatitis (AP). Diabetes Related to Acute Pancreatitis and Its Mechanisms (DREAM) is a prospective multicenter study examining the development of diabetes following AP. This analysis included 395 participants without prior diabetes with an AP episode, focusing on their glucose levels during the event. Two definitions of HDAP were examined: peak glucose >140 mg/dL (HDAP140) and >200 mg/dL (HDAP200). Outpatient glycemic status after recovery (median: 111 days post-AP) was evaluated using fasting glucose, oral glucose tolerance test, and HbA1c. HDAP140 and HDAP200 were present in 37.5% and 7.1% of participants, respectively. Age, race, etiology, and AP severity were significant predictors of HDAP140. Among participants with HDAP140, 14.8% developed early-onset diabetes after AP recovery vs. 1.2% in those without (P = 0.0001). In those with HDAP200, 42.9% developed early-onset diabetes vs. 3.5% in those without (P = 0.0001). The absence of HDAP140 and HDAP200 was associated with negative predictive values of 99% and 97%, respectively, for diabetes. HDAP can be common in individuals without diabetes and is associated with early-onset diabetes following AP. Individuals without HDAP have a low risk of diabetes short term, while those with HDAP200 are at high risk. Monitoring glycemia during AP can identify individuals best suited for early targeted postdischarge care.