A prospective neurosurgical registry evaluating the clinical care of traumatic brain injury patients presenting to Mulago National Referral Hospital in Uganda.
BackgroundTraumatic Brain Injury (TBI) is disproportionally concentrated in low- and middle-income countries (LMICs), with the odds of dying from TBI in Uganda more than 4 times higher than in high income countries (HICs). The objectives of this study are to describe the processes of care and determine risk factors predictive of poor outcomes for TBI patients presenting to Mulago National Referral Hospital (MNRH), Kampala, Uganda.
MethodsWe used a prospective neurosurgical registry based on Research Electronic Data Capture (REDCap) to systematically collect variables spanning 8 categories. Univariate and multivariate analysis were conducted to determine significant predictors of mortality.
Results563 TBI patients were enrolled from 1 June- 30 November 2016. 102 patients (18%) received surgery, 29 patients (5.1%) intended for surgery failed to receive it, and 251 patients (45%) received non-operative management. Overall mortality was 9.6%, which ranged from 4.7% for mild and moderate TBI to 55% for severe TBI patients with GCS 3-5. Within each TBI severity category, mortality differed by management pathway. Variables predictive of mortality were TBI severity, more than one intracranial bleed, failure to receive surgery, high dependency unit admission, ventilator support outside of surgery, and hospital arrival delayed by more than 4 hours.
ConclusionsThe overall mortality rate of 9.6% in Uganda for TBI is high, and likely underestimates the true TBI mortality. Furthermore, the wide-ranging mortality (3-82%), high ICU fatality, and negative impact of care delays suggest shortcomings with the current triaging practices. Lack of surgical intervention when needed was highly predictive of mortality in TBI patients. Further research into the determinants of surgical interventions, quality of step-up care, and prolonged care delays are needed to better understand the complex interplay of variables that affect patient outcome. These insights guide the development of future interventions and resource allocation to improve patient outcomes.
Published Version (Please cite this version)
Kuo, Benjamin J, Silvia D Vaca, Joao Ricardo Nickenig Vissoci, Catherine A Staton, Linda Xu, Michael Muhumuza, Hussein Ssenyonjo, John Mukasa, et al. (2017). A prospective neurosurgical registry evaluating the clinical care of traumatic brain injury patients presenting to Mulago National Referral Hospital in Uganda. PloS one, 12(10). p. e0182285. 10.1371/journal.pone.0182285 Retrieved from https://hdl.handle.net/10161/25901.
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Joao Ricardo Nickenig Vissoci, MSc, PhD is an Assistant Professor of Emergency Medicine, Neurosurgery and Global Health. He is the Chief of the Division of Translational Health Sciences in the Department of Emergency Medicine, co-Director of the Global Emergency Medicine Innovation and Implementation (GEMINI) Research Center and a faculty member of the Research Design and Analysis Core (RDAC) in the Duke Global Health Institute. Dr. Vissoci has a background in social psychology and data science. Dr. Vissoci, a Brazilian native, earned a bachelor’s degree in Psychology from State University of Maringá/Brazil, a Masters in Physical Education, an MBA in Human Resources, and a PhD in Social Psychology. During his PhD, he completed a fellowship in Data Science at Duke University. After graduating his PhD in Social Psychology from the Pontificia Universidade Católica of São Paulo/Brazil, Dr. Vissoci completed a postdoctoral fellowship at the University of Sao Paulo (2015) in Design and Analysis for Mental Health research. He completed a second postdoctoral fellowship at the Duke Global Health Institute in Global Health and Data Science in 2016. Dr. Vissoci held a faculty position and taught Public Health and Health Sciences in Brazil from 2009 to 2015. After completing his fellowship at DGHI, he joined the Duke Department of Emergency Medicine as faculty in 2017. In his last 14 years as faculty (2009-current), he has mentored over 200 trainees at all levels of training from undergraduate, graduate, medical education, postdoctoral to faculty level. He has published over 200 manuscripts and collaborated on over 6 R-level NIH grants, multiple (K and D) NIH training grants, other federal grants UK/Brazil based, and foundational grants.
His research interests focus on leveraging data through analytics and technology to bridge the gap in access and equity in care in low resource settings, translating evidence into practice or policy impact. He uses data science and mixed-methods research to design and implement innovative data-driven solutions to address health care gaps.
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