Paula K. Roberson
High Impact
Professor
faculty
Department Chairs, College of Medicine
58 h-index
143 pubs
15,681 cited
Research Areas
Biography and Research Information
OverviewAI-generated summary
Paula K. Roberson's research focuses on several key areas within health sciences, including maternal and perinatal health, cardiovascular function, and health disparities. She has investigated the relationship between maternal smoking and congenital heart defects as part of the National Birth Defects Prevention Study. Her work also extends to understanding the impact of external factors on medical education and professional development, such as the influence of COVID-19 on the dermatology match process.
Roberson's research group also examines clinical interventions and patient outcomes. This includes studies on the efficacy of fibrinolytic therapy for parapneumonic effusion and the stratification of genetic variants associated with Brugada syndrome using automated patch clamp data. Furthermore, her work addresses the social determinants of health and their effect on post-discharge mortality for veterans, as well as assessing the quality of life for adolescents and caregivers in relation to mental health during the COVID-19 pandemic. Her scholarship metrics include an h-index of 58, 147 total publications, and over 15,600 citations, designating her as a highly cited researcher. She collaborates with several researchers at the University of Arkansas for Medical Sciences, including M. Hameed, Charles A. James, Mary B. Moore, and Amy M. Scurlock.
Metrics
- h-index: 58
- Publications: 143
- Citations: 15,681
Selected Publications
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Gastrostomy tube check radiographs: performance of an alternative diagnostic exam (2025)
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Nationwide survey of benefits provided to radiology residents in the United States (2025)
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G-tube contrast check: Transition from fluoroscopy to abdominal radiographs (2024)
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The influence of social determinants of health on <scp>post‐discharge</scp> mortality of veterans who received care in a transitional care unit (2023)
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Efficacy of standardizing fibrinolytic therapy for parapneumonic effusion (2022)
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Maternal Smoking and Congenital Heart Defects, National Birth Defects Prevention Study, 1997-2011 (2021)
Grants & Funding
- Center for Childhood Obesity Research NIH/NIGMS Co-Investigator
- Molecular and Cellular Mechanisms of Osteoporosis NIH Co-Investigator
- Regulatory Ubiquitination in Immune senescence NIH Co-Investigator
- No FP attached UAMS College of Medicine Principal Investigator
- Effect of Tai Chi on Osteoarthritic Knee Pain in Elders with Mild Dementia NIH Co-Investigator
- Ischemic Stroke Treatment with Microbubbles, a Novel Clot Lysis Therapeutic NIH Co-Investigator
- Arkansas Claude Pepper Older Americans Independence Center at UAMS NIH Co-Investigator
- Early Events in Alzheimer Pathogenesis NIH Co-Investigator
Collaboration Network
Top Collaborators
Charles A. James
3 shared publications
In database
- Efficacy of standardizing fibrinolytic therapy for parapneumonic effusion
- G-tube contrast check: Transition from fluoroscopy to abdominal radiographs
- Gastrostomy tube check radiographs: performance of an alternative diagnostic exam
Mary B. Moore
3 shared publications
In database
- Efficacy of standardizing fibrinolytic therapy for parapneumonic effusion
- G-tube contrast check: Transition from fluoroscopy to abdominal radiographs
- Gastrostomy tube check radiographs: performance of an alternative diagnostic exam
Kevin Wong
3 shared publications
- Efficacy of standardizing fibrinolytic therapy for parapneumonic effusion
- G-tube contrast check: Transition from fluoroscopy to abdominal radiographs
- Gastrostomy tube check radiographs: performance of an alternative diagnostic exam
M. Hameed
University of Arkansas for Medical Sciences
3 shared publications
In database
- G-tube contrast check: Transition from fluoroscopy to abdominal radiographs
- Nationwide survey of benefits provided to radiology residents in the United States
- Gastrostomy tube check radiographs: performance of an alternative diagnostic exam
Matthew J. O’Neill
Brigham and Women's Hospital (US)
3 shared publications
- Cohort-scale automated patch clamp data improves variant classification and penetrance stratification for <i>SCN5A</i> -Brugada Syndrome
- Automated patch clamp data improve variant classification and penetrance stratification for <i>SCN5A</i> –Brugada syndrome
- Abstract 4364153: Cohort-scale automated patch clamp data improves variant classification and penetrance stratification for <i>SCN5A</i> -Brugada Syndrome
Jessa L. Aldridge
Vanderbilt University Medical Center (US)
3 shared publications
- Cohort-scale automated patch clamp data improves variant classification and penetrance stratification for <i>SCN5A</i> -Brugada Syndrome
- Automated patch clamp data improve variant classification and penetrance stratification for <i>SCN5A</i> –Brugada syndrome
- Abstract 4364153: Cohort-scale automated patch clamp data improves variant classification and penetrance stratification for <i>SCN5A</i> -Brugada Syndrome
Joseph F. Solus
Vanderbilt University Medical Center (US)
3 shared publications
- Cohort-scale automated patch clamp data improves variant classification and penetrance stratification for <i>SCN5A</i> -Brugada Syndrome
- Automated patch clamp data improve variant classification and penetrance stratification for <i>SCN5A</i> –Brugada syndrome
- Abstract 4364153: Cohort-scale automated patch clamp data improves variant classification and penetrance stratification for <i>SCN5A</i> -Brugada Syndrome
G Harvey
Vanderbilt University Medical Center (US)
3 shared publications
- Cohort-scale automated patch clamp data improves variant classification and penetrance stratification for <i>SCN5A</i> -Brugada Syndrome
- Automated patch clamp data improve variant classification and penetrance stratification for <i>SCN5A</i> –Brugada syndrome
- Abstract 4364153: Cohort-scale automated patch clamp data improves variant classification and penetrance stratification for <i>SCN5A</i> -Brugada Syndrome
Julien Barc
Institut du Thorax (FR)
3 shared publications
- Cohort-scale automated patch clamp data improves variant classification and penetrance stratification for <i>SCN5A</i> -Brugada Syndrome
- Automated patch clamp data improve variant classification and penetrance stratification for <i>SCN5A</i> –Brugada syndrome
- Abstract 4364153: Cohort-scale automated patch clamp data improves variant classification and penetrance stratification for <i>SCN5A</i> -Brugada Syndrome
Connie R. Bezzina
Amsterdam Neuroscience (NL)
3 shared publications
- Cohort-scale automated patch clamp data improves variant classification and penetrance stratification for <i>SCN5A</i> -Brugada Syndrome
- Automated patch clamp data improve variant classification and penetrance stratification for <i>SCN5A</i> –Brugada syndrome
- Abstract 4364153: Cohort-scale automated patch clamp data improves variant classification and penetrance stratification for <i>SCN5A</i> -Brugada Syndrome
Dan M. Roden
Vanderbilt University Medical Center (US)
3 shared publications
- Cohort-scale automated patch clamp data improves variant classification and penetrance stratification for <i>SCN5A</i> -Brugada Syndrome
- Automated patch clamp data improve variant classification and penetrance stratification for <i>SCN5A</i> –Brugada syndrome
- Abstract 4364153: Cohort-scale automated patch clamp data improves variant classification and penetrance stratification for <i>SCN5A</i> -Brugada Syndrome
Roddy Walsh
Genomics England (GB)
3 shared publications
- Cohort-scale automated patch clamp data improves variant classification and penetrance stratification for <i>SCN5A</i> -Brugada Syndrome
- Automated patch clamp data improve variant classification and penetrance stratification for <i>SCN5A</i> –Brugada syndrome
- Abstract 4364153: Cohort-scale automated patch clamp data improves variant classification and penetrance stratification for <i>SCN5A</i> -Brugada Syndrome
Jamie I. Vandenberg
St Vincent's Health (AU)
3 shared publications
- Cohort-scale automated patch clamp data improves variant classification and penetrance stratification for <i>SCN5A</i> -Brugada Syndrome
- Automated patch clamp data improve variant classification and penetrance stratification for <i>SCN5A</i> –Brugada syndrome
- Abstract 4364153: Cohort-scale automated patch clamp data improves variant classification and penetrance stratification for <i>SCN5A</i> -Brugada Syndrome
Andrew M. Glazer
Vanderbilt University Medical Center (US)
3 shared publications
- Cohort-scale automated patch clamp data improves variant classification and penetrance stratification for <i>SCN5A</i> -Brugada Syndrome
- Automated patch clamp data improve variant classification and penetrance stratification for <i>SCN5A</i> –Brugada syndrome
- Abstract 4364153: Cohort-scale automated patch clamp data improves variant classification and penetrance stratification for <i>SCN5A</i> -Brugada Syndrome
Chai‐Ann Ng
UNSW Sydney (AU)
3 shared publications
- Cohort-scale automated patch clamp data improves variant classification and penetrance stratification for <i>SCN5A</i> -Brugada Syndrome
- Automated patch clamp data improve variant classification and penetrance stratification for <i>SCN5A</i> –Brugada syndrome
- Abstract 4364153: Cohort-scale automated patch clamp data improves variant classification and penetrance stratification for <i>SCN5A</i> -Brugada Syndrome
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