ArticleAnnals of medicine2026
Risk spectrum of admission HbA1c levels and acute pancreatitis severity: a real-world study revealing younger high-risk populations and nonlinear associations.
Article in Annals of medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectiveAcute pancreatitis (AP) is clinically heterogeneous, and early identification of patients at risk for severe progression remains challenging. Glycated hemoglobin (HbA1c) reflects long-term glycemic exposure, but its prognostic relevance in AP is unclear. This study evaluated the association of admission HbA1c with AP severity and complications.
methodsWe conducted a retrospective study of 324 patients hospitalized with AP at a single tertiary center. Patients were categorized into quartiles by admission HbA1c. Multivariable logistic regression assessed associations between HbA1c quartiles and severe AP or complications. Restricted cubic spline analyses explored nonlinear relationships and potential inflection points. Prespecified subgroup analyses tested robustness.
resultsHigher HbA1c levels were associated with less favorable metabolic profiles and stronger inflammatory responses at presentation. Excess risk was mainly concentrated in the highest HbA1c quartile, which showed the clearest association with severe AP and pancreatitis-related complications. Restricted cubic spline analysis demonstrated a significant nonlinear association between HbA1c and severe AP, with a potential inflection point around 6.25%, above which risk increased more markedly. A similar pattern was observed for pancreatitis-related complications. These associations were generally consistent across prespecified subgroups. However, exploratory models based on baseline admission variables, including HbA1c, showed limited discrimination, with an AUC of 0.573 for severe AP and 0.665 for complications.
conclusionHbA1c may serve as an adjunct marker of metabolic vulnerability rather than a strong standalone predictor. The spline-derived inflection point should be considered exploratory and requires external validation.
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