Literature DB >> 33619667

Predictors of Surrogate Decision Makers Selecting Life-Sustaining Therapy for Severe Acute Brain Injury Patients: An Analysis of US Population Survey Data.

Anisha Garg1, Alexandria L Soto2, Andrea K Knies3, Stanislav Kolenikov4, Marci Schalk5, Heather Hammer6, Douglas B White7, Robert G Holloway8, Kevin N Sheth2,9, Liana Fraenkel10,11, David Y Hwang12,13.   

Abstract

BACKGROUND: Patients with a severe acute brain injury admitted to the intensive care unit often have a poor neurological prognosis. In these situations, a clinician is responsible for conducting a goals-of-care conversation with the patient's surrogate decision makers. The diversity in thought and background of surrogate decision makers can present challenges during these conversations. For this reason, our study aimed to identify predictive characteristics of US surrogate decision makers' favoring life-sustaining treatment (LST) over comfort measures only for patients with severe acute brain injury.
METHODS: We analyzed data from a cross-sectional survey study that had recruited 1588 subjects from an online probability-based US population sample. Seven hundred and ninety-two subjects had randomly received a hypothetical scenario regarding a relative intubated with severe acute brain injury with a prognosis of severe disability but with the potential to regain some consciousness. Seven hundred and ninety-six subjects had been randomized to a similar scenario in which the relative was projected to remain vegetative. For each scenario, we conducted univariate analyses and binary logistic regressions to determine predictors of LST selection among available respondent characteristics.
RESULTS: 15.0% of subjects selected LST for the severe disability scenario compared to 11.4% for the vegetative state scenario (p = 0.07), with those selecting LST in both groups expressing less decisional certainty. For the severe disability scenario, independent predictors of LST included having less than a high school education (adjusted OR = 2.87, 95% CI = 1.23-6.76), concern regarding prognostic accuracy (7.64, 3.61-16.15), and concern regarding the cost of care (4.07, 1.80-9.18). For the vegetative scenario, predictors included the youngest age group (30-44 years, 3.33, 1.02-10.86), male gender (3.26, 1.75-6.06), English as a second language (2.94, 1.09-7.89), Evangelical Protestant (3.72, 1.28-10.84) and Catholic (4.01, 1.72-9.36) affiliations, and low income (< $25 K).
CONCLUSION: Several demographic and decisional characteristics of US surrogate decision makers predict LST selection for patients with severe brain injury with varying degrees of poor prognosis. Surrogates concerned about the cost of medical care may nevertheless be inclined to select LST, albeit with high levels of decisional uncertainty, for patients projected to have severe disabilities.
© 2021. Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society.

Entities:  

Keywords:  Brain injuries; Choice behavior; Decision making; Family; Intensive care units; Palliative care

Mesh:

Year:  2021        PMID: 33619667      PMCID: PMC8380750          DOI: 10.1007/s12028-021-01200-9

Source DB:  PubMed          Journal:  Neurocrit Care        ISSN: 1541-6933            Impact factor:   3.532


  11 in total

1.  Differences in level of care at the end of life according to race.

Authors:  Rebecca W Johnson; L Kristin Newby; Christopher B Granger; Wendy A Cook; Eric D Peterson; Melvin Echols; Wanda Bride; Bradi B Granger
Journal:  Am J Crit Care       Date:  2010-07       Impact factor: 2.228

2.  Early mortality following spontaneous intracerebral hemorrhage.

Authors:  J A Zurasky; V Aiyagari; A R Zazulia; A Shackelford; M N Diringer
Journal:  Neurology       Date:  2005-02-22       Impact factor: 9.910

3.  Racial variations in end-of-life care.

Authors:  F P Hopp; S A Duffy
Journal:  J Am Geriatr Soc       Date:  2000-06       Impact factor: 5.562

4.  Minority Patients are Less Likely to Undergo Withdrawal of Care After Spontaneous Intracerebral Hemorrhage.

Authors:  Cora H Ormseth; Guido J Falcone; Sara D Jasak; David M Mampre; Audrey C Leasure; Laura C Miyares; David Y Hwang; Michael L James; Fernando D Testai; Kyra J Becker; David L Tirschwell; Carl D Langefeld; Daniel Woo; Kevin N Sheth
Journal:  Neurocrit Care       Date:  2018-12       Impact factor: 3.210

5.  Surrogate decision makers' interpretation of prognostic information: a mixed-methods study.

Authors:  Lucas S Zier; Peter D Sottile; Seo Yeon Hong; Lisa A Weissfield; Douglas B White
Journal:  Ann Intern Med       Date:  2012-03-06       Impact factor: 25.391

6.  Demographic and clinical determinants of having do not resuscitate orders in the intensive care unit of a comprehensive cancer center.

Authors:  Marylou Cardenas-Turanzas; Susan Gaeta; Aidin Ashoori; Kristen J Price; Joseph L Nates
Journal:  J Palliat Med       Date:  2010-12-31       Impact factor: 2.947

7.  What Families Need and Physicians Deliver: Contrasting Communication Preferences Between Surrogate Decision-Makers and Physicians During Outcome Prognostication in Critically Ill TBI Patients.

Authors:  Thomas Quinn; Jesse Moskowitz; Muhammad W Khan; Lori Shutter; Robert Goldberg; Nananda Col; Kathleen M Mazor; Susanne Muehlschlegel
Journal:  Neurocrit Care       Date:  2017-10       Impact factor: 3.210

8.  Life-sustaining treatments during terminal illness: who wants what?

Authors:  J M Garrett; R P Harris; J K Norburn; D L Patrick; M Danis
Journal:  J Gen Intern Med       Date:  1993-07       Impact factor: 5.128

9.  Phase I Dose-Escalation Study of SCB01A, a Microtubule Inhibitor with Vascular Disrupting Activity, in Patients with Advanced Solid Tumors.

Authors:  Her-Shyong Shiah; Nai-Jung Chiang; Chia-Chi Lin; Chia-Jui Yen; Hui-Jen Tsai; Shang-Yin Wu; Wu-Chou Su; Kwang-Yu Chang; Ching-Chiung Wang; Jang-Yang Chang; Li-Tzong Chen
Journal:  Oncologist       Date:  2020-12-18

10.  Best--worst scaling: What it can do for health care research and how to do it.

Authors:  Terry N Flynn; Jordan J Louviere; Tim J Peters; Joanna Coast
Journal:  J Health Econ       Date:  2006-05-16       Impact factor: 3.883

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  2 in total

1.  Predicting Coma Trajectories: The Impact of Bias and Noise on Shared Decisions.

Authors:  Eelco F M Wijdicks; David Y Hwang
Journal:  Neurocrit Care       Date:  2021-08-23       Impact factor: 3.210

2.  Variability of Prognostic Communication in Critically Ill Neurologic Patients: A Pilot Multicenter Mixed-Methods Study.

Authors:  Connie Ge; Adeline L Goss; Sybil Crawford; Kelsey Goostrey; Praewpannarai Buddadhumaruk; Anne-Marie Shields; Catherine L Hough; Bernard Lo; Shannon S Carson; Jay Steingrub; Douglas B White; Susanne Muehlschlegel
Journal:  Crit Care Explor       Date:  2022-02-21
  2 in total

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