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Browsing by Author "Type 1 Diabetes in Acute Pancreatitis Consortium (T1DAPC)"
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Item Design and Rationale for the Use of Magnetic Resonance Imaging Biomarkers to Predict Diabetes After Acute Pancreatitis in the Diabetes RElated to Acute Pancreatitis and Its Mechanisms Study: From the Type 1 Diabetes in Acute Pancreatitis Consortium(Wolters Kluwer, 2022) Tirkes, Temel; Chinchilli, Vernon M.; Bagci, Ulas; Parker, Jason G.; Zhao, Xuandong; Dasyam, Anil K.; Feranec, Nicholas; Grajo, Joseph R.; Shah, Zarine K.; Poullos, Peter D.; Spilseth, Benjamin; Zaheer, Atif; Xie, Karen L.; Wachsman, Ashley M.; Campbell-Thompson, Martha; Conwell, Darwin L.; Fogel, Evan L.; Forsmark, Christopher E.; Hart, Phil A.; Pandol, Stephen J.; Park, Walter G.; Pratley, Richard E.; Yazici, Cemal; Laughlin, Maren R.; Andersen, Dana K.; Serrano, Jose; Bellin, Melena D.; Yadav, Dhiraj; Type 1 Diabetes in Acute Pancreatitis Consortium (T1DAPC); Radiology and Imaging Sciences, School of MedicineThis core component of the Diabetes RElated to Acute pancreatitis and its Mechanisms (DREAM) study will examine the hypothesis that advanced magnetic resonance imaging (MRI) techniques can reflect underlying pathophysiologic changes and provide imaging biomarkers that predict diabetes mellitus (DM) following acute pancreatitis (AP). A subset of participants in the DREAM study will enroll and undergo serial MRI examinations using a specific research protocol. We aim to differentiate at-risk individuals from those who remain euglycemic by identifying parenchymal features following AP. Performing longitudinal MRI will enable us to observe and understand the natural history of post-AP DM. We will compare MRI parameters obtained by interrogating tissue properties in euglycemic, prediabetic and incident diabetes subjects and correlate them with metabolic, genetic, and immunological phenotypes. Differentiating imaging parameters will be combined to develop a quantitative composite risk score. This composite risk score will potentially have the ability to monitor the risk of DM in clinical practice or trials. We will use artificial intelligence, specifically deep learning, algorithms to optimize the predictive ability of MRI. In addition to the research MRI, the DREAM study will also correlate clinical computerized tomography and MRI scans with DM development.Item Rationale and Design for the Diabetes RElated to Acute Pancreatitis and Its Mechanisms (DREAM) Study: A Prospective Cohort Study From the Type 1 Diabetes in Acute Pancreatitis Consortium (T1DAPC)(Wolters Kluwer, 2022) Hart, Phil A.; Papachristou, Georgios I.; Park, Walter G.; Dyer, Anne-Marie; Chinchilli, Vernon M.; Afghani, Elham; Akshintala, Venkata S.; Andersen, Dana K.; Buxbaum, James L.; Conwell, Darwin L.; Dungan, Kathleen M.; Easler, Jeffrey J.; Fogel, Evan L.; Greenbaum, Carla J.; Kalyani, Rita R.; Korc, Murray; Kozarek, Richard; Laughlin, Maren R.; Lee, Peter J.; Maranki, Jennifer L.; Pandol, Stephen J.; Evans Phillips, Anna; Serrano, Jose; Singh, Vikesh K.; Speake, Cate; Tirkes, Temel; Toledo, Frederico G. S.; Trikudanathan, Guru; Vege, Santhi Swaroop; Wang, Ming; Yazici, Cemal; Zaheer, Atif; Forsmark, Christopher E.; Bellin, Melena D.; Yadav, Dhiraj; Type 1 Diabetes in Acute Pancreatitis Consortium (T1DAPC); Medicine, School of MedicineAcute pancreatitis (AP) is a disease characterized by an acute inflammatory phase followed by a convalescent phase. Diabetes mellitus (DM) was historically felt to be a transient phenomenon related to acute inflammation; however, it is increasingly recognized as an important late and chronic complication. There are several challenges that have prevented precisely determining the incidence rate of DM after AP and understanding the underlying mechanisms. The DREAM (Diabetes RElated to Acute Pancreatitis and its Mechanisms) Study is a prospective cohort study designed to address these and other knowledge gaps to provide the evidence needed to screen for, prevent, and treat DM after AP. In the following article, we summarize literature regarding the epidemiology of DM after AP and provide the rationale and an overview of the DREAM study.Item Standard Operating Procedures for Biospecimen Collection, Processing, and Storage: From the Type 1 Diabetes in Acute Pancreatitis Consortium(Wolters Kluwer, 2022) Wasserfall, Clive; Dyer, Anne-Marie; Speake, Cate; Andersen, Dana K.; Baab, Kendall Thomas; Bellin, Melena D.; Broach, James R.; Campbell-Thompson, Martha; Chinchilli, Vernon M.; Lee, Peter J.; Park, Walter G.; Pratley, Richard E.; Saloman, Jami L.; Sims, Emily K.; Tang, Gong; Yadav, Dhiraj; Yazici, Cemal; Conwell, Darwin L.; Type 1 Diabetes in Acute Pancreatitis Consortium (T1DAPC); Pediatrics, School of MedicineDifferences in methods for biospecimen collection, processing, and storage can yield considerable variability and error. Therefore, best practices for standard operating procedures are critical for successful discovery, development, and validation of disease biomarkers. Here, we describe standard operating procedures developed for biospecimen collection during the DREAM (Diabetes RElated to Acute pancreatitis and its Mechanisms) Study within the Type 1 Diabetes in Acute Pancreatitis Consortium (T1DAPC). Notably these protocols were developed using an integrative process based on prior consortium experience and with input from working groups with expertise in immunology, pancreatitis and diabetes. Publication and adoption consistent biospecimen protocols will inform future studies and allow for better comparisons across different metabolic research efforts.