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Impact Of Diabetes Status And Related Factors On Covid-19-Associated Hospitalization: A Nationwide Retrospective Cohort Study Of 116,370 Adults With Sars-Cov-2 Infection., Erin M. Tallon, Osagie Ebekozien, Janine Sanchez, Vincent S. Staggs, Diana Ferro, Ryan Mcdonough, Carla Demeterco-Berggren, Sarit Polsky, Patricia Gomez, Neha Patel, Priya Prahalad, Ori Odugbesan, Priyanka Mathias, Joyce M. Lee, Chelsey Smith, Chi-Ren Shyu, Mark A. Clements
Impact Of Diabetes Status And Related Factors On Covid-19-Associated Hospitalization: A Nationwide Retrospective Cohort Study Of 116,370 Adults With Sars-Cov-2 Infection., Erin M. Tallon, Osagie Ebekozien, Janine Sanchez, Vincent S. Staggs, Diana Ferro, Ryan Mcdonough, Carla Demeterco-Berggren, Sarit Polsky, Patricia Gomez, Neha Patel, Priya Prahalad, Ori Odugbesan, Priyanka Mathias, Joyce M. Lee, Chelsey Smith, Chi-Ren Shyu, Mark A. Clements
Manuscripts, Articles, Book Chapters and Other Papers
Aims: We examined diabetes status (no diabetes; type 1 diabetes [T1D]; type 2 diabetes [T2D]) and other demographic and clinical factors as correlates of coronavirus disease 2019 (COVID-19)-related hospitalization. Further, we evaluated predictors of COVID-19-related hospitalization in T1D and T2D.
Methods: We analyzed electronic health record data from the de-identified COVID-19 database (December 2019 through mid-September 2020; 87 US health systems). Logistic mixed models were used to examine predictors of hospitalization at index encounters associated with confirmed SARS-CoV-2 infection.
Results: In 116,370 adults ( >=18 years old) with COVID-19 (93,098 no diabetes; 802 T1D; 22,470 T2D), factors that independently increased …
Pediatric Growth Patterns In Youth-Onset Type 2 Diabetes Mellitus: Implications For Physiologically-Based Pharmacokinetic Models., Chelsea M. Hosey, Kelsee Halpin, Valentina Shakhnovich, Chengpeng Bi, Brooke Sweeney, Yun Yan, J Steven Leeder
Pediatric Growth Patterns In Youth-Onset Type 2 Diabetes Mellitus: Implications For Physiologically-Based Pharmacokinetic Models., Chelsea M. Hosey, Kelsee Halpin, Valentina Shakhnovich, Chengpeng Bi, Brooke Sweeney, Yun Yan, J Steven Leeder
Manuscripts, Articles, Book Chapters and Other Papers
An accurate understanding of the changes in height and weight of children with age is critical to the development of models predicting drug concentrations in children (i.e., physiologically-based pharmacokinetic models). However, curves describing the growth of a typical population of children may not accurately characterize growth of children with various conditions, such as obesity. Therefore, to develop height and weight versus age growth curves for youth who were diagnosed with type 2 diabetes, we extracted data from electronic medical records. Robust nonlinear models were parameterized to the equations describing height and weight versus age as defined by the Centers for …