Prediction of Pancreatogenic Diabetes After Partial Resection of the Pancreas

The primary aim of the study is to identify clinical, laboratory, imaging, and pathohistological risk factors for the development of pancreatogenic diabetes after partial resection of the pancreas (PRP) and, based on these, to build a predictive model that would enable reliable and accurate identification of patients who will develop pancreatogenic diabetes. A review of the literature shows that there is currently no validated tool available in clinical practice for identifying patients at risk of this type of diabetes after PRP. Etiological differences between type 2 diabetes and pancreatogenic diabetes often lead to late diagnosis, limiting opportunities for timely intervention. The development of a comprehensive predictive model would contribute to a better understanding of the pathophysiology of pancreatogenic diabetes, enable the identification of patients at risk, facilitate tailored clinical monitoring, and allow the implementation of targeted preventive or therapeutic measures in the perioperative period. Based on a review of the literature and clinical observations, the investigators formulated the following hypotheses: H1: Clinical, laboratory, imaging, and pathohistological variables are independently associated with the development of pancreatogenic diabetes after partial pancreatic resection. H2: A predictive model that allows reliable and accurate identification of patients who will develop pancreatogenic diabetes can be build based on the identified variables (H1). H3: A comprehensive predictive model in the perioperative period allows more precise identification of patients who will develop pancreatogenic diabetes, and thus more effective risk stratification compared to the use of individual risk factors (variables). Based on the reviewed literature and our own clinical observations, this constitutes an original contribution to science. The investigators expect that the research will identify key clinical, laboratory, imaging, and pathohistological factors associated with the development of pancreatogenic diabetes after partial pancreatic resection. The development of a clinically useful predictive model that will allow individual risk assessment for the development of pancreatogenic diabetes in patients after partial pancreatic resection is anticipated. A similar comprehensive model has not yet been described in the accessible literature. The research will contribute to a better understanding of metabolic changes and will enable the identification of patients who will develop pancreatogenic diabetes after partial pancreatic resection. The results of the study could provide a basis for improved perioperative monitoring of these patients in the field of pancreatogenic diabetes.