Medicine and Health Sciences Commons^™

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

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 …

Long-Term Excess Risk Of Stroke In People With Type 2 Diabetes In Sweden According To Blood Pressure Level: A Population-Based Case-Control Study., C Hedén Ståhl, M Lind, A-M Svensson, M Kosiborod, S Gudbjörnsdottir, A Pivodic, Mark A. Clements, A Rosengren

Manuscripts, Articles, Book Chapters and Other Papers

AIMS: To estimate the risk of stroke in people with Type 2 diabetes with different blood pressure levels compared with the risk in the general population in Sweden.

METHODS: This prospective case-control study included 408 076 people with Type 2 diabetes, aged ≥ 18 years, and free of prior stroke, registered in the Swedish National Diabetes Register 1998-2011. Age- and sex-matched control subjects (n = 1 913 507) without stroke from the general population were included. Stroke diagnoses were retrieved using International Classification of Disease codes from the Swedish patient and death registers. Cox hazard ratios and 95% confidence intervals …

Predictors Of Loss To Follow-Up Among Children With Type 2 Diabetes., Ashley Shoemaker, Peiyao Cheng, Robin L. Gal, Craig Kollman, William V. Tamborlane, Georgeanna J. Klingensmith, Mark A. Clements, Tamara S. Hannon, Rubina Heptulla, Joane Less, Jamie Wood, Pediatric Diabetes Consortium

Manuscripts, Articles, Book Chapters and Other Papers

BACKGROUND/AIMS: Youth with type 2 diabetes (T2D) have poor compliance with medical care. This study aimed to determine which demographic and clinical factors differ between youth with T2D who receive care in a pediatric diabetes center versus youth lost to follow-up for >18 months.

METHODS: Data were analyzed from 496 subjects in the Pe-diatric Diabetes Consortium registry. Enrollment variables were selected a priori and analyzed with univariable and multivariable logistic regression models.

RESULTS: After a median of 1.3 years from enrollment, 55% of patients were lost to follow-up. The final model included age, race/ethnicity, parent education, and estimated distance to …