Withdrawal of Life-supporting Treatment in Severe Traumatic Brain Injury.
Date
2020-08
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Abstract
Importance
There are limited data on which factors affect the critical and complex decision to withdraw life-supporting treatment (LST) in patients with severe traumatic brain injury (sTBI).Objective
To determine demographic and clinical factors associated with the decision to withdraw LST in patients with sTBI.Design, setting, and participants
This retrospective analysis of inpatient data from more than 825 trauma centers across the US in the American College of Surgeons Trauma Quality Improvement Program database from January 2013 to December 2015 included adult patients with sTBI and documentation of a decision regarding withdrawal of LST (WLST). Data analysis was conducted in September 2019.Main outcomes and measures
Factors associated with WLST in sTBI.Results
A total of 37931 patients (9817 women [25.9%]) were included in the multivariable analysis; 7864 (20.7%) had WLST. Black patients (4806 [13.2%]; odds ratio [OR], 0.66; 95% CI, 0.59-0.72; P < .001) and patients of other race (4798 [13.2%]; OR, 0.83; 95% CI, 0.76-0.91; P < .001) were less likely than white patients (26 864 [73.7%]) to have WLST. Patients from hospitals in the Midwest (OR, 1.12; 95% CI, 1.04-1.20; P = .002) or Northeast (OR, 1.23; 95% CI, 1.13-1.34; P < .001) were more likely to have WLST than patients from hospitals in the South. Patients with Medicare (OR, 1.55; 95% CI, 1.43-1.69; P < .001) and self-pay patients (OR, 1.36; 95% CI, 1.25-1.47; P < .001) were more likely to have WLST than patients with private insurance. Older patients and those with lower Glasgow Coma Scale scores, higher Injury Severity Scores, or craniotomy were generally more likely to have WLST. Withdrawal of LST was more likely for patients with functionally dependent health status (OR, 1.30; 95% CI, 1.08-1.58; P = .01), hematoma (OR, 1.19; 95% CI, 1.12-1.27; P < .001), dementia (OR, 1.29; 95% CI, 1.08-1.53; P = .004), and disseminated cancer (OR, 2.82; 95% CI, 2.07-3.82; P < .001) than for patients without these conditions.Conclusions and relevance
Withdrawal of LST is common in sTBI and socioeconomic factors are associated with the decision to withdraw LST. These results highlight the many factors that contribute to decision-making in sTBI and demonstrate that in a complex and variable disease process, variation based on race, payment, and region presents as a potential challenge.Type
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Publication Info
Williamson, Theresa, Marc D Ryser, Peter A Ubel, Jihad Abdelgadir, Charis A Spears, Beiyu Liu, Jordan Komisarow, Monica E Lemmon, et al. (2020). Withdrawal of Life-supporting Treatment in Severe Traumatic Brain Injury. JAMA surgery, 155(8). pp. 723–731. 10.1001/jamasurg.2020.1790 Retrieved from https://hdl.handle.net/10161/34227.
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Scholars@Duke
Marc Daniel Ryser
Marc D. Ryser conducts research in cancer early detection, with a particular focus on breast cancer overdiagnosis and overtreatment. Using a multi-scale approach, his group generates and analyzes biologic, clinical and population data using a variety of mathematical, statistical and computational tools. Dr. Ryser teaches an immersive research seminar for undergraduate students called “Math & Medicine.”
Website: https://sites.duke.edu/marcdryser/
Peter A Ubel
I am a physician and behavioral scientist at Duke University. My research and writing explores the quirks in human nature that influence our lives — the mixture of rational and irrational forces that affect our health, our happiness and the way our society functions. (What fun would it be to tackle just the easy problems?)
I am currently exploring controversial issues about the role of values and preferences in health care decision making, from decisions at the bedside to policy decisions. I use the tools of decision psychology and behavioral economics to explore topics like informed consent, shared decision making and health care spending. My books include Pricing Life (MIT Press 2000) and Free Market Madness (Harvard Business Press, 2009). My newest book, Critical Decisions (HarperCollins), came out in September of 2012, and explores the challenges of shared decision making between doctors and patients.
Beiyu Liu
Overview: Beiyu currently collaborates with clinicians, residents and fellows in the Department of Surgery, Department of Dermatology, and Pharmacy. He has extensive biomedical research experience and his specific areas of interest include regression analysis, predictive modeling, survival analysis, and observational studies.
Jordan Komisarow
Monica Elizabeth Lemmon
Shivanand Lad
Dr. Nandan Lad is a neurosurgeon, scientist, and entrepreneur and Professor and Vice Chair of Innovation for Duke Neurosurgery. He is Director of the Functional & Restorative Neuromodulation Program and the Duke NeuroInnovations Program, a systematic approach to innovation to large unmet clinical needs.
He completed his MD and PhD in Biochemistry at Chicago Medical School and his neurosurgical residency training at Stanford with fellowships in both Surgical Innovation and Functional Neurosurgery.
Neuromodulation; Neurorestoration; Bioengineering; Medical Device Design; Clinical Trials; Data Science; Health Outcomes.
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