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Martin FP, Goronflot T, Moyer JD, Huet O, Asehnoune K, Cinotti R, Gourraud PA, Roquilly A. Predictive Models of Long-Term Outcome in Patients with Moderate to Severe Traumatic Brain Injury are Biased Toward Mortality Prediction. Neurocrit Care 2024:10.1007/s12028-024-02082-3. [PMID: 39138720 DOI: 10.1007/s12028-024-02082-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Accepted: 07/26/2024] [Indexed: 08/15/2024]
Abstract
BACKGROUND The prognostication of long-term functional outcomes remains challenging in patients with traumatic brain injury (TBI). Our aim was to demonstrate that intensive care unit (ICU) variables are not efficient to predict 6-month functional outcome in survivors with moderate to severe TBI (msTBI) but are mostly associated with mortality, which leads to a mortality bias for models predicting a composite outcome of mortality and severe disability. METHODS We analyzed the data from the multicenter randomized controlled Continuous Hyperosmolar Therapy in Traumatic Brain-Injured Patients trial and developed predictive models using machine learning methods and baseline characteristics and predictors collected during ICU stay. We compared our models' predictions of 6-month binary Glasgow Outcome Scale extended (GOS-E) score in all patients with msTBI (unfavorable GOS-E 1-4 vs. favorable GOS-E 5-8) with mortality (GOS-E 1 vs. GOS-E 2-8) and binary functional outcome in survivors with msTBI (severe disability GOS-E 2-4 vs. moderate to no disability GOS-E 5-8). We investigated the link between ICU variables and long-term functional outcomes in survivors with msTBI using predictive modeling and factor analysis of mixed data and validated our hypotheses on the International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) model. RESULTS Based on data from 370 patients with msTBI and classically used ICU variables, the prediction of the 6-month outcome in survivors was inefficient (mean area under the receiver operating characteristic 0.52). Using factor analysis of mixed data graph, we demonstrated that high-variance ICU variables were not associated with outcome in survivors with msTBI (p = 0.15 for dimension 1, p = 0.53 for dimension 2) but mostly with mortality (p < 0.001 for dimension 1), leading to a mortality bias for models predicting a composite outcome of mortality and severe disability. We finally identified this mortality bias in the IMPACT model. CONCLUSIONS We demonstrated using machine learning-based predictive models that classically used ICU variables are strongly associated with mortality but not with 6-month outcome in survivors with msTBI, leading to a mortality bias when predicting a composite outcome of mortality and severe disability.
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Affiliation(s)
- Florian P Martin
- Nantes Université, Institut National de la Santé et de la Recherche Médicale (INSERM), UMR 1064, Center for Research in Transplantation and Translational Immunology (CR2TI), 22 Boulevard Bénoni Goullin, 44200, Nantes, France.
- Department of Anesthesiology and Surgical Intensive Care Unit, Centre Hospitalier Universitaire (CHU) Nantes, Nantes, France.
| | - Thomas Goronflot
- CHU Nantes, Pôle Hospitalo-Universitaire 11: Santé Publique, Clinique Des Données, INSERM, Nantes Université, Nantes, France
| | - Jean D Moyer
- Department of Anesthesia and Critical Care, Départements Médico-Universitaires Parabol, Assistance Publique-Hôpitaux de Paris Nord, Beaujon Hospital, Paris, France
| | - Olivier Huet
- Anesthesia and Intensive Care Unit, CHU Brest, Brest, France
| | - Karim Asehnoune
- Nantes Université, Institut National de la Santé et de la Recherche Médicale (INSERM), UMR 1064, Center for Research in Transplantation and Translational Immunology (CR2TI), 22 Boulevard Bénoni Goullin, 44200, Nantes, France
- Department of Anesthesiology and Surgical Intensive Care Unit, Centre Hospitalier Universitaire (CHU) Nantes, Nantes, France
| | - Raphaël Cinotti
- Department of Anesthesiology and Surgical Intensive Care Unit, Centre Hospitalier Universitaire (CHU) Nantes, Nantes, France
- Methods in Patient-Centered Outcomes and Healthy Research (SPHERE), INSERM, UMR 1246, Nantes Université, Université de Tours, Nantes, France
| | - Pierre A Gourraud
- Nantes Université, Institut National de la Santé et de la Recherche Médicale (INSERM), UMR 1064, Center for Research in Transplantation and Translational Immunology (CR2TI), 22 Boulevard Bénoni Goullin, 44200, Nantes, France
- CHU Nantes, Pôle Hospitalo-Universitaire 11: Santé Publique, Clinique Des Données, INSERM, Nantes Université, Nantes, France
| | - Antoine Roquilly
- Nantes Université, Institut National de la Santé et de la Recherche Médicale (INSERM), UMR 1064, Center for Research in Transplantation and Translational Immunology (CR2TI), 22 Boulevard Bénoni Goullin, 44200, Nantes, France
- Department of Anesthesiology and Surgical Intensive Care Unit, Centre Hospitalier Universitaire (CHU) Nantes, Nantes, France
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Malhotra AK, Shakil H, Essa A, Mathieu F, Taran S, Badhiwala J, He Y, Yuan EY, Kulkarni AV, Wilson JR, Nathens AB, Witiw CD. Influence of health insurance on withdrawal of life sustaining treatment for patients with isolated traumatic brain injury: a retrospective multi-center observational cohort study. Crit Care 2024; 28:251. [PMID: 39026325 PMCID: PMC11264615 DOI: 10.1186/s13054-024-05027-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Accepted: 07/06/2024] [Indexed: 07/20/2024] Open
Abstract
BACKGROUND Healthcare inequities for patients with traumatic brain injury (TBI) represent a major priority area for trauma quality improvement. We hypothesized a relationship between health insurance status and timing of withdrawal of life sustaining treatment (WLST) for adults with severe TBI. METHODS This multicenter retrospective observational cohort study utilized data collected between 2017 and 2020. We identified adult (age ≥ 16) patients with isolated severe TBI admitted participating Trauma Quality Improvement Program centers. We determined the relationship between insurance status (public, private, and uninsured) and the timing of WLST using a competing risk survival analysis framework adjusting for baseline, clinical, injury and trauma center characteristics. Multivariable cause-specific Cox regressions were used to compute adjusted hazard ratios (HR) reflecting timing of WLST, accounting for mortality events. We also quantified the between-center residual variability in WLST using the median odds ratio (MOR) and measured insurance status association with access to rehabilitation at discharge. RESULTS We identified 42,111 adults with isolated severe TBI treated across 509 trauma centers across North America. There were 10,771 (25.6%) WLST events in the cohort and a higher unadjusted incidence of WLST events was evident in public insurance patients compared to private or uninsured groups. After adjustment, WLST occurred earlier for publicly insured (HR 1.07, 95% CI 1.02-1.12) and uninsured patients (HR 1.29, 95% CI 1.18-1.41) compared to privately insured patients. Access to rehabilitation was lower for both publicly insured and uninsured patients compared to patients with private insurance. Accounting for case-mix, the MOR was 1.49 (95% CI 1.43-1.55), reflecting significant residual between-center variation in WLST decision-making. CONCLUSIONS Our findings highlight the presence of disparate WLST practices independently associated with health insurance status. Additionally, these results emphasize between-center variability in WLST, persisting despite adjustments for measurable patient and trauma center characteristics.
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Affiliation(s)
- Armaan K Malhotra
- Division of Neurosurgery, Unity Health Toronto, St. Michael's Hospital, 30 Bond Street, Toronto, ON, M5B1W8, Canada
- Li Ka Shing Knowledge Institute, Toronto, ON, Canada
- Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Husain Shakil
- Division of Neurosurgery, Unity Health Toronto, St. Michael's Hospital, 30 Bond Street, Toronto, ON, M5B1W8, Canada
- Li Ka Shing Knowledge Institute, Toronto, ON, Canada
- Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Ahmad Essa
- Division of Neurosurgery, Unity Health Toronto, St. Michael's Hospital, 30 Bond Street, Toronto, ON, M5B1W8, Canada
- Division of Orthopedics, Department of Surgery, Shamir Medical Center (Assaf Harofeh), Zerifin, Israel
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Francois Mathieu
- Division of Neurosurgery, Unity Health Toronto, St. Michael's Hospital, 30 Bond Street, Toronto, ON, M5B1W8, Canada
- Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada
| | - Shaurya Taran
- Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
- Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada
| | - Jetan Badhiwala
- Division of Neurosurgery, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Yingshi He
- Division of Neurosurgery, Unity Health Toronto, St. Michael's Hospital, 30 Bond Street, Toronto, ON, M5B1W8, Canada
- Li Ka Shing Knowledge Institute, Toronto, ON, Canada
| | - Eva Y Yuan
- Division of Neurosurgery, Unity Health Toronto, St. Michael's Hospital, 30 Bond Street, Toronto, ON, M5B1W8, Canada
- Li Ka Shing Knowledge Institute, Toronto, ON, Canada
| | - Abhaya V Kulkarni
- Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
- Division of Neurosurgery, Hospital for Sick Children, Toronto, ON, Canada
| | - Jefferson R Wilson
- Division of Neurosurgery, Unity Health Toronto, St. Michael's Hospital, 30 Bond Street, Toronto, ON, M5B1W8, Canada
- Li Ka Shing Knowledge Institute, Toronto, ON, Canada
- Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Avery B Nathens
- Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
- Division of General Surgery, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Christopher D Witiw
- Division of Neurosurgery, Unity Health Toronto, St. Michael's Hospital, 30 Bond Street, Toronto, ON, M5B1W8, Canada.
- Li Ka Shing Knowledge Institute, Toronto, ON, Canada.
- Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada.
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White AJ, Kelly-Hedrick M, Miranda SP, Abdelbarr MM, Lázaro-Muñoz G, Pouratian N, Shen F, Nahed BV, Williamson T. Bioethics and Neurosurgery: An Overview of Existing and Emerging Topics for the Practicing Neurosurgeon. World Neurosurg 2024; 190:181-186. [PMID: 39004179 DOI: 10.1016/j.wneu.2024.07.051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2024] [Accepted: 07/05/2024] [Indexed: 07/16/2024]
Abstract
Neurosurgery is a field with complex ethical issues. In this article, we aim to provide an overview of key and emerging ethical issues in neurosurgery with a focus on issues relevant to practicing neurosurgeons. These issues include those of informed consent, capacity, clinical trials, emerging neurotechnology, innovation, equity and justice, and emerging bioethics areas including community engagement and organizational ethics. We argue that bioethics can help neurosurgeons think about and address these issues, and, in turn, the field of bioethics can benefit from engagement by neurosurgeons. Several ideas for increasing engagement in bioethics are proposed.
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Affiliation(s)
- Alexandra J White
- Department of Neurosurgery, University of California, Los Angeles, Los Angeles, California, USA
| | - Margot Kelly-Hedrick
- Department of Neurological Surgery, University of Washington, Seattle, Washington, USA.
| | - Stephen P Miranda
- Department of Neurosurgery, University of Pennsylvania, Pennsylvania, Pennsylvania, USA
| | | | | | - Nader Pouratian
- Department of Neurological Surgery, University of Texas Southwestern, Dallas, Texas, USA
| | - Francis Shen
- Center for Bioethics, Harvard Medical School, Boston, Massachusetts, USA; Harvard Law School, Cambridge, Massachusetts, USA
| | - Brian V Nahed
- Department of Neurosurgery, Massachusetts General Hospital, Boston, Massachusetts, USA; Harvard Medical School, Boston, Massachusetts, USA
| | - Theresa Williamson
- Department of Neurosurgery, Massachusetts General Hospital, Boston, Massachusetts, USA; Harvard Medical School, Boston, Massachusetts, USA
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Lissak IA, Young MJ. Limitation of life sustaining therapy in disorders of consciousness: ethics and practice. Brain 2024; 147:2274-2288. [PMID: 38387081 PMCID: PMC11224617 DOI: 10.1093/brain/awae060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 02/01/2024] [Accepted: 02/08/2024] [Indexed: 02/24/2024] Open
Abstract
Clinical conversations surrounding the continuation or limitation of life-sustaining therapies (LLST) are both challenging and tragically necessary for patients with disorders of consciousness (DoC) following severe brain injury. Divergent cultural, philosophical and religious perspectives contribute to vast heterogeneity in clinical approaches to LLST-as reflected in regional differences and inter-clinician variability. Here we provide an ethical analysis of factors that inform LLST decisions among patients with DoC. We begin by introducing the clinical and ethical challenge and clarifying the distinction between withdrawing and withholding life-sustaining therapy. We then describe relevant factors that influence LLST decision-making including diagnostic and prognostic uncertainty, perception of pain, defining a 'good' outcome, and the role of clinicians. In concluding sections, we explore global variation in LLST practices as they pertain to patients with DoC and examine the impact of cultural and religious perspectives on approaches to LLST. Understanding and respecting the cultural and religious perspectives of patients and surrogates is essential to protecting patient autonomy and advancing goal-concordant care during critical moments of medical decision-making involving patients with DoC.
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Affiliation(s)
- India A Lissak
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Michael J Young
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
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Al-Fadhl MD, Karam MN, Chen J, Zackariya SK, Lain MC, Bales JR, Higgins AB, Laing JT, Wang HS, Andrews MG, Thomas AV, Smith L, Fox MD, Zackariya SK, Thomas SJ, Tincher AM, Al-Fadhl HD, Weston M, Marsh PL, Khan HA, Thomas EJ, Miller JB, Bailey JA, Koenig JJ, Waxman DA, Srikureja D, Fulkerson DH, Fox S, Bingaman G, Zimmer DF, Thompson MA, Bunch CM, Walsh MM. Traumatic Brain Injury as an Independent Predictor of Futility in the Early Resuscitation of Patients in Hemorrhagic Shock. J Clin Med 2024; 13:3915. [PMID: 38999481 PMCID: PMC11242176 DOI: 10.3390/jcm13133915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Revised: 06/08/2024] [Accepted: 06/26/2024] [Indexed: 07/14/2024] Open
Abstract
This review explores the concept of futility timeouts and the use of traumatic brain injury (TBI) as an independent predictor of the futility of resuscitation efforts in severely bleeding trauma patients. The national blood supply shortage has been exacerbated by the lingering influence of the COVID-19 pandemic on the number of blood donors available, as well as by the adoption of balanced hemostatic resuscitation protocols (such as the increasing use of 1:1:1 packed red blood cells, plasma, and platelets) with and without early whole blood resuscitation. This has underscored the urgent need for reliable predictors of futile resuscitation (FR). As a result, clinical, radiologic, and laboratory bedside markers have emerged which can accurately predict FR in patients with severe trauma-induced hemorrhage, such as the Suspension of Transfusion and Other Procedures (STOP) criteria. However, the STOP criteria do not include markers for TBI severity or transfusion cut points despite these patients requiring large quantities of blood components in the STOP criteria validation cohort. Yet, guidelines for neuroprognosticating patients with TBI can require up to 72 h, which makes them less useful in the minutes and hours following initial presentation. We examine the impact of TBI on bleeding trauma patients, with a focus on those with coagulopathies associated with TBI. This review categorizes TBI into isolated TBI (iTBI), hemorrhagic isolated TBI (hiTBI), and polytraumatic TBI (ptTBI). Through an analysis of bedside parameters (such as the proposed STOP criteria), coagulation assays, markers for TBI severity, and transfusion cut points as markers of futilty, we suggest amendments to current guidelines and the development of more precise algorithms that incorporate prognostic indicators of severe TBI as an independent parameter for the early prediction of FR so as to optimize blood product allocation.
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Affiliation(s)
- Mahmoud D Al-Fadhl
- Department of Medical Education, South Bend Campus, Indiana University School of Medicine, South Bend, IN 46617, USA
| | - Marie Nour Karam
- Department of Medical Education, South Bend Campus, Indiana University School of Medicine, South Bend, IN 46617, USA
| | - Jenny Chen
- Department of Medical Education, South Bend Campus, Indiana University School of Medicine, South Bend, IN 46617, USA
| | - Sufyan K Zackariya
- Department of Medical Education, South Bend Campus, Indiana University School of Medicine, South Bend, IN 46617, USA
| | - Morgan C Lain
- Department of Medical Education, South Bend Campus, Indiana University School of Medicine, South Bend, IN 46617, USA
| | - John R Bales
- Department of Medical Education, South Bend Campus, Indiana University School of Medicine, South Bend, IN 46617, USA
| | - Alexis B Higgins
- Department of Medical Education, South Bend Campus, Indiana University School of Medicine, South Bend, IN 46617, USA
| | - Jordan T Laing
- Department of Medical Education, South Bend Campus, Indiana University School of Medicine, South Bend, IN 46617, USA
| | - Hannah S Wang
- Department of Medical Education, South Bend Campus, Indiana University School of Medicine, South Bend, IN 46617, USA
| | - Madeline G Andrews
- Department of Medical Education, South Bend Campus, Indiana University School of Medicine, South Bend, IN 46617, USA
| | - Anthony V Thomas
- Department of Medical Education, South Bend Campus, Indiana University School of Medicine, South Bend, IN 46617, USA
| | - Leah Smith
- Department of Medical Education, South Bend Campus, Indiana University School of Medicine, South Bend, IN 46617, USA
| | - Mark D Fox
- Department of Medical Education, South Bend Campus, Indiana University School of Medicine, South Bend, IN 46617, USA
| | - Saniya K Zackariya
- Department of Internal Medicine, Saint Joseph Regional Medical Center, Mishawaka, IN 46545, USA
| | - Samuel J Thomas
- Department of Internal Medicine, Saint Joseph Regional Medical Center, Mishawaka, IN 46545, USA
| | - Anna M Tincher
- Department of Medical Education, South Bend Campus, Indiana University School of Medicine, South Bend, IN 46617, USA
| | - Hamid D Al-Fadhl
- Department of Medical Education, South Bend Campus, Indiana University School of Medicine, South Bend, IN 46617, USA
| | - May Weston
- Department of Internal Medicine, Saint Joseph Regional Medical Center, Mishawaka, IN 46545, USA
| | - Phillip L Marsh
- Department of Internal Medicine, Saint Joseph Regional Medical Center, Mishawaka, IN 46545, USA
| | - Hassaan A Khan
- Department of Internal Medicine, Saint Joseph Regional Medical Center, Mishawaka, IN 46545, USA
| | - Emmanuel J Thomas
- Department of Internal Medicine, Saint Joseph Regional Medical Center, Mishawaka, IN 46545, USA
| | - Joseph B Miller
- Department of Emergency Medicine, Henry Ford Hospital, Detroit, MI 48202, USA
| | - Jason A Bailey
- Department of Emergency Medicine, Elkhart General Hospital, Elkhart, IN 46515, USA
| | - Justin J Koenig
- Department of Trauma & Surgical Services, Memorial Hospital, South Bend, IN 46601, USA
| | - Dan A Waxman
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN 46601, USA
- Versiti Blood Center of Indiana, Indianapolis, IN 46208, USA
| | - Daniel Srikureja
- Department of Surgery, Memorial Hospital, South Bend, IN 46601, USA
| | - Daniel H Fulkerson
- Department of Trauma & Surgical Services, Memorial Hospital, South Bend, IN 46601, USA
- Department of Neurosurgery, Memorial Hospital, South Bend, IN 46601, USA
| | - Sarah Fox
- Department of Trauma & Surgical Services, Memorial Hospital, South Bend, IN 46601, USA
| | - Greg Bingaman
- Department of Trauma & Surgical Services, Memorial Hospital, South Bend, IN 46601, USA
| | - Donald F Zimmer
- Department of Emergency Medicine, Memorial Hospital, South Bend, IN 46601, USA
| | - Mark A Thompson
- Department of Surgery, Memorial Hospital, South Bend, IN 46601, USA
| | - Connor M Bunch
- Department of Emergency Medicine, Henry Ford Hospital, Detroit, MI 48202, USA
| | - Mark M Walsh
- Department of Internal Medicine, Saint Joseph Regional Medical Center, Mishawaka, IN 46545, USA
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Muehlschlegel S. Prognostication in Neurocritical Care. Continuum (Minneap Minn) 2024; 30:878-903. [PMID: 38830074 DOI: 10.1212/con.0000000000001433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/05/2024]
Abstract
OBJECTIVE This article synthesizes the current literature on prognostication in neurocritical care, identifies existing challenges, and proposes future research directions to reduce variability and enhance scientific and patient-centered approaches to neuroprognostication. LATEST DEVELOPMENTS Patients with severe acute brain injury often lack the capacity to make their own medical decisions, leaving surrogate decision makers responsible for life-or-death choices. These decisions heavily rely on clinicians' prognostication, which is still considered an art because of the previous lack of specific guidelines. Consequently, there is significant variability in neuroprognostication practices. This article examines various aspects of neuroprognostication. It explores the cognitive approach to prognostication, highlights the use of statistical modeling such as Bayesian models and machine learning, emphasizes the importance of clinician-family communication during prognostic disclosures, and proposes shared decision making for more patient-centered care. ESSENTIAL POINTS This article identifies ongoing challenges in the field and emphasizes the need for future research to ameliorate variability in neuroprognostication. By focusing on scientific methodologies and patient-centered approaches, this research aims to provide guidance and tools that may enhance neuroprognostication in neurocritical care.
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Gakuba C, Le Barbey C, Sar A, Bonnet G, Cerasuolo D, Giabicani M, Moyer JD. Evaluation of ChatGPT in Predicting 6-Month Outcomes After Traumatic Brain Injury. Crit Care Med 2024; 52:942-950. [PMID: 38445975 DOI: 10.1097/ccm.0000000000006236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/07/2024]
Abstract
OBJECTIVES To evaluate the capacity of ChatGPT, a widely accessible and uniquely popular artificial intelligence-based chatbot, in predicting the 6-month outcome following moderate-to-severe traumatic brain injury (TBI). DESIGN Single-center observational retrospective study. SETTING Data are from a neuro-ICU from a level 1 trauma center. PATIENTS All TBI patients admitted to ICU between September 2021 and October 2022 were included in a prospective database. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS Based on anonymized clinical, imaging, and biological information available at the patients' hospital admission and extracted from the database, clinical vignettes were retrospectively submitted to ChatGPT for prediction of patients' outcomes. The predictions of two intensivists (one neurointensivist and one non-neurointensivist) both from another level 1 trauma center (Beaujon Hospital), were also collected as was the International Mission on Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury (IMPACT) scoring. Each intensivist, as well as ChatGPT, made their prognostic evaluations independently, without knowledge of the others' predictions and of the patients' actual management and outcome. Both the intensivists and ChatGPT were given access to the exact same set of information. The main outcome was a 6-month-functional status dichotomized into favorable (Glasgow Outcome Scale Extended [GOSE] ≥ 5) versus poor (GOSE < 5). Prediction of intracranial hypertension management, pulmonary infectious risk, and removal of life-sustaining therapies was also investigated as secondary outcomes. Eighty consecutive moderate-to-severe TBI patients were included. For the 6-month outcome prognosis, area under the receiver operating characteristic curve (AUC-ROC) for ChatGPT, the neurointensivist, the non-neurointensivist, and IMPACT were, respectively, 0.62 (0.50-0.74), 0.70 (0.59-0.82), 0.71 (0.59-0.82), and 0.81 (0.72-0.91). ChatGPT had the highest sensitivity (100%), but the lowest specificity (26%). For secondary outcomes, ChatGPT's prognoses were generally less accurate than clinicians' prognoses, with lower AUC values for most outcomes. CONCLUSIONS This study does not support the use of ChatGPT for prediction of outcomes after TBI.
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Affiliation(s)
- Clement Gakuba
- CHU de Caen Normandie, Department of Anesthesiology and Critical Care Medicine, Caen, France
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - Charlene Le Barbey
- CHU de Caen Normandie, Department of Anesthesiology and Critical Care Medicine, Caen, France
| | - Alexandre Sar
- CHU de Caen Normandie, Department of Anesthesiology and Critical Care Medicine, Caen, France
| | - Gregory Bonnet
- Normandie Univ, UNICAEN, ENSICAEN, CNRS, Department of Groupe de Recherche en Informatique, Image, et Instrumentation de Caen (GREYC), Caen, France
| | - Damiano Cerasuolo
- CHU de Caen Normandie, Department of Public Health, Caen, France
- Normandie Univ, UNICAEN, INSERM U1086, ANTICIPE, Caen, France
| | - Mikhael Giabicani
- Department of Anaesthesiology and Critical Care, Beaujon Hospital, DMU Parabol, AP-HP Nord, Paris, France
| | - Jean-Denis Moyer
- CHU de Caen Normandie, Department of Anesthesiology and Critical Care Medicine, Caen, France
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Bhogadi SK, Nelson A, Hosseinpour H, Anand T, Hejazi O, Colosimo C, Spencer AL, Ditillo M, Magnotti LJ, Joseph B. Effect of PCC on outcomes of severe traumatic brain injury patients on preinjury anticoagulation. Am J Surg 2024; 232:138-141. [PMID: 38309997 DOI: 10.1016/j.amjsurg.2024.01.035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2023] [Revised: 01/28/2024] [Accepted: 01/29/2024] [Indexed: 02/05/2024]
Abstract
INTRODUCTION This study aims to evaluate effect of 4-factor PCC on outcomes of severe TBI patients on preinjury anticoagulants undergoing craniotomy/craniectomy. METHODS In this analysis of 2018-2020 ACS-TQIP, patients with isolated blunt severe TBI (Head-AIS≥3, nonhead-AIS<2) using preinjury anticoagulants who underwent craniotomy/craniectomy were identified and stratified into PCC and No-PCC groups. Outcomes were time to surgery and mortality. Multivariable binary logistic and linear regression analyses were performed. RESULTS 1598 patients were identified (PCC-107[7 %], No-PCC-1491[93 %]). Mean age was 74(11) years, 65 % were male, median head AIS was 4. Median time to PCC administration was 109 min. On univariable analysis, PCC group had shorter time to surgery (PCC-341, No-PCC-620 min, p = 0.002), but higher mortality (PCC35 %, No-PCC21 %,p = 0.001). On regression analysis, PCC was independently associated with shorter time to surgery (β = -1934,95 %CI = -3339to-26), but not mortality (aOR = 0.70,95 %CI = 0.14-3.62). CONCLUSION PCC may be a safe adjunct for urgent reversal of coagulopathy in TBI patients using preinjury anticoagulants.
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Affiliation(s)
- Sai Krishna Bhogadi
- Division of Trauma, Critical Care, Burns, and Emergency Surgery, Department of Surgery, College of Medicine, University of Arizona, Tucson, AZ, USA.
| | - Adam Nelson
- Division of Trauma, Critical Care, Burns, and Emergency Surgery, Department of Surgery, College of Medicine, University of Arizona, Tucson, AZ, USA.
| | - Hamidreza Hosseinpour
- Division of Trauma, Critical Care, Burns, and Emergency Surgery, Department of Surgery, College of Medicine, University of Arizona, Tucson, AZ, USA.
| | - Tanya Anand
- Division of Trauma, Critical Care, Burns, and Emergency Surgery, Department of Surgery, College of Medicine, University of Arizona, Tucson, AZ, USA.
| | - Omar Hejazi
- Division of Trauma, Critical Care, Burns, and Emergency Surgery, Department of Surgery, College of Medicine, University of Arizona, Tucson, AZ, USA.
| | - Christina Colosimo
- Division of Trauma, Critical Care, Burns, and Emergency Surgery, Department of Surgery, College of Medicine, University of Arizona, Tucson, AZ, USA.
| | - Audrey L Spencer
- Division of Trauma, Critical Care, Burns, and Emergency Surgery, Department of Surgery, College of Medicine, University of Arizona, Tucson, AZ, USA.
| | - Michael Ditillo
- Division of Trauma, Critical Care, Burns, and Emergency Surgery, Department of Surgery, College of Medicine, University of Arizona, Tucson, AZ, USA.
| | - Louis J Magnotti
- Division of Trauma, Critical Care, Burns, and Emergency Surgery, Department of Surgery, College of Medicine, University of Arizona, Tucson, AZ, USA.
| | - Bellal Joseph
- Division of Trauma, Critical Care, Burns, and Emergency Surgery, Department of Surgery, College of Medicine, University of Arizona, Tucson, AZ, USA.
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Sanders WR, Barber JK, Temkin NR, Foreman B, Giacino JT, Williamson T, Edlow BL, Manley GT, Bodien YG. Recovery Potential in Patients Who Died After Withdrawal of Life-Sustaining Treatment: A TRACK-TBI Propensity Score Analysis. J Neurotrauma 2024. [PMID: 38739032 DOI: 10.1089/neu.2024.0014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/14/2024] Open
Abstract
Among patients with severe traumatic brain injury (TBI), there is high prognostic uncertainty but growing evidence that recovery of independence is possible. Nevertheless, families are often asked to make decisions about withdrawal of life-sustaining treatment (WLST) within days of injury. The range of potential outcomes for patients who died after WLST (WLST+) is unknown, posing a challenge for prognostic modeling and clinical counseling. We investigated the potential for survival and recovery of independence after acute TBI in patients who died after WLST. We used Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) data and propensity score matching to pair participants with WLST+ to those with a similar probability of WLST (based on demographic and clinical characteristics), but for whom life-sustaining treatment was not withdrawn (WLST-). To optimize matching, we divided the WLST- cohort into tiers (Tier 1 = 0-11%, Tier 2 = 11-27%, Tier 3 = 27-70% WLST propensity). We estimated the level of recovery that could be expected in WLST+ participants by evaluating 3-, 6-, and 12-month Glasgow Outcome Scale-Extended (GOSE) and Disability Rating Scale outcomes in matched WLST- participants. Of 90 WLST+ participants (80% male, mean [standard deviation; SD] age = 59.2 [17.9] years, median [IQR] days to WLST = 5.4 [2.2, 11.7]), 80 could be matched to WLST- participants. Of 56 WLST- participants who were followed at 6 months, 31 (55%) died. Among survivors in the overall sample and survivors in Tiers 1 and 2, more than 30% recovered at least partial independence (GOSE ≥4). In Tier 3, recovery to GOSE ≥4 occurred at 12 months, but not 6 months, post-injury. These results suggest a substantial proportion of patients with TBI and WLST may have survived and achieved at least partial independence. However, death or severe disability is a common outcome when the probability of WLST is high. While further validation is needed, our findings support a more cautious clinical approach to WLST and more complete reporting on WLST in TBI studies.
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Affiliation(s)
- William R Sanders
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire, USA
| | - Jason K Barber
- Department of Neurological Surgery, University of Washington, Seattle, Washington, USA
| | - Nancy R Temkin
- Department of Neurological Surgery, University of Washington, Seattle, Washington, USA
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Brandon Foreman
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati, Cincinnati, Ohio, USA
| | - Joseph T Giacino
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Charlestown, Massachusetts, USA
- Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, Massachusetts, USA
| | - Theresa Williamson
- Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts, USA
| | - Geoffrey T Manley
- Department of Neurological Surgery, University of California San Francisco, San Francisco, California, USA
| | - Yelena G Bodien
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Charlestown, Massachusetts, USA
- Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, Massachusetts, USA
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10
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Aude CA, Vattipally VN, Das O, Ran KR, Giwa GA, Rincon-Torroella J, Xu R, Byrne JP, Muehlschlegel S, Suarez JI, Mukherjee D, Huang J, Azad TD, Bettegowda C. Machine Learning Identifies Variation in Timing of Palliative Care Consultations Among Traumatic Brain Injury Patients. RESEARCH SQUARE 2024:rs.3.rs-4290808. [PMID: 38746163 PMCID: PMC11092864 DOI: 10.21203/rs.3.rs-4290808/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Background and Objective Timely palliative care involvement offers demonstrable benefits for traumatic brain injury (TBI) patients; however, palliative care consultations (PCCs) are used inconsistently during TBI management. This study aimed to employ advanced machine learning techniques to elucidate the primary drivers of PCC timing variability for TBI patients. Methods Data on admission, hospital course, and outcomes were collected for a cohort of 232 TBI patients who received both PCCs and neurosurgical consultations during the same hospitalization. Principal Component Analysis (PCA) and K-means clustering were used to identify patient phenotypes, which were then compared using Kaplan-Meier analysis. An extreme gradient boosting model (XGBoost) was employed to determine drivers of PCC timing, with model interpretation performed using SHapley Additive exPlanations (SHAP). Results Cluster A (n = 86) consisted mainly of older (median [IQR] = 87 [78, 94] years), White females with mild TBIs and demonstrated the shortest time-to-PCC (2.5 [1.0, 7.0] days). Cluster B (n = 108) also sustained mild TBIs but comprised moderately younger (81 [75, 86] years) married White males with later PCC (5.0 [3.0, 10.8] days). Cluster C (n = 38) represented much younger (46.5 [29.5, 59.8] years), more severely injured, non-White patients with the latest PCC initiation (9.0 [4.2, 17.0] days). The clusters did not differ by discharge disposition (p = 0.4) or frequency inpatient mortality (p > 0.9); however, Kaplan-Meier analysis revealed a significant difference in the time from admission to PCC (p < 0.001), despite no differences in time from admission to mortality (p = 0.18). SHAP analysis of the XGBoost model identified age, sex, and race as the most influential drivers of PCC timing. Conclusions This study highlights crucial disparities in PCC timing for TBI patients and underscores the need for targeted strategies to ensure timely and equitable palliative care integration for this vulnerable population.
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Affiliation(s)
| | | | - Oishika Das
- The Johns Hopkins University School of Medicine
| | | | | | | | - Risheng Xu
- The Johns Hopkins University School of Medicine
| | | | | | | | | | - Judy Huang
- The Johns Hopkins University School of Medicine
| | - Tej D Azad
- The Johns Hopkins University School of Medicine
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11
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Mansour A, Powla PP, Alvarado-Dyer R, Fakhri F, Das P, Horowitz P, Goldenberg FD, Lazaridis C. Comparative Analysis of Clinical Severity and Outcomes in Penetrating Versus Blunt Traumatic Brain Injury Propensity Matched Cohorts. Neurotrauma Rep 2024; 5:348-358. [PMID: 38595793 PMCID: PMC11002325 DOI: 10.1089/neur.2024.0009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/11/2024] Open
Abstract
Traumatic brain injury (TBI) is a global health challenge; however, penetrating brain injury (PBI) remains under-represented in evidence-based knowledge and research efforts. This study utilized data from the Trauma Quality Improvement Program (TQIP) of the National Trauma Data Bank (NTDB) to investigate outcomes of PBI as compared with clinical-severity-matched non-penetrating or blunt TBI. A total of 1765 patients with PBI were 1:1 propensity score-matched for clinical severity with blunt TBI patients. The intent of PBI was self-inflicted in 34.1% of the cases, and the mechanism was firearm-inflicted in 89.1%. Mortality was found to be significantly more common in PBI than in the severity- matched TBI cohort (33.9% vs. 14.3 %, p < 0.001) as was unfavorable outcome. Mortality was mediated by withdrawal of life-sustaining therapies (WOLST) 30% of the time, and WOLST occurred earlier (median 3 days vs. 6 days, p < 0.001) in PBI. Increased rate of mortality was observed with a Glasgow Coma Scale (GCS) of <11 in PBI as compared with <7 in blunt TBI. In conclusion, PBI patients exhibited higher mortality rates and unfavorable outcomes; one third of excess mortality was mediated by WOLST. The study also brings into question the applicability of the conventional TBI classification, based on GCS, in PBI. We emphasize the need to address the observed disparities and better understand the distinctive characteristics and mechanisms underlying PBI outcomes to improve patient care and reduce mortality.
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Affiliation(s)
- Ali Mansour
- Department of Neurology, Division of Neurocritical Care, University of Chicago Medical Center, Chicago, Illinois, USA
- Department of Neurological Surgery, University of Chicago Medical Center, Chicago, Illinois, USA
| | - Plamena P. Powla
- Department of Neurology, Division of Neurocritical Care, University of Chicago Medical Center, Chicago, Illinois, USA
| | - Ronald Alvarado-Dyer
- Department of Neurology, Neurosciences Intensive Care Unit, OU Health University of Oklahoma Medical Center, Oklahoma City, Oklahoma, USA
| | - Farima Fakhri
- Department of Neurology, Division of Neurocritical Care, University of Chicago Medical Center, Chicago, Illinois, USA
| | - Paramita Das
- Department of Neurological Surgery, University of Chicago Medical Center, Chicago, Illinois, USA
| | - Peleg Horowitz
- Department of Neurological Surgery, University of Chicago Medical Center, Chicago, Illinois, USA
| | - Fernando D. Goldenberg
- Department of Neurology, Division of Neurocritical Care, University of Chicago Medical Center, Chicago, Illinois, USA
- Department of Neurological Surgery, University of Chicago Medical Center, Chicago, Illinois, USA
| | - Christos Lazaridis
- Department of Neurology, Division of Neurocritical Care, University of Chicago Medical Center, Chicago, Illinois, USA
- Department of Neurological Surgery, University of Chicago Medical Center, Chicago, Illinois, USA
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12
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Muehlschlegel S, Rajajee V, Wartenberg KE, Alexander SA, Busl KM, Creutzfeldt CJ, Fontaine GV, Hocker SE, Hwang DY, Kim KS, Madzar D, Mahanes D, Mainali S, Meixensberger J, Sakowitz OW, Varelas PN, Weimar C, Westermaier T. Guidelines for Neuroprognostication in Critically Ill Adults with Moderate-Severe Traumatic Brain Injury. Neurocrit Care 2024; 40:448-476. [PMID: 38366277 PMCID: PMC10959796 DOI: 10.1007/s12028-023-01902-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 11/22/2023] [Indexed: 02/18/2024]
Abstract
BACKGROUND Moderate-severe traumatic brain injury (msTBI) carries high morbidity and mortality worldwide. Accurate neuroprognostication is essential in guiding clinical decisions, including patient triage and transition to comfort measures. Here we provide recommendations regarding the reliability of major clinical predictors and prediction models commonly used in msTBI neuroprognostication, guiding clinicians in counseling surrogate decision-makers. METHODS Using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology, we conducted a systematic narrative review of the most clinically relevant predictors and prediction models cited in the literature. The review involved framing specific population/intervention/comparator/outcome/timing/setting (PICOTS) questions and employing stringent full-text screening criteria to examine the literature, focusing on four GRADE criteria: quality of evidence, desirability of outcomes, values and preferences, and resource use. Moreover, good practice recommendations addressing the key principles of neuroprognostication were drafted. RESULTS After screening 8125 articles, 41 met our eligibility criteria. Ten clinical variables and nine grading scales were selected. Many articles varied in defining "poor" functional outcomes. For consistency, we treated "poor" as "unfavorable". Although many clinical variables are associated with poor outcome in msTBI, only the presence of bilateral pupillary nonreactivity on admission, conditional on accurate assessment without confounding from medications or injuries, was deemed moderately reliable for counseling surrogates regarding 6-month functional outcomes or in-hospital mortality. In terms of prediction models, the Corticosteroid Randomization After Significant Head Injury (CRASH)-basic, CRASH-CT (CRASH-basic extended by computed tomography features), International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT)-core, IMPACT-extended, and IMPACT-lab models were recommended as moderately reliable in predicting 14-day to 6-month mortality and functional outcomes at 6 months and beyond. When using "moderately reliable" predictors or prediction models, the clinician must acknowledge "substantial" uncertainty in the prognosis. CONCLUSIONS These guidelines provide recommendations to clinicians on the formal reliability of individual predictors and prediction models of poor outcome when counseling surrogates of patients with msTBI and suggest broad principles of neuroprognostication.
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Affiliation(s)
- Susanne Muehlschlegel
- Departments of Neurology and Anesthesiology/Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | | | | | | | - Katharina M Busl
- Departments of Neurology and Neurosurgery, University of Florida College of Medicine, Gainesville, FL, USA
| | | | - Gabriel V Fontaine
- Departments of Pharmacy and Neurosciences, Intermountain Health, Salt Lake City, UT, USA
| | - Sara E Hocker
- Department of Neurology, Saint Luke's Health System, Kansas City, MO, USA
| | - David Y Hwang
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Keri S Kim
- Department of Pharmacy Practice, University of Illinois at Chicago, Chicago, IL, USA
| | - Dominik Madzar
- Department of Neurology, University of Erlangen-Nuremberg, Erlangen, Germany
| | - Dea Mahanes
- Departments of Neurology and Neurosurgery, University of Virginia Health, Charlottesville, VA, USA
| | - Shraddha Mainali
- Department of Neurology, Virginia Commonwealth University, Richmond, VA, USA
| | | | - Oliver W Sakowitz
- Department of Neurosurgery, Neurosurgery Center Ludwigsburg-Heilbronn, Ludwigsburg, Germany
| | | | - Christian Weimar
- Institute of Medical Informatics, Biometry, and Epidemiology, University Hospital Essen, Essen, Germany
- BDH-Klinik Elzach, Elzach, Germany
| | - Thomas Westermaier
- Department of Neurosurgery, Helios Amper Klinikum Dachau, Dachau, Germany.
- Faculty of Medicine, University of Würzburg, Würzburg, Germany.
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13
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Gabbe BJ, Keeves J, McKimmie A, Gadowski AM, Holland AJ, Semple BD, Young JT, Crowe L, Ownsworth T, Bagg MK, Antonic-Baker A, Hicks AJ, Hill R, Curtis K, Romero L, Ponsford JL, Lannin NA, O'Brien TJ, Cameron PA, Cooper DJ, Rushworth N, Fitzgerald M. The Australian Traumatic Brain Injury Initiative: Systematic Review and Consensus Process to Determine the Predictive Value of Demographic, Injury Event, and Social Characteristics on Outcomes for People With Moderate-Severe Traumatic Brain Injury. J Neurotrauma 2024. [PMID: 38115598 DOI: 10.1089/neu.2023.0461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2023] Open
Abstract
The objective of the Australian Traumatic Brain Injury (AUS-TBI) Initiative is to develop a data dictionary to inform data collection and facilitate prediction of outcomes of people who experience moderate-severe TBI in Australia. The aim of this systematic review was to summarize the evidence of the association between demographic, injury event, and social characteristics with outcomes, in people with moderate-severe TBI, to identify potentially predictive indicators. Standardized searches were implemented across bibliographic databases to March 31, 2022. English-language reports, excluding case series, which evaluated the association between demographic, injury event, and social characteristics, and any clinical outcome in at least 10 patients with moderate-severe TBI were included. Abstracts and full text records were independently screened by at least two reviewers in Covidence. A pre-defined algorithm was used to assign a judgement of predictive value to each observed association. The review findings were discussed with an expert panel to determine the feasibility of incorporation of routine measurement into standard care. The search strategy retrieved 16,685 records; 867 full-length records were screened, and 111 studies included. Twenty-two predictors of 32 different outcomes were identified; 7 were classified as high-level (age, sex, ethnicity, employment, insurance, education, and living situation at the time of injury). After discussion with an expert consensus group, 15 were recommended for inclusion in the data dictionary. This review identified numerous predictors capable of enabling early identification of those at risk for poor outcomes and improved personalization of care through inclusion in routine data collection.
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Affiliation(s)
- Belinda J Gabbe
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
- Health Data Research UK, Swansea University Medical School, Swansea University, Singleton Park, United Kingdom
| | - Jemma Keeves
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
- Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
- Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin School of Population Health, Curtin University, Bentley, WA, Australia
| | - Ancelin McKimmie
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Adelle M Gadowski
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Andrew J Holland
- The Children's Hospital at Westmead Clinical School, Faculty of Medicine and Health, University of Sydney School of Medicine, Westmead, Australia
| | - Bridgette D Semple
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC, Australia
| | - Jesse T Young
- Institute for Mental Health Policy Research, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, Australia
- Clinical Sciences Murdoch Children's Research Institute, Parkville, VIC, Australia
- School of Population and Global Health, The University of Western Australia, Perth, WA, Australia
- Justice Health Group, Curtin School of Population Health, Curtin University, Bentley, WA, Australia
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Louise Crowe
- Clinical Sciences Murdoch Children's Research Institute, Parkville, VIC, Australia
| | - Tamara Ownsworth
- School of Applied Psychology and the Hopkins Centre, Griffith University, Brisbane, Australia
| | - Matthew K Bagg
- Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
- Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin School of Population Health, Curtin University, Bentley, WA, Australia
- Centre for Pain IMPACT, Neuroscience Research Australia, Sydney, NSW, Australia
- School of Health Sciences, University of Notre Dame Australia, Fremantle, WA, Australia
| | - Ana Antonic-Baker
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC, Australia
| | - Amelia J Hicks
- Monash-Epworth Rehabilitation Research Centre, Epworth Healthcare, Melbourne, VIC, Australia
- School of Psychological Sciences, Monash University, Melbourne, VIC, Australia
| | - Regina Hill
- Regina Hill Effective Consulting Pty. Ltd., Melbourne, VIC, Australia
| | - Kate Curtis
- Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW, Australia
- Illawarra Shoalhaven LHD, Wollongong, NSW, Australia
- George Institute for Global Health, Newtown, NSW, Australia
| | | | - Jennie L Ponsford
- Monash-Epworth Rehabilitation Research Centre, Epworth Healthcare, Melbourne, VIC, Australia
- School of Psychological Sciences, Monash University, Melbourne, VIC, Australia
| | - Natasha A Lannin
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC, Australia
- Alfred Health, Melbourne, VIC, Australia
| | - Terence J O'Brien
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC, Australia
| | - Peter A Cameron
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
- National Trauma Research Institute, Melbourne, VIC, Australia
- Emergency and Trauma Centre, The Alfred Hospital, Melbourne, VIC, Australia
| | - D Jamie Cooper
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
- Australian and New Zealand Intensive Care Research Centre, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
- Department of Intensive Care and Hyperbaric Medicine, The Alfred, Melbourne, VIC, Australia
| | | | - Melinda Fitzgerald
- Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
- Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin School of Population Health, Curtin University, Bentley, WA, Australia
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14
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Bath J, Barylak M, Kedda E, Harvey E, Locklear T, Martinez M, Collier B, Weppner J. Timing of withdrawal of life-sustaining therapy in traumatic brain injury: exploring indicators of poor prognosis in adult and geriatric populations. Brain Inj 2024; 38:267-272. [PMID: 38294172 DOI: 10.1080/02699052.2024.2309656] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 01/20/2024] [Indexed: 02/01/2024]
Abstract
OBJECTIVE The lack of objective prognostication tools for severe traumatic brain injury (TBI) causes variability in the application of withdrawal of life-saving treatment (WLST). We aimed to determine whether WLST in persons with severe TBI is associated with known indicators of poor prognosis. METHODS This retrospective descriptive study focused on adult (18-64 years) and geriatric (≥65 years) patients with severe TBI who were admitted between August 1, 2018 and July 31, 2021 at a Level I trauma center and subsequently underwent WLST. The data collected from the Trauma Registry and electronic health records included information regarding demographic characteristics, injury severity, clinical variables, and length of hospital stay and were used to examine the indicators of poor prognosis and WLST. RESULTS Among the 164 participants with TBI who met the inclusion criteria, 61.0% were geriatric, and 122 (74.4%) patients had 0 or only 1 of the poor prognostic indicators prior to WLST. The non-geriatric group had more indicators of poor prognosis than the geriatric group. Participants with fewer indicators of poor prognosis had a longer length-of-stay. CONCLUSION In severe TBI cases, standardized prognostication tools can help guide informed WLST decisions, particularly in geriatric patients, improving care consistency.
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Affiliation(s)
| | - Martin Barylak
- Virginia Tech Carilion School of Medicine, Roanoke, VA, USA
| | - Edward Kedda
- Edward Via College of Osteopathic Medicine, Blacksburg, VA, USA
| | | | | | | | - Bryan Collier
- Carilion Clinic, Roanoke, VA, USA
- Department of Surgery, Virginia Tech Carilion School of Medicine, Roanoke, VA, USA
| | - Justin Weppner
- Carilion Clinic, Roanoke, VA, USA
- Department of Internal Medicine, Virginia Tech Carilion School of Medicine, Roanoke, VA, USA
- Department of Internal Medicine, Edward Via College of Osteopathic Medicine, Blacksburg, VA, USA
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15
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Smith CW, Malhotra AK, Hammill C, Beaton D, Harrington EM, He Y, Shakil H, McFarlan A, Jones B, Lin HM, Mathieu F, Nathens AB, Ackery AD, Mok G, Mamdani M, Mathur S, Wilson JR, Moreland R, Colak E, Witiw CD. Vision Transformer-based Decision Support for Neurosurgical Intervention in Acute Traumatic Brain Injury: Automated Surgical Intervention Support Tool. Radiol Artif Intell 2024; 6:e230088. [PMID: 38197796 PMCID: PMC10982820 DOI: 10.1148/ryai.230088] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 11/15/2023] [Accepted: 12/18/2023] [Indexed: 01/11/2024]
Abstract
Purpose To develop an automated triage tool to predict neurosurgical intervention for patients with traumatic brain injury (TBI). Materials and Methods A provincial trauma registry was reviewed to retrospectively identify patients with TBI from 2005 to 2022 treated at a specialized Canadian trauma center. Model training, validation, and testing were performed using head CT scans with binary reference standard patient-level labels corresponding to whether the patient received neurosurgical intervention. Performance and accuracy of the model, the Automated Surgical Intervention Support Tool for TBI (ASIST-TBI), were also assessed using a held-out consecutive test set of all patients with TBI presenting to the center between March 2021 and September 2022. Results Head CT scans from 2806 patients with TBI (mean age, 57 years ± 22 [SD]; 1955 [70%] men) were acquired between 2005 and 2021 and used for training, validation, and testing. Consecutive scans from an additional 612 patients (mean age, 61 years ± 22; 443 [72%] men) were used to assess the performance of ASIST-TBI. There was accurate prediction of neurosurgical intervention with an area under the receiver operating characteristic curve (AUC) of 0.92 (95% CI: 0.88, 0.94), accuracy of 87% (491 of 562), sensitivity of 87% (196 of 225), and specificity of 88% (295 of 337) on the test dataset. Performance on the held-out test dataset remained robust with an AUC of 0.89 (95% CI: 0.85, 0.91), accuracy of 84% (517 of 612), sensitivity of 85% (199 of 235), and specificity of 84% (318 of 377). Conclusion A novel deep learning model was developed that could accurately predict the requirement for neurosurgical intervention using acute TBI CT scans. Keywords: CT, Brain/Brain Stem, Surgery, Trauma, Prognosis, Classification, Application Domain, Traumatic Brain Injury, Triage, Machine Learning, Decision Support Supplemental material is available for this article. © RSNA, 2024 See also commentary by Haller in this issue.
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Affiliation(s)
| | | | - Christopher Hammill
- From the Division of Neurosurgery (C.W.S., A.K.M., E.M.H., Y.H.,
H.S., J.R.W., C.D.W.), Trauma Program and Quality Assurance (A.M., E.C.),
Department of Emergency Medicine (A.D.A., G.M.), and Department of Medical
Imaging (S.M., R.M., E.C.), St Michael's Hospital, 30 Bond St, Toronto,
ON, Canada M5B 1W8; Li Ka Shing Knowledge Institute (C.W.S., A.K.M., E.M.H.,
Y.H., H.S., H.M.L., M.M., S.M., J.R.W., E.C., C.D.W.) and Data Science and
Advanced Analytics (C.H., D.B., B.J., M.M.), Unity Health Toronto, Toronto,
Ontario, Canada; Institute for Health Policy, Management and Evaluation (A.K.M.,
H.S., M.M., J.R.W., C.D.W.), Interdepartmental Division of Critical Care (F.M.),
Temerty Faculty of Medicine (A.D.A., G.M., M.M., S.M., J.R.W., R.M., C.D.W.),
and Leslie Dan Faculty of Pharmacy (M.M.), University of Toronto, Toronto,
Ontario, Canada; and Division of Trauma Surgery, Sunnybrook Health Sciences
Centre, Toronto, Ontario, Canada (A.B.N.)
| | - Derek Beaton
- From the Division of Neurosurgery (C.W.S., A.K.M., E.M.H., Y.H.,
H.S., J.R.W., C.D.W.), Trauma Program and Quality Assurance (A.M., E.C.),
Department of Emergency Medicine (A.D.A., G.M.), and Department of Medical
Imaging (S.M., R.M., E.C.), St Michael's Hospital, 30 Bond St, Toronto,
ON, Canada M5B 1W8; Li Ka Shing Knowledge Institute (C.W.S., A.K.M., E.M.H.,
Y.H., H.S., H.M.L., M.M., S.M., J.R.W., E.C., C.D.W.) and Data Science and
Advanced Analytics (C.H., D.B., B.J., M.M.), Unity Health Toronto, Toronto,
Ontario, Canada; Institute for Health Policy, Management and Evaluation (A.K.M.,
H.S., M.M., J.R.W., C.D.W.), Interdepartmental Division of Critical Care (F.M.),
Temerty Faculty of Medicine (A.D.A., G.M., M.M., S.M., J.R.W., R.M., C.D.W.),
and Leslie Dan Faculty of Pharmacy (M.M.), University of Toronto, Toronto,
Ontario, Canada; and Division of Trauma Surgery, Sunnybrook Health Sciences
Centre, Toronto, Ontario, Canada (A.B.N.)
| | - Erin M. Harrington
- From the Division of Neurosurgery (C.W.S., A.K.M., E.M.H., Y.H.,
H.S., J.R.W., C.D.W.), Trauma Program and Quality Assurance (A.M., E.C.),
Department of Emergency Medicine (A.D.A., G.M.), and Department of Medical
Imaging (S.M., R.M., E.C.), St Michael's Hospital, 30 Bond St, Toronto,
ON, Canada M5B 1W8; Li Ka Shing Knowledge Institute (C.W.S., A.K.M., E.M.H.,
Y.H., H.S., H.M.L., M.M., S.M., J.R.W., E.C., C.D.W.) and Data Science and
Advanced Analytics (C.H., D.B., B.J., M.M.), Unity Health Toronto, Toronto,
Ontario, Canada; Institute for Health Policy, Management and Evaluation (A.K.M.,
H.S., M.M., J.R.W., C.D.W.), Interdepartmental Division of Critical Care (F.M.),
Temerty Faculty of Medicine (A.D.A., G.M., M.M., S.M., J.R.W., R.M., C.D.W.),
and Leslie Dan Faculty of Pharmacy (M.M.), University of Toronto, Toronto,
Ontario, Canada; and Division of Trauma Surgery, Sunnybrook Health Sciences
Centre, Toronto, Ontario, Canada (A.B.N.)
| | - Yingshi He
- From the Division of Neurosurgery (C.W.S., A.K.M., E.M.H., Y.H.,
H.S., J.R.W., C.D.W.), Trauma Program and Quality Assurance (A.M., E.C.),
Department of Emergency Medicine (A.D.A., G.M.), and Department of Medical
Imaging (S.M., R.M., E.C.), St Michael's Hospital, 30 Bond St, Toronto,
ON, Canada M5B 1W8; Li Ka Shing Knowledge Institute (C.W.S., A.K.M., E.M.H.,
Y.H., H.S., H.M.L., M.M., S.M., J.R.W., E.C., C.D.W.) and Data Science and
Advanced Analytics (C.H., D.B., B.J., M.M.), Unity Health Toronto, Toronto,
Ontario, Canada; Institute for Health Policy, Management and Evaluation (A.K.M.,
H.S., M.M., J.R.W., C.D.W.), Interdepartmental Division of Critical Care (F.M.),
Temerty Faculty of Medicine (A.D.A., G.M., M.M., S.M., J.R.W., R.M., C.D.W.),
and Leslie Dan Faculty of Pharmacy (M.M.), University of Toronto, Toronto,
Ontario, Canada; and Division of Trauma Surgery, Sunnybrook Health Sciences
Centre, Toronto, Ontario, Canada (A.B.N.)
| | - Husain Shakil
- From the Division of Neurosurgery (C.W.S., A.K.M., E.M.H., Y.H.,
H.S., J.R.W., C.D.W.), Trauma Program and Quality Assurance (A.M., E.C.),
Department of Emergency Medicine (A.D.A., G.M.), and Department of Medical
Imaging (S.M., R.M., E.C.), St Michael's Hospital, 30 Bond St, Toronto,
ON, Canada M5B 1W8; Li Ka Shing Knowledge Institute (C.W.S., A.K.M., E.M.H.,
Y.H., H.S., H.M.L., M.M., S.M., J.R.W., E.C., C.D.W.) and Data Science and
Advanced Analytics (C.H., D.B., B.J., M.M.), Unity Health Toronto, Toronto,
Ontario, Canada; Institute for Health Policy, Management and Evaluation (A.K.M.,
H.S., M.M., J.R.W., C.D.W.), Interdepartmental Division of Critical Care (F.M.),
Temerty Faculty of Medicine (A.D.A., G.M., M.M., S.M., J.R.W., R.M., C.D.W.),
and Leslie Dan Faculty of Pharmacy (M.M.), University of Toronto, Toronto,
Ontario, Canada; and Division of Trauma Surgery, Sunnybrook Health Sciences
Centre, Toronto, Ontario, Canada (A.B.N.)
| | - Amanda McFarlan
- From the Division of Neurosurgery (C.W.S., A.K.M., E.M.H., Y.H.,
H.S., J.R.W., C.D.W.), Trauma Program and Quality Assurance (A.M., E.C.),
Department of Emergency Medicine (A.D.A., G.M.), and Department of Medical
Imaging (S.M., R.M., E.C.), St Michael's Hospital, 30 Bond St, Toronto,
ON, Canada M5B 1W8; Li Ka Shing Knowledge Institute (C.W.S., A.K.M., E.M.H.,
Y.H., H.S., H.M.L., M.M., S.M., J.R.W., E.C., C.D.W.) and Data Science and
Advanced Analytics (C.H., D.B., B.J., M.M.), Unity Health Toronto, Toronto,
Ontario, Canada; Institute for Health Policy, Management and Evaluation (A.K.M.,
H.S., M.M., J.R.W., C.D.W.), Interdepartmental Division of Critical Care (F.M.),
Temerty Faculty of Medicine (A.D.A., G.M., M.M., S.M., J.R.W., R.M., C.D.W.),
and Leslie Dan Faculty of Pharmacy (M.M.), University of Toronto, Toronto,
Ontario, Canada; and Division of Trauma Surgery, Sunnybrook Health Sciences
Centre, Toronto, Ontario, Canada (A.B.N.)
| | - Blair Jones
- From the Division of Neurosurgery (C.W.S., A.K.M., E.M.H., Y.H.,
H.S., J.R.W., C.D.W.), Trauma Program and Quality Assurance (A.M., E.C.),
Department of Emergency Medicine (A.D.A., G.M.), and Department of Medical
Imaging (S.M., R.M., E.C.), St Michael's Hospital, 30 Bond St, Toronto,
ON, Canada M5B 1W8; Li Ka Shing Knowledge Institute (C.W.S., A.K.M., E.M.H.,
Y.H., H.S., H.M.L., M.M., S.M., J.R.W., E.C., C.D.W.) and Data Science and
Advanced Analytics (C.H., D.B., B.J., M.M.), Unity Health Toronto, Toronto,
Ontario, Canada; Institute for Health Policy, Management and Evaluation (A.K.M.,
H.S., M.M., J.R.W., C.D.W.), Interdepartmental Division of Critical Care (F.M.),
Temerty Faculty of Medicine (A.D.A., G.M., M.M., S.M., J.R.W., R.M., C.D.W.),
and Leslie Dan Faculty of Pharmacy (M.M.), University of Toronto, Toronto,
Ontario, Canada; and Division of Trauma Surgery, Sunnybrook Health Sciences
Centre, Toronto, Ontario, Canada (A.B.N.)
| | - Hui Ming Lin
- From the Division of Neurosurgery (C.W.S., A.K.M., E.M.H., Y.H.,
H.S., J.R.W., C.D.W.), Trauma Program and Quality Assurance (A.M., E.C.),
Department of Emergency Medicine (A.D.A., G.M.), and Department of Medical
Imaging (S.M., R.M., E.C.), St Michael's Hospital, 30 Bond St, Toronto,
ON, Canada M5B 1W8; Li Ka Shing Knowledge Institute (C.W.S., A.K.M., E.M.H.,
Y.H., H.S., H.M.L., M.M., S.M., J.R.W., E.C., C.D.W.) and Data Science and
Advanced Analytics (C.H., D.B., B.J., M.M.), Unity Health Toronto, Toronto,
Ontario, Canada; Institute for Health Policy, Management and Evaluation (A.K.M.,
H.S., M.M., J.R.W., C.D.W.), Interdepartmental Division of Critical Care (F.M.),
Temerty Faculty of Medicine (A.D.A., G.M., M.M., S.M., J.R.W., R.M., C.D.W.),
and Leslie Dan Faculty of Pharmacy (M.M.), University of Toronto, Toronto,
Ontario, Canada; and Division of Trauma Surgery, Sunnybrook Health Sciences
Centre, Toronto, Ontario, Canada (A.B.N.)
| | - François Mathieu
- From the Division of Neurosurgery (C.W.S., A.K.M., E.M.H., Y.H.,
H.S., J.R.W., C.D.W.), Trauma Program and Quality Assurance (A.M., E.C.),
Department of Emergency Medicine (A.D.A., G.M.), and Department of Medical
Imaging (S.M., R.M., E.C.), St Michael's Hospital, 30 Bond St, Toronto,
ON, Canada M5B 1W8; Li Ka Shing Knowledge Institute (C.W.S., A.K.M., E.M.H.,
Y.H., H.S., H.M.L., M.M., S.M., J.R.W., E.C., C.D.W.) and Data Science and
Advanced Analytics (C.H., D.B., B.J., M.M.), Unity Health Toronto, Toronto,
Ontario, Canada; Institute for Health Policy, Management and Evaluation (A.K.M.,
H.S., M.M., J.R.W., C.D.W.), Interdepartmental Division of Critical Care (F.M.),
Temerty Faculty of Medicine (A.D.A., G.M., M.M., S.M., J.R.W., R.M., C.D.W.),
and Leslie Dan Faculty of Pharmacy (M.M.), University of Toronto, Toronto,
Ontario, Canada; and Division of Trauma Surgery, Sunnybrook Health Sciences
Centre, Toronto, Ontario, Canada (A.B.N.)
| | - Avery B. Nathens
- From the Division of Neurosurgery (C.W.S., A.K.M., E.M.H., Y.H.,
H.S., J.R.W., C.D.W.), Trauma Program and Quality Assurance (A.M., E.C.),
Department of Emergency Medicine (A.D.A., G.M.), and Department of Medical
Imaging (S.M., R.M., E.C.), St Michael's Hospital, 30 Bond St, Toronto,
ON, Canada M5B 1W8; Li Ka Shing Knowledge Institute (C.W.S., A.K.M., E.M.H.,
Y.H., H.S., H.M.L., M.M., S.M., J.R.W., E.C., C.D.W.) and Data Science and
Advanced Analytics (C.H., D.B., B.J., M.M.), Unity Health Toronto, Toronto,
Ontario, Canada; Institute for Health Policy, Management and Evaluation (A.K.M.,
H.S., M.M., J.R.W., C.D.W.), Interdepartmental Division of Critical Care (F.M.),
Temerty Faculty of Medicine (A.D.A., G.M., M.M., S.M., J.R.W., R.M., C.D.W.),
and Leslie Dan Faculty of Pharmacy (M.M.), University of Toronto, Toronto,
Ontario, Canada; and Division of Trauma Surgery, Sunnybrook Health Sciences
Centre, Toronto, Ontario, Canada (A.B.N.)
| | - Alun D. Ackery
- From the Division of Neurosurgery (C.W.S., A.K.M., E.M.H., Y.H.,
H.S., J.R.W., C.D.W.), Trauma Program and Quality Assurance (A.M., E.C.),
Department of Emergency Medicine (A.D.A., G.M.), and Department of Medical
Imaging (S.M., R.M., E.C.), St Michael's Hospital, 30 Bond St, Toronto,
ON, Canada M5B 1W8; Li Ka Shing Knowledge Institute (C.W.S., A.K.M., E.M.H.,
Y.H., H.S., H.M.L., M.M., S.M., J.R.W., E.C., C.D.W.) and Data Science and
Advanced Analytics (C.H., D.B., B.J., M.M.), Unity Health Toronto, Toronto,
Ontario, Canada; Institute for Health Policy, Management and Evaluation (A.K.M.,
H.S., M.M., J.R.W., C.D.W.), Interdepartmental Division of Critical Care (F.M.),
Temerty Faculty of Medicine (A.D.A., G.M., M.M., S.M., J.R.W., R.M., C.D.W.),
and Leslie Dan Faculty of Pharmacy (M.M.), University of Toronto, Toronto,
Ontario, Canada; and Division of Trauma Surgery, Sunnybrook Health Sciences
Centre, Toronto, Ontario, Canada (A.B.N.)
| | - Garrick Mok
- From the Division of Neurosurgery (C.W.S., A.K.M., E.M.H., Y.H.,
H.S., J.R.W., C.D.W.), Trauma Program and Quality Assurance (A.M., E.C.),
Department of Emergency Medicine (A.D.A., G.M.), and Department of Medical
Imaging (S.M., R.M., E.C.), St Michael's Hospital, 30 Bond St, Toronto,
ON, Canada M5B 1W8; Li Ka Shing Knowledge Institute (C.W.S., A.K.M., E.M.H.,
Y.H., H.S., H.M.L., M.M., S.M., J.R.W., E.C., C.D.W.) and Data Science and
Advanced Analytics (C.H., D.B., B.J., M.M.), Unity Health Toronto, Toronto,
Ontario, Canada; Institute for Health Policy, Management and Evaluation (A.K.M.,
H.S., M.M., J.R.W., C.D.W.), Interdepartmental Division of Critical Care (F.M.),
Temerty Faculty of Medicine (A.D.A., G.M., M.M., S.M., J.R.W., R.M., C.D.W.),
and Leslie Dan Faculty of Pharmacy (M.M.), University of Toronto, Toronto,
Ontario, Canada; and Division of Trauma Surgery, Sunnybrook Health Sciences
Centre, Toronto, Ontario, Canada (A.B.N.)
| | - Muhammad Mamdani
- From the Division of Neurosurgery (C.W.S., A.K.M., E.M.H., Y.H.,
H.S., J.R.W., C.D.W.), Trauma Program and Quality Assurance (A.M., E.C.),
Department of Emergency Medicine (A.D.A., G.M.), and Department of Medical
Imaging (S.M., R.M., E.C.), St Michael's Hospital, 30 Bond St, Toronto,
ON, Canada M5B 1W8; Li Ka Shing Knowledge Institute (C.W.S., A.K.M., E.M.H.,
Y.H., H.S., H.M.L., M.M., S.M., J.R.W., E.C., C.D.W.) and Data Science and
Advanced Analytics (C.H., D.B., B.J., M.M.), Unity Health Toronto, Toronto,
Ontario, Canada; Institute for Health Policy, Management and Evaluation (A.K.M.,
H.S., M.M., J.R.W., C.D.W.), Interdepartmental Division of Critical Care (F.M.),
Temerty Faculty of Medicine (A.D.A., G.M., M.M., S.M., J.R.W., R.M., C.D.W.),
and Leslie Dan Faculty of Pharmacy (M.M.), University of Toronto, Toronto,
Ontario, Canada; and Division of Trauma Surgery, Sunnybrook Health Sciences
Centre, Toronto, Ontario, Canada (A.B.N.)
| | - Shobhit Mathur
- From the Division of Neurosurgery (C.W.S., A.K.M., E.M.H., Y.H.,
H.S., J.R.W., C.D.W.), Trauma Program and Quality Assurance (A.M., E.C.),
Department of Emergency Medicine (A.D.A., G.M.), and Department of Medical
Imaging (S.M., R.M., E.C.), St Michael's Hospital, 30 Bond St, Toronto,
ON, Canada M5B 1W8; Li Ka Shing Knowledge Institute (C.W.S., A.K.M., E.M.H.,
Y.H., H.S., H.M.L., M.M., S.M., J.R.W., E.C., C.D.W.) and Data Science and
Advanced Analytics (C.H., D.B., B.J., M.M.), Unity Health Toronto, Toronto,
Ontario, Canada; Institute for Health Policy, Management and Evaluation (A.K.M.,
H.S., M.M., J.R.W., C.D.W.), Interdepartmental Division of Critical Care (F.M.),
Temerty Faculty of Medicine (A.D.A., G.M., M.M., S.M., J.R.W., R.M., C.D.W.),
and Leslie Dan Faculty of Pharmacy (M.M.), University of Toronto, Toronto,
Ontario, Canada; and Division of Trauma Surgery, Sunnybrook Health Sciences
Centre, Toronto, Ontario, Canada (A.B.N.)
| | - Jefferson R. Wilson
- From the Division of Neurosurgery (C.W.S., A.K.M., E.M.H., Y.H.,
H.S., J.R.W., C.D.W.), Trauma Program and Quality Assurance (A.M., E.C.),
Department of Emergency Medicine (A.D.A., G.M.), and Department of Medical
Imaging (S.M., R.M., E.C.), St Michael's Hospital, 30 Bond St, Toronto,
ON, Canada M5B 1W8; Li Ka Shing Knowledge Institute (C.W.S., A.K.M., E.M.H.,
Y.H., H.S., H.M.L., M.M., S.M., J.R.W., E.C., C.D.W.) and Data Science and
Advanced Analytics (C.H., D.B., B.J., M.M.), Unity Health Toronto, Toronto,
Ontario, Canada; Institute for Health Policy, Management and Evaluation (A.K.M.,
H.S., M.M., J.R.W., C.D.W.), Interdepartmental Division of Critical Care (F.M.),
Temerty Faculty of Medicine (A.D.A., G.M., M.M., S.M., J.R.W., R.M., C.D.W.),
and Leslie Dan Faculty of Pharmacy (M.M.), University of Toronto, Toronto,
Ontario, Canada; and Division of Trauma Surgery, Sunnybrook Health Sciences
Centre, Toronto, Ontario, Canada (A.B.N.)
| | - Robert Moreland
- From the Division of Neurosurgery (C.W.S., A.K.M., E.M.H., Y.H.,
H.S., J.R.W., C.D.W.), Trauma Program and Quality Assurance (A.M., E.C.),
Department of Emergency Medicine (A.D.A., G.M.), and Department of Medical
Imaging (S.M., R.M., E.C.), St Michael's Hospital, 30 Bond St, Toronto,
ON, Canada M5B 1W8; Li Ka Shing Knowledge Institute (C.W.S., A.K.M., E.M.H.,
Y.H., H.S., H.M.L., M.M., S.M., J.R.W., E.C., C.D.W.) and Data Science and
Advanced Analytics (C.H., D.B., B.J., M.M.), Unity Health Toronto, Toronto,
Ontario, Canada; Institute for Health Policy, Management and Evaluation (A.K.M.,
H.S., M.M., J.R.W., C.D.W.), Interdepartmental Division of Critical Care (F.M.),
Temerty Faculty of Medicine (A.D.A., G.M., M.M., S.M., J.R.W., R.M., C.D.W.),
and Leslie Dan Faculty of Pharmacy (M.M.), University of Toronto, Toronto,
Ontario, Canada; and Division of Trauma Surgery, Sunnybrook Health Sciences
Centre, Toronto, Ontario, Canada (A.B.N.)
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16
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Malhotra AK, Shakil H, Smith CW, Sader N, Ladha K, Wijeysundera DN, Singhal A, Kulkarni AV, Wilson JR, Witiw CD, Nathens AB. Withdrawal of Life-Sustaining Treatment for Pediatric Patients With Severe Traumatic Brain Injury. JAMA Surg 2024; 159:287-296. [PMID: 38117514 PMCID: PMC10733846 DOI: 10.1001/jamasurg.2023.6531] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Accepted: 09/13/2023] [Indexed: 12/21/2023]
Abstract
Importance The decision to withdraw life-sustaining treatment for pediatric patients with severe traumatic brain injury (TBI) is challenging for clinicians and families with limited evidence quantifying existing practices. Given the lack of standardized clinical guidelines, variable practice patterns across trauma centers seem likely. Objective To evaluate the factors influencing decisions to withdraw life-sustaining treatment across North American trauma centers for pediatric patients with severe TBI and to quantify any existing between-center variability in withdrawal of life-sustaining treatment practices. Design, Setting, and Participants This retrospective cohort study used data collected from 515 trauma centers through the American College of Surgeons Trauma Quality Improvement Program between 2017 and 2020. Pediatric patients younger than 19 years with severe TBI and a documented decision for withdrawal of life-sustaining treatment were included. Data were analyzed from January to May 2023. Main Outcomes and Measures A random intercept multilevel logistic regression model was used to quantify patient, injury, and hospital characteristics associated with the decision to withdraw life-sustaining treatment; the median odds ratio was used to characterize residual between-center variability. Centers were ranked by their conditional random intercepts and quartile-specific adjusted mortalities were computed. Results A total of 9803 children (mean [SD] age, 12.6 [5.7]; 2920 [29.8%] female) with severe TBI were identified, 1003 of whom (10.2%) had a documented decision to withdraw life-sustaining treatment. Patient-level factors associated with an increase in likelihood of withdrawal of life-sustaining treatment were young age (younger than 3 years), higher severity intracranial and extracranial injuries, and mechanism of injury related to firearms. Following adjustment for patient and hospital attributes, the median odds ratio was 1.54 (95% CI, 1.46-1.62), suggesting residual variation in withdrawal of life-sustaining treatment between centers. When centers were grouped into quartiles by their propensity for withdrawal of life-sustaining treatment, adjusted mortality was higher for fourth-quartile compared to first-quartile centers (odds ratio, 1.66; 95% CI, 1.45-1.88). Conclusions and Relevance Several patient and injury factors were associated with withdrawal of life-sustaining treatment decision-making for pediatric patients with severe TBI in this study. Variation in withdrawal of life-sustaining treatment practices between trauma centers was observed after adjustment for case mix; this variation was associated with differences in risk-adjusted mortality rates. Taken together, these findings highlight the presence of inconsistent approaches to withdrawal of life-sustaining treatment in children, which speaks to the need for guidelines to address this significant practice pattern variation.
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Affiliation(s)
- Armaan K. Malhotra
- Division of Neurosurgery, Unity Health, Toronto, Ontario, Canada
- Li Ka Shing Knowledge Institute, Unity Health, Toronto, Ontario, Canada
- Institute for Health Policy, Management and Evaluation, University of Toronto, Ontario, Canada
| | - Husain Shakil
- Division of Neurosurgery, Unity Health, Toronto, Ontario, Canada
- Li Ka Shing Knowledge Institute, Unity Health, Toronto, Ontario, Canada
- Institute for Health Policy, Management and Evaluation, University of Toronto, Ontario, Canada
| | - Christopher W. Smith
- Division of Neurosurgery, Unity Health, Toronto, Ontario, Canada
- Li Ka Shing Knowledge Institute, Unity Health, Toronto, Ontario, Canada
| | - Nicholas Sader
- Division of Neurosurgery, Foothills Medical Center, University of Calgary, Calgary, Alberta, Canada
| | - Karim Ladha
- Li Ka Shing Knowledge Institute, Unity Health, Toronto, Ontario, Canada
- Institute for Health Policy, Management and Evaluation, University of Toronto, Ontario, Canada
- Division of Anesthesiology, Unity Health, Toronto, Ontario, Canada
| | - Duminda N. Wijeysundera
- Li Ka Shing Knowledge Institute, Unity Health, Toronto, Ontario, Canada
- Institute for Health Policy, Management and Evaluation, University of Toronto, Ontario, Canada
- Division of Anesthesiology, Unity Health, Toronto, Ontario, Canada
| | - Ashutosh Singhal
- Division of Neurosurgery, British Columbia Children’s Hospital, Vancouver, British Columbia, Canada
| | - Abhaya V. Kulkarni
- Institute for Health Policy, Management and Evaluation, University of Toronto, Ontario, Canada
- Division of Neurosurgery, Hospital for Sick Children, Toronto, Ontario, Canada
| | - Jefferson R. Wilson
- Division of Neurosurgery, Unity Health, Toronto, Ontario, Canada
- Li Ka Shing Knowledge Institute, Unity Health, Toronto, Ontario, Canada
- Institute for Health Policy, Management and Evaluation, University of Toronto, Ontario, Canada
| | - Christopher D. Witiw
- Division of Neurosurgery, Unity Health, Toronto, Ontario, Canada
- Li Ka Shing Knowledge Institute, Unity Health, Toronto, Ontario, Canada
- Institute for Health Policy, Management and Evaluation, University of Toronto, Ontario, Canada
| | - Avery B. Nathens
- Institute for Health Policy, Management and Evaluation, University of Toronto, Ontario, Canada
- Division of General Surgery, Sunnybrook Health Sciences Center, Toronto, Ontario, Canada
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17
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Boerwinkle VL, Manjón I, Sussman BL, McGary A, Mirea L, Gillette K, Broman-Fulks J, Cediel EG, Arhin M, Hunter SE, Wyckoff SN, Allred K, Tom D. Resting-State Functional Magnetic Resonance Imaging Network Association With Mortality, Epilepsy, Cognition, and Motor Two-Year Outcomes in Suspected Severe Neonatal Acute Brain Injury. Pediatr Neurol 2024; 152:41-55. [PMID: 38198979 DOI: 10.1016/j.pediatrneurol.2023.12.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 11/14/2023] [Accepted: 12/06/2023] [Indexed: 01/12/2024]
Abstract
BACKGROUND AND OBJECTIVES In acute brain injury of neonates, resting-state functional magnetic resonance imaging (MRI) (RS) showed incremental association with consciousness, mortality, cognitive and motor development, and epilepsy, with correction for multiple comparisons, at six months postgestation in neonates with suspected acute brain injury (ABI). However, there are relatively few developmental milestones at six months to benchmark against, thus, we extended this cohort study to evaluate two-year outcomes. METHODS In 40 consecutive neonates with ABI and RS, ordinal scores of resting-state networks; MRI, magnetic resonance spectroscopy, and electroencephalography; and up to 42-month outcomes of mortality, general and motor development, Pediatric Cerebral Performance Category Scale (PCPC), and epilepsy informed associations between tests and outcomes. RESULTS Mean gestational age was 37.8 weeks, 68% were male, and 60% had hypoxic-ischemic encephalopathy. Three died in-hospital, four at six to 42 months, and five were lost to follow-up. Associations included basal ganglia network with PCPC (P = 0.0003), all-mortality (P = 0.005), and motor (P = 0.0004); language/frontoparietal network with developmental delay (P = 0.009), PCPC (P = 0.006), and all-mortality (P = 0.01); default mode network with developmental delay (P = 0.003), PCPC (P = 0.004), neonatal intensive care unit mortality (P = 0.01), and motor (P = 0.009); RS seizure onset zone with epilepsy (P = 0.01); and anatomic MRI with epilepsy (P = 0.01). CONCLUSION For the first time, at any age, resting state functional MRI in ABI is associated with long-term epilepsy and RSNs predicted mortality in neonates. Severity of RSN abnormality was associated with incrementally worsened neurodevelopment including cognition, language, and motor function over two years.
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Affiliation(s)
- Varina L Boerwinkle
- Division of Child Neurology, University of North Carolina Medical School, Chapel Hill, North Carolina.
| | - Iliana Manjón
- University of Arizona College of Medicine - Tucson, Tucson, Arizona
| | - Bethany L Sussman
- Division of Neuroscience Research, Barrow Neurological Institute at Phoenix Children's Hospital, Phoenix, Arizona
| | - Alyssa McGary
- Department of Clinical Research, Phoenix Children's Hospital, Phoenix, Arizona
| | - Lucia Mirea
- Department of Clinical Research, Phoenix Children's Hospital, Phoenix, Arizona
| | - Kirsten Gillette
- Division of Child Neurology, University of North Carolina Medical School, Chapel Hill, North Carolina
| | - Jordan Broman-Fulks
- Division of Child Neurology, University of North Carolina Medical School, Chapel Hill, North Carolina
| | - Emilio G Cediel
- Division of Child Neurology, University of North Carolina Medical School, Chapel Hill, North Carolina
| | - Martin Arhin
- Division of Child Neurology, University of North Carolina Medical School, Chapel Hill, North Carolina
| | - Senyene E Hunter
- Division of Child Neurology, University of North Carolina Medical School, Chapel Hill, North Carolina
| | - Sarah N Wyckoff
- Division of Neuroscience Research, Barrow Neurological Institute at Phoenix Children's Hospital, Phoenix, Arizona
| | - Kimberlee Allred
- Division of Neonatology, Phoenix Children's Hospital, Phoenix, Arizona
| | - Deborah Tom
- Division of Neonatology, Phoenix Children's Hospital, Phoenix, Arizona
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18
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Roohollahi F, Molavi S, Mohammadi M, Mohamadi M, Mohammadi A, Kankam SB, Farahbakhsh F, Moarrefdezfouli A, Peters ME, Albrecht JS, Gardner RC, Rahimi-Movaghar V. Prognostic Value of Frailty for Outcome Following Traumatic Brain Injury: A Systematic Review and Meta-Analysis. J Neurotrauma 2024; 41:331-348. [PMID: 37416987 DOI: 10.1089/neu.2023.0176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/08/2023] Open
Abstract
Frailty is a known predictor of negative health outcomes. The role of frailty in predicting outcomes after traumatic brain injury (TBI), however, is unclear. This systematic review aimed to evaluate the association between frailty and adverse outcomes in patients with TBI. We identified relevant articles that investigated the relationship between frailty and outcomes in patients with TBI by searching PubMed/MEDLINE, Web of Science, Scopus, and EMBASE from inception until 23 March 2023. To evaluate the risk of bias in the included studies, we utilized the Newcastle-Ottawa Scale (NOS). In addition, quantitative synthesis and meta-analyses were performed. We identified 12 studies that met our inclusion criteria; three were prospective. Of included studies, eight had low risk, three had moderate risk, and one had high risk of bias. Frailty was significantly associated with death in five studies, with an increased risk of in-hospital death and complications observed in frail patients. Frailty was associated with longer hospital stays and unfavorable outcome measured by the Extended Glasgow Outcome Scale (GOSE) in four studies. The meta-analysis found that higher frailty significantly increased the odds of non-routine discharge and unfavorable outcome as measured by GOSE scores of 4 or lower. The pooled odds ratio (OR) for non-routine discharge, was 1.80, with a 95% confidence interval (CI) of 1.15-2.84; and for unfavorable outcome, it was 1.91, with a 95% CI of 1.09-3.36. The analysis, however, did not find a significant predictive role for frailty on death (30-day or in-hospital death). The OR for higher frailty and death was 1.42 with a 95% CI of 0.92-2.19. Frailty should be considered in the evaluation of patients with TBI to identify those who may be at increased risk of negative outcomes.
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Affiliation(s)
- Faramarz Roohollahi
- Department of Neurosurgery, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
- Spine Center of Excellence , Yas Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Shervin Molavi
- Department of Neurosurgery, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Mobin Mohamadi
- School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Aynaz Mohammadi
- School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Samuel Berchi Kankam
- Department of Neurosurgery, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
- Spine Center of Excellence , Yas Hospital, Tehran University of Medical Sciences, Tehran, Iran
- Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Farzin Farahbakhsh
- Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Azin Moarrefdezfouli
- Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Matthew E Peters
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, Maryland, USA
| | - Jennifer S Albrecht
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Raquel C Gardner
- Department of Neurology, University of California San Francisco, San Francisco, California, USA
| | - Vafa Rahimi-Movaghar
- Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran
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Vlachos S, Rubenfeld G, Menon D, Harrison D, Rowan K, Maharaj R. Early and late withdrawal of life-sustaining treatment after out-of-hospital cardiac arrest in the United Kingdom: Institutional variation and association with hospital mortality. Resuscitation 2023; 193:109956. [PMID: 37661013 DOI: 10.1016/j.resuscitation.2023.109956] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 08/23/2023] [Accepted: 08/24/2023] [Indexed: 09/05/2023]
Abstract
AIM Frequency and timing of Withdrawal of Life-Sustaining Treatment (WLST) after Out-of-Hospital Cardiac Arrest (OHCA) vary across Intensive Care Units (ICUs) in the United Kingdom (UK) and may be a marker of lower healthcare quality if instituted too frequently or too early. We aimed to describe WLST practice, quantify its variability across UK ICUs, and assess the effect of institutional deviation from average practice on patients' risk-adjusted hospital mortality. METHODS We conducted a retrospective multi-centre cohort study including all adult patients admitted after OHCA to UK ICUs between 2010 and 2017. We identified patient and ICU characteristics associated with early (within 72 h) and late (>72 h) WLST and quantified the between-ICU variation. We used the ICU-level observed-to-expected (O/E) ratios of early and late-WLST frequency as separate metrics of institutional deviation from average practice and calculated their association with patients' hospital mortality. RESULTS We included 28,438 patients across 204 ICUs. 10,775 (37.9%) had WLST and 6397 (59.4%) of them had early-WLST. Both WLST types were strongly associated with patient-level demographics and pre-existing conditions but weakly with ICU-level characteristics. After adjustment, we found unexplained between-ICU variation for both early-WLST (Median Odds Ratio 1.59, 95%CrI 1.49-1.71) and late-WLST (MOR 1.39, 95%CrI 1.31-1.50). Importantly, patients' hospital mortality was higher in ICUs with higher O/E ratio of early-WLST (OR 1.29, 95%CI 1.21-1.38, p < 0.001) or late-WLST (OR 1.39, 95%CI 1.31-1.48, p < 0.001). CONCLUSIONS Significant variability exists between UK ICUs in WLST frequency and timing. This matters because unexplained higher-than-expected WLST frequency is associated with higher hospital mortality independently of timing, potentially signalling prognostic pessimism and lower healthcare quality.
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Affiliation(s)
- Savvas Vlachos
- King's College London, School of Cardio-Vascular Medicine and Sciences, Strand, London WC2R 2LS, UK.
| | - Gordon Rubenfeld
- University of Toronto, Interdepartmental Division of Critical Care, ON M5S Toronto, Ontario, Canada
| | - David Menon
- University of Cambridge, Department of Medicine, CB2 1TN Cambridge, UK
| | - David Harrison
- Intensive Care National Audit & Research Centre, Department of Statistics, WC1V 6AZ London, UK
| | - Kathryn Rowan
- National Institute for Health and Care Research, W1T 7HA London, UK
| | - Ritesh Maharaj
- London School of Economics and Political Science, Department of Health Policy and Health Economics, WC2A 2AE London, UK
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20
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Shakil H, Malhotra AK, Jaffe RH, Smith CW, Harrington EM, Wang AP, Yuan EY, He Y, Ladha K, Wijeysundera DN, Nathens AB, Wilson JR, Witiw CD. Factors influencing withdrawal of life-supporting treatment in cervical spinal cord injury: a large multicenter observational cohort study. Crit Care 2023; 27:448. [PMID: 37980485 PMCID: PMC10656773 DOI: 10.1186/s13054-023-04725-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Accepted: 11/08/2023] [Indexed: 11/20/2023] Open
Abstract
BACKGROUND Traumatic spinal cord injury (SCI) leads to profound neurologic sequelae, and the provision of life-supporting treatment serves great importance among this patient population. The decision for withdrawal of life-supporting treatment (WLST) in complete traumatic SCI is complex with the lack of guidelines and limited understanding of practice patterns. We aimed to evaluate the individual and contextual factors associated with the decision for WLST and assess between-center differences in practice patterns across North American trauma centers for patients with complete cervical SCI. METHODS This retrospective multicenter observational cohort study utilized data derived from the American College of Surgeons Trauma Quality Improvement Program database between 2017 and 2020. The study included adult patients (> 16 years) with complete cervical SCI. We constructed a multilevel mixed effect logistic regression model to adjust for patient, injury and hospital factors influencing WLST. Factors associated with WLST were estimated through odds ratios with 95% confidence intervals. Hospital variability was characterized using the median odds ratio. Unexplained residual variability was assessed through the proportional change in variation between models. RESULTS We identified 5070 patients with complete cervical SCI treated across 477 hospitals, of which 960 (18.9%) had WLST. Patient-level factors associated with significantly increased likelihood of WLST were advanced age, male sex, white race, prior dementia, low presenting Glasgow Coma Scale score, having a pre-hospital cardiac arrest, SCI level of C3 or above, and concurrent severe injury to the head or thorax. Patient-level factors associated with significantly decreased likelihood of WLST included being racially Black or Asian. There was significant variability across hospitals in the likelihood for WLST while accounting for case-mix, hospital size, and teaching status (MOR 1.51 95% CI 1.22-1.75). CONCLUSIONS A notable proportion of patients with complete cervical SCI undergo WLST during their in-hospital admission. We have highlighted several factors associated with this decision and identified considerable variability between hospitals. Further work to standardize WLST guidelines may improve equity of care provided to this patient population.
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Affiliation(s)
- Husain Shakil
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada
- Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Armaan K Malhotra
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada
- Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Rachael H Jaffe
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada
- Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Christopher W Smith
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada
| | - Erin M Harrington
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada
| | - Alick P Wang
- Division of Neurosurgery, Department of Surgery, University of Ottawa, Ottawa, ON, Canada
| | - Eva Y Yuan
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada
| | - Yingshi He
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada
| | - Karim Ladha
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada
- Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, ON, Canada
- Department of Anesthesia, St. Michael's Hospital, Toronto, ON, Canada
- Department of Anesthesiology and Pain Medicine, University of Toronto, Toronto, ON, Canada
| | - Duminda N Wijeysundera
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada
- Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, ON, Canada
- Department of Anesthesia, St. Michael's Hospital, Toronto, ON, Canada
- Department of Anesthesiology and Pain Medicine, University of Toronto, Toronto, ON, Canada
| | - Avery B Nathens
- Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, ON, Canada
- Division of Trauma Surgery, Sunnybrook Health Sciences Center, Toronto, ON, Canada
| | - Jefferson R Wilson
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada
- Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Christopher D Witiw
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada.
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada.
- Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, ON, Canada.
- Division of Neurosurgery, Department of Surgery, St. Michael's Hospital, 30 Bond Street, Toronto, ON, M5B 1W8, Canada.
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Mitchell T, Williamson T. Caring for Ourselves, Supporting Anti-Racist Programming in Medicine. Am J Lifestyle Med 2023; 17:799-802. [PMID: 38511121 PMCID: PMC10948921 DOI: 10.1177/15598276221131296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/22/2024] Open
Abstract
Healthcare disparities and racism are finally being addressed in medical education. Medical schools are working to implement anti-racist programming; however, this can have a negative impact on the mental health of doctors and medical students of color. Continually hearing about people of one's racial group suffering from inequity can have a negative personal and performance impact. Specifically, providers of color want to be a part of the anti-racist movement, but it takes a toll on their mental and emotional wellbeing in the process. Through the support of their respective institutions, it is important for these providers to prioritize self-care such as engaging in physical activity, coaching and therapy. By caring for themselves in and outside of the work environment, providers of color will be better able to fight for anti-racism in healthcare. In this essay, we discuss the importance of health disparity education, challenges in implementing successful healthcare disparity curricula, and possible solutions to support providers and trainees of color.
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Affiliation(s)
- Taylor Mitchell
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA (TM, TW); and Department of Bioethics Center, Harvard Medical School, Boston, MA, USA (TM, TW)
| | - Theresa Williamson
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA (TM, TW); and Department of Bioethics Center, Harvard Medical School, Boston, MA, USA (TM, TW)
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22
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Pokrzywa CJ, Al Tannir AH, Sparapani R, Rabas MS, Holena D, Murphy PB, Creutzfeldt CJ, Somberg L, Nattinger A, Morris RS. The Variation of Withdrawal of Life Sustaining Therapy in Older Adults With Traumatic Brain Injury. J Surg Res 2023; 291:34-42. [PMID: 37331190 DOI: 10.1016/j.jss.2023.05.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 05/11/2023] [Accepted: 05/18/2023] [Indexed: 06/20/2023]
Abstract
INTRODUCTION The decision to withdraw life sustaining treatment (WDLST) in older adults with traumatic brain injury is subject to wide variability leading to nonbeneficial interventions and unnecessary use of hospital resources. We hypothesized that patient and hospital factors are associated with WDLST and WDLST timing. METHODS All traumatic brain injury patients ≥65 with Glasgow coma scores (GCS) of 4-11 from 2018 to 2019 at level I and II centers were selected from the National Trauma Data Bank. Patients with head abbreviated injury scores 5-6 or death within 24 h were excluded. Bayesian additive regression tree analysis was performed to identify the cumulative incidence function (CIF) and the relative risks (RR) over time for withdrawal of care, discharge to hospice (DH), and death. Death alone (no WDLST or DH) served as the comparator group for all analyses. A subanalysis of the composite outcome WDLST/DH (defined as end-of-life-care), with death (no WDLST or DH) as a comparator cohort was performed. RESULTS We included 2126 patients, of whom 1957 (57%) underwent WDLST, 402 (19%) died, and 469 (22%) were DH. 60% of patients were male, and the mean age was 80 y. The majority of patients were injured by fall (76%, n = 1644). Patients who were DH were more often female (51% DH versus 39% WDLST), had a past medical history of dementia (45% DH versus 18% WDLST), and had lower admission injury severity score (14 DH versus 18.6 WDLST) (P < 0.001). Compared to those who DH, those who underwent WDLST had a lower GCS (9.8 versus 8.4, P < 0.001). CIF of WDSLT and DH increased with age, stabilizing by day 3. At day 3, patients ≥90 y had an increased RR of DH compared to WDLST (RR 2.5 versus 1.4). As GCS increased, CIF and RR of WDLST decreased, while CIF and RR of DH increased (RR on day 3 for GCS 12: WDLST 0.42 versus DH 1.31).Patients at nonprofit institutions were more likely to undergo WDLST (RR 1.15) compared to DH (0.68). Compared to patients of White race, patients of Black race had a lower RR of WDLST at all timepoints. CONCLUSIONS Patient and hospital factors influence the practice of end-of-life-care (WDLST, DH, and death), highlighting the need to better understand variability to target palliative care interventions and standardize care across populations and trauma centers.
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Affiliation(s)
| | | | - Rodney Sparapani
- Division of Biostatistics, Department of Institute for Health and Equity, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Mackenzie S Rabas
- Department of Surgery, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Daniel Holena
- Department of Surgery, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Patrick B Murphy
- Department of Surgery, Medical College of Wisconsin, Milwaukee, Wisconsin
| | | | - Lewis Somberg
- Department of Surgery, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Ann Nattinger
- Department of Medicine, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Rachel S Morris
- Department of Surgery, Medical College of Wisconsin, Milwaukee, Wisconsin.
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23
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Lissak IA, Edlow BL, Rosenthal E, Young MJ. Ethical Considerations in Neuroprognostication Following Acute Brain Injury. Semin Neurol 2023; 43:758-767. [PMID: 37802121 DOI: 10.1055/s-0043-1775597] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/08/2023]
Abstract
Neuroprognostication following acute brain injury (ABI) is a complex process that involves integrating vast amounts of information to predict a patient's likely trajectory of neurologic recovery. In this setting, critically evaluating salient ethical questions is imperative, and the implications often inform high-stakes conversations about the continuation, limitation, or withdrawal of life-sustaining therapy. While neuroprognostication is central to these clinical "life-or-death" decisions, the ethical underpinnings of neuroprognostication itself have been underexplored for patients with ABI. In this article, we discuss the ethical challenges of individualized neuroprognostication including parsing and communicating its inherent uncertainty to surrogate decision-makers. We also explore the population-based ethical considerations that arise in the context of heterogenous prognostication practices. Finally, we examine the emergence of artificial intelligence-aided neuroprognostication, proposing an ethical framework relevant to both modern and longstanding prognostic tools.
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Affiliation(s)
- India A Lissak
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Brian L Edlow
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
| | - Eric Rosenthal
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Michael J Young
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
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Goss A, Ge C, Crawford S, Goostrey K, Buddadhumaruk P, Hough CL, Lo B, Carson S, Steingrub J, White DB, Muehlschlegel S. Prognostic Language in Critical Neurologic Illness: A Multicenter Mixed-Methods Study. Neurology 2023; 101:e558-e569. [PMID: 37290972 PMCID: PMC10401677 DOI: 10.1212/wnl.0000000000207462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 04/13/2023] [Indexed: 06/10/2023] Open
Abstract
BACKGROUND AND OBJECTIVES There are no evidence-based guidelines for discussing prognosis in critical neurologic illness, but in general, experts recommend that clinicians communicate prognosis using estimates, such as numerical or qualitative expressions of risk. Little is known about how real-world clinicians communicate prognosis in critical neurologic illness. Our primary objective was to characterize prognostic language clinicians used in critical neurologic illness. We additionally explored whether prognostic language differed between prognostic domains (e.g., survival, cognition). METHODS We conducted a multicenter cross-sectional mixed-methods study analyzing deidentified transcripts of audio-recorded clinician-family meetings for patients with neurologic illness requiring intensive care (e.g., intracerebral hemorrhage, traumatic brain injury, severe stroke) from 7 US centers. Two coders assigned codes for prognostic language type and domain of prognosis to each clinician prognostic statement. Prognostic language was coded as probabilistic (estimating the likelihood of an outcome occurring, e.g., "80% survival"; "She'll probably survive") or nonprobabilistic (characterizing outcomes without offering likelihood; e.g., "She may not survive"). We applied univariate and multivariate binomial logistic regression to examine independent associations between prognostic language and domain of prognosis. RESULTS We analyzed 43 clinician-family meetings for 39 patients with 78 surrogates and 27 clinicians. Clinicians made 512 statements about survival (median 0/meeting [interquartile range (IQR) 0-2]), physical function (median 2 [IQR 0-7]), cognition (median 2 [IQR 0-6]), and overall recovery (median 2 [IQR 1-4]). Most statements were nonprobabilistic (316/512 [62%]); 10 of 512 prognostic statements (2%) offered numeric estimates; and 21% (9/43) of family meetings only contained nonprobabilistic language. Compared with statements about cognition, statements about survival (odds ratio [OR] 2.50, 95% CI 1.01-6.18, p = 0.048) and physical function (OR 3.22, 95% 1.77-5.86, p < 0.001) were more frequently probabilistic. Statements about physical function were less likely to be uncertainty-based than statements about cognition (OR 0.34, 95% CI 0.17-0.66, p = 0.002). DISCUSSION Clinicians preferred not to use estimates (either numeric or qualitative) when discussing critical neurologic illness prognosis, especially when they discussed cognitive outcomes. These findings may inform interventions to improve prognostic communication in critical neurologic illness.
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Affiliation(s)
- Adeline Goss
- From the Division of Neurology (A.G.), Department of Internal Medicine, Highland Hospital, Oakland, CA; Department of Neurology (C.G., K.G.), and Tan Chingfang Graduate School of Nursing (S. Crawford), University of Massachusetts Chan Medical School, Worcester; Department of Critical Care Medicine (P.B., D.B.W.), University of Pittsburgh School of Medicine, PA; Division of Pulmonary, Allergy, and Critical Care Medicine (C.L.H.), Department of Medicine, Oregon Health & Science University, Portland; Department of Medicine (B.L.), University of California San Francisco; Division of Pulmonary and Critical Care Medicine (S. Carson), Department of Medicine, University of North Carolina Hospitals, Chapel Hill; Division of Pulmonary Medicine and Critical Care Medicine (J.S.), Department of Internal Medicine, University of Massachusetts Chan Medical School-Baystate, Springfield; and Departments of Neurology, Anesthesia/Critical Care, and Surgery (S.M.), University of Massachusetts Chan Medical School, Worcester
| | - Connie Ge
- From the Division of Neurology (A.G.), Department of Internal Medicine, Highland Hospital, Oakland, CA; Department of Neurology (C.G., K.G.), and Tan Chingfang Graduate School of Nursing (S. Crawford), University of Massachusetts Chan Medical School, Worcester; Department of Critical Care Medicine (P.B., D.B.W.), University of Pittsburgh School of Medicine, PA; Division of Pulmonary, Allergy, and Critical Care Medicine (C.L.H.), Department of Medicine, Oregon Health & Science University, Portland; Department of Medicine (B.L.), University of California San Francisco; Division of Pulmonary and Critical Care Medicine (S. Carson), Department of Medicine, University of North Carolina Hospitals, Chapel Hill; Division of Pulmonary Medicine and Critical Care Medicine (J.S.), Department of Internal Medicine, University of Massachusetts Chan Medical School-Baystate, Springfield; and Departments of Neurology, Anesthesia/Critical Care, and Surgery (S.M.), University of Massachusetts Chan Medical School, Worcester.
| | - Sybil Crawford
- From the Division of Neurology (A.G.), Department of Internal Medicine, Highland Hospital, Oakland, CA; Department of Neurology (C.G., K.G.), and Tan Chingfang Graduate School of Nursing (S. Crawford), University of Massachusetts Chan Medical School, Worcester; Department of Critical Care Medicine (P.B., D.B.W.), University of Pittsburgh School of Medicine, PA; Division of Pulmonary, Allergy, and Critical Care Medicine (C.L.H.), Department of Medicine, Oregon Health & Science University, Portland; Department of Medicine (B.L.), University of California San Francisco; Division of Pulmonary and Critical Care Medicine (S. Carson), Department of Medicine, University of North Carolina Hospitals, Chapel Hill; Division of Pulmonary Medicine and Critical Care Medicine (J.S.), Department of Internal Medicine, University of Massachusetts Chan Medical School-Baystate, Springfield; and Departments of Neurology, Anesthesia/Critical Care, and Surgery (S.M.), University of Massachusetts Chan Medical School, Worcester
| | - Kelsey Goostrey
- From the Division of Neurology (A.G.), Department of Internal Medicine, Highland Hospital, Oakland, CA; Department of Neurology (C.G., K.G.), and Tan Chingfang Graduate School of Nursing (S. Crawford), University of Massachusetts Chan Medical School, Worcester; Department of Critical Care Medicine (P.B., D.B.W.), University of Pittsburgh School of Medicine, PA; Division of Pulmonary, Allergy, and Critical Care Medicine (C.L.H.), Department of Medicine, Oregon Health & Science University, Portland; Department of Medicine (B.L.), University of California San Francisco; Division of Pulmonary and Critical Care Medicine (S. Carson), Department of Medicine, University of North Carolina Hospitals, Chapel Hill; Division of Pulmonary Medicine and Critical Care Medicine (J.S.), Department of Internal Medicine, University of Massachusetts Chan Medical School-Baystate, Springfield; and Departments of Neurology, Anesthesia/Critical Care, and Surgery (S.M.), University of Massachusetts Chan Medical School, Worcester
| | - Praewpannanrai Buddadhumaruk
- From the Division of Neurology (A.G.), Department of Internal Medicine, Highland Hospital, Oakland, CA; Department of Neurology (C.G., K.G.), and Tan Chingfang Graduate School of Nursing (S. Crawford), University of Massachusetts Chan Medical School, Worcester; Department of Critical Care Medicine (P.B., D.B.W.), University of Pittsburgh School of Medicine, PA; Division of Pulmonary, Allergy, and Critical Care Medicine (C.L.H.), Department of Medicine, Oregon Health & Science University, Portland; Department of Medicine (B.L.), University of California San Francisco; Division of Pulmonary and Critical Care Medicine (S. Carson), Department of Medicine, University of North Carolina Hospitals, Chapel Hill; Division of Pulmonary Medicine and Critical Care Medicine (J.S.), Department of Internal Medicine, University of Massachusetts Chan Medical School-Baystate, Springfield; and Departments of Neurology, Anesthesia/Critical Care, and Surgery (S.M.), University of Massachusetts Chan Medical School, Worcester
| | - Catherine L Hough
- From the Division of Neurology (A.G.), Department of Internal Medicine, Highland Hospital, Oakland, CA; Department of Neurology (C.G., K.G.), and Tan Chingfang Graduate School of Nursing (S. Crawford), University of Massachusetts Chan Medical School, Worcester; Department of Critical Care Medicine (P.B., D.B.W.), University of Pittsburgh School of Medicine, PA; Division of Pulmonary, Allergy, and Critical Care Medicine (C.L.H.), Department of Medicine, Oregon Health & Science University, Portland; Department of Medicine (B.L.), University of California San Francisco; Division of Pulmonary and Critical Care Medicine (S. Carson), Department of Medicine, University of North Carolina Hospitals, Chapel Hill; Division of Pulmonary Medicine and Critical Care Medicine (J.S.), Department of Internal Medicine, University of Massachusetts Chan Medical School-Baystate, Springfield; and Departments of Neurology, Anesthesia/Critical Care, and Surgery (S.M.), University of Massachusetts Chan Medical School, Worcester
| | - Bernard Lo
- From the Division of Neurology (A.G.), Department of Internal Medicine, Highland Hospital, Oakland, CA; Department of Neurology (C.G., K.G.), and Tan Chingfang Graduate School of Nursing (S. Crawford), University of Massachusetts Chan Medical School, Worcester; Department of Critical Care Medicine (P.B., D.B.W.), University of Pittsburgh School of Medicine, PA; Division of Pulmonary, Allergy, and Critical Care Medicine (C.L.H.), Department of Medicine, Oregon Health & Science University, Portland; Department of Medicine (B.L.), University of California San Francisco; Division of Pulmonary and Critical Care Medicine (S. Carson), Department of Medicine, University of North Carolina Hospitals, Chapel Hill; Division of Pulmonary Medicine and Critical Care Medicine (J.S.), Department of Internal Medicine, University of Massachusetts Chan Medical School-Baystate, Springfield; and Departments of Neurology, Anesthesia/Critical Care, and Surgery (S.M.), University of Massachusetts Chan Medical School, Worcester
| | - Shannon Carson
- From the Division of Neurology (A.G.), Department of Internal Medicine, Highland Hospital, Oakland, CA; Department of Neurology (C.G., K.G.), and Tan Chingfang Graduate School of Nursing (S. Crawford), University of Massachusetts Chan Medical School, Worcester; Department of Critical Care Medicine (P.B., D.B.W.), University of Pittsburgh School of Medicine, PA; Division of Pulmonary, Allergy, and Critical Care Medicine (C.L.H.), Department of Medicine, Oregon Health & Science University, Portland; Department of Medicine (B.L.), University of California San Francisco; Division of Pulmonary and Critical Care Medicine (S. Carson), Department of Medicine, University of North Carolina Hospitals, Chapel Hill; Division of Pulmonary Medicine and Critical Care Medicine (J.S.), Department of Internal Medicine, University of Massachusetts Chan Medical School-Baystate, Springfield; and Departments of Neurology, Anesthesia/Critical Care, and Surgery (S.M.), University of Massachusetts Chan Medical School, Worcester
| | - Jay Steingrub
- From the Division of Neurology (A.G.), Department of Internal Medicine, Highland Hospital, Oakland, CA; Department of Neurology (C.G., K.G.), and Tan Chingfang Graduate School of Nursing (S. Crawford), University of Massachusetts Chan Medical School, Worcester; Department of Critical Care Medicine (P.B., D.B.W.), University of Pittsburgh School of Medicine, PA; Division of Pulmonary, Allergy, and Critical Care Medicine (C.L.H.), Department of Medicine, Oregon Health & Science University, Portland; Department of Medicine (B.L.), University of California San Francisco; Division of Pulmonary and Critical Care Medicine (S. Carson), Department of Medicine, University of North Carolina Hospitals, Chapel Hill; Division of Pulmonary Medicine and Critical Care Medicine (J.S.), Department of Internal Medicine, University of Massachusetts Chan Medical School-Baystate, Springfield; and Departments of Neurology, Anesthesia/Critical Care, and Surgery (S.M.), University of Massachusetts Chan Medical School, Worcester
| | - Douglas B White
- From the Division of Neurology (A.G.), Department of Internal Medicine, Highland Hospital, Oakland, CA; Department of Neurology (C.G., K.G.), and Tan Chingfang Graduate School of Nursing (S. Crawford), University of Massachusetts Chan Medical School, Worcester; Department of Critical Care Medicine (P.B., D.B.W.), University of Pittsburgh School of Medicine, PA; Division of Pulmonary, Allergy, and Critical Care Medicine (C.L.H.), Department of Medicine, Oregon Health & Science University, Portland; Department of Medicine (B.L.), University of California San Francisco; Division of Pulmonary and Critical Care Medicine (S. Carson), Department of Medicine, University of North Carolina Hospitals, Chapel Hill; Division of Pulmonary Medicine and Critical Care Medicine (J.S.), Department of Internal Medicine, University of Massachusetts Chan Medical School-Baystate, Springfield; and Departments of Neurology, Anesthesia/Critical Care, and Surgery (S.M.), University of Massachusetts Chan Medical School, Worcester
| | - Susanne Muehlschlegel
- From the Division of Neurology (A.G.), Department of Internal Medicine, Highland Hospital, Oakland, CA; Department of Neurology (C.G., K.G.), and Tan Chingfang Graduate School of Nursing (S. Crawford), University of Massachusetts Chan Medical School, Worcester; Department of Critical Care Medicine (P.B., D.B.W.), University of Pittsburgh School of Medicine, PA; Division of Pulmonary, Allergy, and Critical Care Medicine (C.L.H.), Department of Medicine, Oregon Health & Science University, Portland; Department of Medicine (B.L.), University of California San Francisco; Division of Pulmonary and Critical Care Medicine (S. Carson), Department of Medicine, University of North Carolina Hospitals, Chapel Hill; Division of Pulmonary Medicine and Critical Care Medicine (J.S.), Department of Internal Medicine, University of Massachusetts Chan Medical School-Baystate, Springfield; and Departments of Neurology, Anesthesia/Critical Care, and Surgery (S.M.), University of Massachusetts Chan Medical School, Worcester.
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Bhogadi SK, Magnotti LJ, Hosseinpour H, Anand T, El-Qawaqzeh K, Nelson A, Colosimo C, Spencer AL, Friese R, Joseph B. The final decision among the injured elderly, to stop or to continue? Predictors of withdrawal of life supporting treatment. J Trauma Acute Care Surg 2023; 94:778-783. [PMID: 36899461 DOI: 10.1097/ta.0000000000003924] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
Abstract
BACKGROUND There is a paucity of data on factors that influence the decision regarding withdrawal of life supporting treatment (WLST) in geriatric trauma patients. We aimed to identify predictors of WLST in geriatric trauma patients. METHODS This retrospective analysis of the American College of Surgeons- Trauma Quality Improvement Program (2017-2019) included all severely injured (Injury Severity Score >15) geriatric trauma patients (≥65 years). Multivariable logistic regression was performed to identify independent predictors of WLST. RESULTS There were 155,583 patients included. Mean age was 77 ± 7 years, 55% were male, 97% sustained blunt injury, and the median Injury Severity Score was 17 [16-25]. Overall WLST rate was 10.8%. On MLR analysis, increasing age (adjusted odds ratio [aOR], 1.35; 95% confidence interval [CI], 1.33-1.37; p < 0.001), male sex (aOR, 1.14; 95% CI, 1.09-1.18; p < 0.001), White race (aOR, 1.44; 95% CI, 1.36-1.52; p < 0.001), frailty (aOR, 1.42; 95% CI, 1.34-1.50; p < 0.001), government insurance (aOR, 1.27; 95% CI, 1.20-1.33; p < 0.001), presence of advance directive limiting care (aOR, 2.55; 95% CI, 2.40-2.70; p < 0.001), severe traumatic brain injury (aOR, 1.80; 95% CI, 1.66-1.95; p < 0.001), ventilator requirement (aOR, 12.73; 95% CI, 12.09-13.39; p < 0.001), and treatment at higher level trauma centers (Level I aOR, 1.49; 95% CI, 1.42-1.57; p < 0.001; Level II aOR, 1.43; 95% CI, 1.35-1.51; p < 0.001) were independently associated with higher odds of WLST. CONCLUSION Our results suggest that nearly one in 10 severely injured geriatric trauma patients undergo WLST. Multiple patient and hospital related factors contribute to decision making and directed efforts are necessary to create a more standardized process. LEVEL OF EVIDENCE Prognostic and Epidemiological; Level III.
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Affiliation(s)
- Sai Krishna Bhogadi
- From the Division of Trauma, Critical Care, Burns, and Emergency Surgery, Department of Surgery, College of Medicine, University of Arizona, Tucson, Arizona
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Predictors of In-Hospital Mortality and Home Discharge in Patients with Aneurysmal Subarachnoid Hemorrhage: A 4-Year Retrospective Analysis. Neurocrit Care 2023; 38:85-95. [PMID: 36114314 DOI: 10.1007/s12028-022-01596-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Accepted: 08/18/2022] [Indexed: 10/14/2022]
Abstract
BACKGROUND Factors associated with discharge disposition and mortality following aneurysmal subarachnoid hemorrhage (aSAH) are not well-characterized. We used a national all-payer database to identify factors associated with home discharge and in-hospital mortality. METHODS The National Inpatient Sample was queried for patients with aSAH within a 4-year range. Weighted multivariable logistic regression models were constructed and adjusted for age, sex, race, household income, insurance status, comorbidity burden, National Inpatient Sample SAH Severity Score, disease severity, treatment modality, in-hospital complications, and hospital characteristics (size, teaching status, and region). RESULTS Our sample included 37,965 patients: 33,605 were discharged alive and 14,350 were discharged home. Black patients had lower odds of in-hospital mortality compared with White patients (adjusted odds ratio [aOR] = 0.67, 95% confidence interval [CI] 0.52-0.86, p = 0.002). Compared with patients with private insurance, those with Medicare were less likely to have a home discharge (aOR = 0.58, 95% CI 0.46-0.74, p < 0.001), whereas those with self-pay (aOR = 2.97, 95% CI 2.29-3.86, p < 0.001) and no charge (aOR = 3.21, 95% CI 1.57-6.55, p = 0.001) were more likely to have a home discharge. Household income percentile was not associated with discharge disposition or in-hospital mortality. Paradoxically, increased number of Elixhauser comorbidities was associated with significantly lower odds of in-hospital mortality. CONCLUSIONS We demonstrate independent associations with hospital characteristics, patient characteristics, and treatment characteristics as related to discharge disposition and in-hospital mortality following aSAH, adjusted for disease severity.
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Neuroprognostication. Crit Care Clin 2023; 39:139-152. [DOI: 10.1016/j.ccc.2022.06.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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Mitchell T, Abdelgadir J, Oshotse C, Ubel PA, Williamson T. Definitely, Maybe: Helping Patients Make Decisions about Surgery When Prognosis Is Uncertain. THE JOURNAL OF CLINICAL ETHICS 2023; 34:169-174. [PMID: 37229741 DOI: 10.1086/724770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
AbstractThe sudden onset of severe traumatic brain injury (sTBI) is an event suffered by millions of individuals each year. Regardless of this frequency in occurrence, accurate prognostication remains difficult to achieve among physicians. There are many variables that affect this prognosis. Physicians are expected to assess the clinical indications of the brain injury while considering other factors such as patient quality of life, patient preferences, and environmental context. However, this lack of certainty in prognosis can ultimately affect treatment recommendations and prompt clinical ethical issues at the bedside, as it leaves room for physician bias and interpretation. In this article, we introduce data on neurosurgeon values that may shed light on the process physicians and patients involved in sTBI undergo. In doing so, we highlight the many nuances in decision-making for patients suffering from sTBI and discuss potential solutions to better patient-physician or surrogate-physician interactions.
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Eagle SR, Nwachuku E, Elmer J, Deng H, Okonkwo DO, Pease M. Performance of CRASH and IMPACT Prognostic Models for Traumatic Brain Injury at 12 and 24 Months Post-Injury. Neurotrauma Rep 2023; 4:118-123. [PMID: 36895818 PMCID: PMC9989509 DOI: 10.1089/neur.2022.0082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/05/2023] Open
Abstract
The Corticoid Randomization after Significant Head Injury (CRASH) and International Mission for Prognosis and Analysis of Clinical Trials (IMPACT) prognostic models are the most reported prognostic models for traumatic brain injury (TBI) in the scientific literature. However, these models were developed and validated to predict 6-month unfavorable outcome and mortality, and growing evidence supports continuous improvements in functional outcome after severe TBI up to 2 years post-injury. The purpose of this study was to evaluate CRASH and IMPACT model performance beyond 6 months post-injury to include 12 and 24 months post-injury. Discriminative validity remained consistent over time and comparable to earlier recovery time points (area under the curve = 0.77-0.83). Both models had poor fit for unfavorable outcomes, explaining less than one quarter of the variation in outcomes for severe TBI patients. The CRASH model had significant values for the Hosmer-Lemeshow test at 12 and 24 months, indicating poor model fit past the previous validation point. There is concern in the scientific literature that TBI prognostic models are being used by neurotrauma clinicians to support clinical decision making despite the goal of the models' development being to support research study design. The results of this study indicate that the CRASH and IMPACT models should not be used in routine clinical practice because of poor model fit that worsens over time and the large, unexplained variance in outcomes.
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Affiliation(s)
- Shawn R Eagle
- Department of Neurological Surgery, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Enyinna Nwachuku
- Department of Neurological Surgery, Cleveland Clinic, Akron, Ohio, USA
| | - Jonathan Elmer
- Department of Clinical Care Medicine, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Hansen Deng
- Department of Neurological Surgery, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - David O Okonkwo
- Department of Neurological Surgery, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Matthew Pease
- Department of Neurological Surgery, Memorial Sloan Kettering, New York, New York, USA
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Maas AIR, Menon DK, Manley GT, Abrams M, Åkerlund C, Andelic N, Aries M, Bashford T, Bell MJ, Bodien YG, Brett BL, Büki A, Chesnut RM, Citerio G, Clark D, Clasby B, Cooper DJ, Czeiter E, Czosnyka M, Dams-O’Connor K, De Keyser V, Diaz-Arrastia R, Ercole A, van Essen TA, Falvey É, Ferguson AR, Figaji A, Fitzgerald M, Foreman B, Gantner D, Gao G, Giacino J, Gravesteijn B, Guiza F, Gupta D, Gurnell M, Haagsma JA, Hammond FM, Hawryluk G, Hutchinson P, van der Jagt M, Jain S, Jain S, Jiang JY, Kent H, Kolias A, Kompanje EJO, Lecky F, Lingsma HF, Maegele M, Majdan M, Markowitz A, McCrea M, Meyfroidt G, Mikolić A, Mondello S, Mukherjee P, Nelson D, Nelson LD, Newcombe V, Okonkwo D, Orešič M, Peul W, Pisică D, Polinder S, Ponsford J, Puybasset L, Raj R, Robba C, Røe C, Rosand J, Schueler P, Sharp DJ, Smielewski P, Stein MB, von Steinbüchel N, Stewart W, Steyerberg EW, Stocchetti N, Temkin N, Tenovuo O, Theadom A, Thomas I, Espin AT, Turgeon AF, Unterberg A, Van Praag D, van Veen E, Verheyden J, Vyvere TV, Wang KKW, Wiegers EJA, Williams WH, Wilson L, Wisniewski SR, Younsi A, Yue JK, Yuh EL, Zeiler FA, Zeldovich M, Zemek R. Traumatic brain injury: progress and challenges in prevention, clinical care, and research. Lancet Neurol 2022; 21:1004-1060. [PMID: 36183712 PMCID: PMC10427240 DOI: 10.1016/s1474-4422(22)00309-x] [Citation(s) in RCA: 235] [Impact Index Per Article: 117.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Accepted: 07/22/2022] [Indexed: 02/06/2023]
Abstract
Traumatic brain injury (TBI) has the highest incidence of all common neurological disorders, and poses a substantial public health burden. TBI is increasingly documented not only as an acute condition but also as a chronic disease with long-term consequences, including an increased risk of late-onset neurodegeneration. The first Lancet Neurology Commission on TBI, published in 2017, called for a concerted effort to tackle the global health problem posed by TBI. Since then, funding agencies have supported research both in high-income countries (HICs) and in low-income and middle-income countries (LMICs). In November 2020, the World Health Assembly, the decision-making body of WHO, passed resolution WHA73.10 for global actions on epilepsy and other neurological disorders, and WHO launched the Decade for Action on Road Safety plan in 2021. New knowledge has been generated by large observational studies, including those conducted under the umbrella of the International Traumatic Brain Injury Research (InTBIR) initiative, established as a collaboration of funding agencies in 2011. InTBIR has also provided a huge stimulus to collaborative research in TBI and has facilitated participation of global partners. The return on investment has been high, but many needs of patients with TBI remain unaddressed. This update to the 2017 Commission presents advances and discusses persisting and new challenges in prevention, clinical care, and research. In LMICs, the occurrence of TBI is driven by road traffic incidents, often involving vulnerable road users such as motorcyclists and pedestrians. In HICs, most TBI is caused by falls, particularly in older people (aged ≥65 years), who often have comorbidities. Risk factors such as frailty and alcohol misuse provide opportunities for targeted prevention actions. Little evidence exists to inform treatment of older patients, who have been commonly excluded from past clinical trials—consequently, appropriate evidence is urgently required. Although increasing age is associated with worse outcomes from TBI, age should not dictate limitations in therapy. However, patients injured by low-energy falls (who are mostly older people) are about 50% less likely to receive critical care or emergency interventions, compared with those injured by high-energy mechanisms, such as road traffic incidents. Mild TBI, defined as a Glasgow Coma sum score of 13–15, comprises most of the TBI cases (over 90%) presenting to hospital. Around 50% of adult patients with mild TBI presenting to hospital do not recover to pre-TBI levels of health by 6 months after their injury. Fewer than 10% of patients discharged after presenting to an emergency department for TBI in Europe currently receive follow-up. Structured follow-up after mild TBI should be considered good practice, and urgent research is needed to identify which patients with mild TBI are at risk for incomplete recovery. The selection of patients for CT is an important triage decision in mild TBI since it allows early identification of lesions that can trigger hospital admission or life-saving surgery. Current decision making for deciding on CT is inefficient, with 90–95% of scanned patients showing no intracranial injury but being subjected to radiation risks. InTBIR studies have shown that measurement of blood-based biomarkers adds value to previously proposed clinical decision rules, holding the potential to improve efficiency while reducing radiation exposure. Increased concentrations of biomarkers in the blood of patients with a normal presentation CT scan suggest structural brain damage, which is seen on MR scanning in up to 30% of patients with mild TBI. Advanced MRI, including diffusion tensor imaging and volumetric analyses, can identify additional injuries not detectable by visual inspection of standard clinical MR images. Thus, the absence of CT abnormalities does not exclude structural damage—an observation relevant to litigation procedures, to management of mild TBI, and when CT scans are insufficient to explain the severity of the clinical condition. Although blood-based protein biomarkers have been shown to have important roles in the evaluation of TBI, most available assays are for research use only. To date, there is only one vendor of such assays with regulatory clearance in Europe and the USA with an indication to rule out the need for CT imaging for patients with suspected TBI. Regulatory clearance is provided for a combination of biomarkers, although evidence is accumulating that a single biomarker can perform as well as a combination. Additional biomarkers and more clinical-use platforms are on the horizon, but cross-platform harmonisation of results is needed. Health-care efficiency would benefit from diversity in providers. In the intensive care setting, automated analysis of blood pressure and intracranial pressure with calculation of derived parameters can help individualise management of TBI. Interest in the identification of subgroups of patients who might benefit more from some specific therapeutic approaches than others represents a welcome shift towards precision medicine. Comparative-effectiveness research to identify best practice has delivered on expectations for providing evidence in support of best practices, both in adult and paediatric patients with TBI. Progress has also been made in improving outcome assessment after TBI. Key instruments have been translated into up to 20 languages and linguistically validated, and are now internationally available for clinical and research use. TBI affects multiple domains of functioning, and outcomes are affected by personal characteristics and life-course events, consistent with a multifactorial bio-psycho-socio-ecological model of TBI, as presented in the US National Academies of Sciences, Engineering, and Medicine (NASEM) 2022 report. Multidimensional assessment is desirable and might be best based on measurement of global functional impairment. More work is required to develop and implement recommendations for multidimensional assessment. Prediction of outcome is relevant to patients and their families, and can facilitate the benchmarking of quality of care. InTBIR studies have identified new building blocks (eg, blood biomarkers and quantitative CT analysis) to refine existing prognostic models. Further improvement in prognostication could come from MRI, genetics, and the integration of dynamic changes in patient status after presentation. Neurotrauma researchers traditionally seek translation of their research findings through publications, clinical guidelines, and industry collaborations. However, to effectively impact clinical care and outcome, interactions are also needed with research funders, regulators, and policy makers, and partnership with patient organisations. Such interactions are increasingly taking place, with exemplars including interactions with the All Party Parliamentary Group on Acquired Brain Injury in the UK, the production of the NASEM report in the USA, and interactions with the US Food and Drug Administration. More interactions should be encouraged, and future discussions with regulators should include debates around consent from patients with acute mental incapacity and data sharing. Data sharing is strongly advocated by funding agencies. From January 2023, the US National Institutes of Health will require upload of research data into public repositories, but the EU requires data controllers to safeguard data security and privacy regulation. The tension between open data-sharing and adherence to privacy regulation could be resolved by cross-dataset analyses on federated platforms, with the data remaining at their original safe location. Tools already exist for conventional statistical analyses on federated platforms, however federated machine learning requires further development. Support for further development of federated platforms, and neuroinformatics more generally, should be a priority. This update to the 2017 Commission presents new insights and challenges across a range of topics around TBI: epidemiology and prevention (section 1 ); system of care (section 2 ); clinical management (section 3 ); characterisation of TBI (section 4 ); outcome assessment (section 5 ); prognosis (Section 6 ); and new directions for acquiring and implementing evidence (section 7 ). Table 1 summarises key messages from this Commission and proposes recommendations for the way forward to advance research and clinical management of TBI.
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Affiliation(s)
- Andrew I R Maas
- Department of Neurosurgery, Antwerp University Hospital and University of Antwerp, Edegem, Belgium
| | - David K Menon
- Division of Anaesthesia, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK
| | - Geoffrey T Manley
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
| | - Mathew Abrams
- International Neuroinformatics Coordinating Facility, Karolinska Institutet, Stockholm, Sweden
| | - Cecilia Åkerlund
- Department of Physiology and Pharmacology, Section of Perioperative Medicine and Intensive Care, Karolinska Institutet, Stockholm, Sweden
| | - Nada Andelic
- Division of Clinical Neuroscience, Department of Physical Medicine and Rehabilitation, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Marcel Aries
- Department of Intensive Care, Maastricht UMC, Maastricht, Netherlands
| | - Tom Bashford
- Division of Anaesthesia, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK
| | - Michael J Bell
- Critical Care Medicine, Neurological Surgery and Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Yelena G Bodien
- Department of Neurology and Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, MA, USA
| | - Benjamin L Brett
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, USA
| | - András Büki
- Department of Neurosurgery, Faculty of Medicine and Health Örebro University, Örebro, Sweden
- Department of Neurosurgery, Medical School; ELKH-PTE Clinical Neuroscience MR Research Group; and Neurotrauma Research Group, Janos Szentagothai Research Centre, University of Pecs, Pecs, Hungary
| | - Randall M Chesnut
- Department of Neurological Surgery and Department of Orthopaedics and Sports Medicine, University of Washington, Harborview Medical Center, Seattle, WA, USA
| | - Giuseppe Citerio
- School of Medicine and Surgery, Universita Milano Bicocca, Milan, Italy
- NeuroIntensive Care, San Gerardo Hospital, Azienda Socio Sanitaria Territoriale (ASST) Monza, Monza, Italy
| | - David Clark
- Brain Physics Lab, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK
| | - Betony Clasby
- Department of Sociological Studies, University of Sheffield, Sheffield, UK
| | - D Jamie Cooper
- School of Public Health and Preventive Medicine, Monash University and The Alfred Hospital, Melbourne, VIC, Australia
| | - Endre Czeiter
- Department of Neurosurgery, Medical School; ELKH-PTE Clinical Neuroscience MR Research Group; and Neurotrauma Research Group, Janos Szentagothai Research Centre, University of Pecs, Pecs, Hungary
| | - Marek Czosnyka
- Brain Physics Lab, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK
| | - Kristen Dams-O’Connor
- Department of Rehabilitation and Human Performance and Department of Neurology, Brain Injury Research Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Véronique De Keyser
- Department of Neurosurgery, Antwerp University Hospital and University of Antwerp, Edegem, Belgium
| | - Ramon Diaz-Arrastia
- Department of Neurology and Center for Brain Injury and Repair, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ari Ercole
- Division of Anaesthesia, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK
| | - Thomas A van Essen
- Department of Neurosurgery, Leiden University Medical Center, Leiden, Netherlands
- Department of Neurosurgery, Medical Center Haaglanden, The Hague, Netherlands
| | - Éanna Falvey
- College of Medicine and Health, University College Cork, Cork, Ireland
| | - Adam R Ferguson
- Brain and Spinal Injury Center, Department of Neurological Surgery, Weill Institute for Neurosciences, University of California San Francisco and San Francisco Veterans Affairs Healthcare System, San Francisco, CA, USA
| | - Anthony Figaji
- Division of Neurosurgery and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Melinda Fitzgerald
- Curtin Health Innovation Research Institute, Curtin University, Bentley, WA, Australia
- Perron Institute for Neurological and Translational Sciences, Nedlands, WA, Australia
| | - Brandon Foreman
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati Gardner Neuroscience Institute, University of Cincinnati, Cincinnati, OH, USA
| | - Dashiell Gantner
- School of Public Health and Preventive Medicine, Monash University and The Alfred Hospital, Melbourne, VIC, Australia
| | - Guoyi Gao
- Department of Neurosurgery, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine
| | - Joseph Giacino
- Department of Physical Medicine and Rehabilitation, Harvard Medical School and Spaulding Rehabilitation Hospital, Charlestown, MA, USA
| | - Benjamin Gravesteijn
- Department of Public Health, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Fabian Guiza
- Department and Laboratory of Intensive Care Medicine, University Hospitals Leuven and KU Leuven, Leuven, Belgium
| | - Deepak Gupta
- Department of Neurosurgery, Neurosciences Centre and JPN Apex Trauma Centre, All India Institute of Medical Sciences, New Delhi, India
| | - Mark Gurnell
- Metabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Juanita A Haagsma
- Department of Public Health, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Flora M Hammond
- Department of Physical Medicine and Rehabilitation, Indiana University School of Medicine, Rehabilitation Hospital of Indiana, Indianapolis, IN, USA
| | - Gregory Hawryluk
- Section of Neurosurgery, GB1, Health Sciences Centre, University of Manitoba, Winnipeg, MB, Canada
| | - Peter Hutchinson
- Brain Physics Lab, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK
| | - Mathieu van der Jagt
- Department of Intensive Care, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Sonia Jain
- Biostatistics Research Center, Herbert Wertheim School of Public Health, University of California, San Diego, CA, USA
| | - Swati Jain
- Brain Physics Lab, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK
| | - Ji-yao Jiang
- Department of Neurosurgery, Shanghai Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Hope Kent
- Department of Psychology, University of Exeter, Exeter, UK
| | - Angelos Kolias
- Brain Physics Lab, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK
| | - Erwin J O Kompanje
- Department of Intensive Care, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Fiona Lecky
- Centre for Urgent and Emergency Care Research, Health Services Research Section, School of Health and Related Research, University of Sheffield, Sheffield, UK
| | - Hester F Lingsma
- Department of Public Health, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Marc Maegele
- Cologne-Merheim Medical Center, Department of Trauma and Orthopedic Surgery, Witten/Herdecke University, Cologne, Germany
| | - Marek Majdan
- Institute for Global Health and Epidemiology, Department of Public Health, Faculty of Health Sciences and Social Work, Trnava University, Trnava, Slovakia
| | - Amy Markowitz
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
| | - Michael McCrea
- Department of Neurosurgery and Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Geert Meyfroidt
- Department and Laboratory of Intensive Care Medicine, University Hospitals Leuven and KU Leuven, Leuven, Belgium
| | - Ana Mikolić
- Department of Public Health, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Stefania Mondello
- Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy
| | - Pratik Mukherjee
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - David Nelson
- Section for Anesthesiology and Intensive Care, Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Lindsay D Nelson
- Department of Neurosurgery and Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Virginia Newcombe
- Division of Anaesthesia, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK
| | - David Okonkwo
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Matej Orešič
- School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Wilco Peul
- Department of Neurosurgery, Leiden University Medical Center, Leiden, Netherlands
| | - Dana Pisică
- Department of Public Health, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Neurosurgery, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Suzanne Polinder
- Department of Public Health, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Jennie Ponsford
- Monash-Epworth Rehabilitation Research Centre, Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, VIC, Australia
| | - Louis Puybasset
- Department of Anesthesiology and Intensive Care, APHP, Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, France
| | - Rahul Raj
- Department of Neurosurgery, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Chiara Robba
- Department of Anaesthesia and Intensive Care, Policlinico San Martino IRCCS for Oncology and Neuroscience, Genova, Italy, and Dipartimento di Scienze Chirurgiche e Diagnostiche, University of Genoa, Italy
| | - Cecilie Røe
- Division of Clinical Neuroscience, Department of Physical Medicine and Rehabilitation, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Jonathan Rosand
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | | | - David J Sharp
- Department of Brain Sciences, Imperial College London, London, UK
| | - Peter Smielewski
- Brain Physics Lab, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK
| | - Murray B Stein
- Department of Psychiatry and Department of Family Medicine and Public Health, UCSD School of Medicine, La Jolla, CA, USA
| | - Nicole von Steinbüchel
- Institute of Medical Psychology and Medical Sociology, University Medical Center Goettingen, Goettingen, Germany
| | - William Stewart
- Department of Neuropathology, Queen Elizabeth University Hospital and University of Glasgow, Glasgow, UK
| | - Ewout W Steyerberg
- Department of Biomedical Data Sciences Leiden University Medical Center, Leiden, Netherlands
| | - Nino Stocchetti
- Department of Pathophysiology and Transplantation, Milan University, and Neuroscience ICU, Fondazione IRCCS Ca Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Nancy Temkin
- Departments of Neurological Surgery, and Biostatistics, University of Washington, Seattle, WA, USA
| | - Olli Tenovuo
- Department of Rehabilitation and Brain Trauma, Turku University Hospital, and Department of Neurology, University of Turku, Turku, Finland
| | - Alice Theadom
- National Institute for Stroke and Applied Neurosciences, Faculty of Health and Environmental Studies, Auckland University of Technology, Auckland, New Zealand
| | - Ilias Thomas
- School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Abel Torres Espin
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
| | - Alexis F Turgeon
- Department of Anesthesiology and Critical Care Medicine, Division of Critical Care Medicine, Université Laval, CHU de Québec-Université Laval Research Center, Québec City, QC, Canada
| | - Andreas Unterberg
- Department of Neurosurgery, Heidelberg University Hospital, Heidelberg, Germany
| | - Dominique Van Praag
- Departments of Clinical Psychology and Neurosurgery, Antwerp University Hospital, and University of Antwerp, Edegem, Belgium
| | - Ernest van Veen
- Department of Public Health, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | | | - Thijs Vande Vyvere
- Department of Radiology, Faculty of Medicine and Health Sciences, Department of Rehabilitation Sciences (MOVANT), Antwerp University Hospital, and University of Antwerp, Edegem, Belgium
| | - Kevin K W Wang
- Department of Psychiatry, University of Florida, Gainesville, FL, USA
| | - Eveline J A Wiegers
- Department of Public Health, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - W Huw Williams
- Centre for Clinical Neuropsychology Research, Department of Psychology, University of Exeter, Exeter, UK
| | - Lindsay Wilson
- Division of Psychology, University of Stirling, Stirling, UK
| | - Stephen R Wisniewski
- University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania, USA
| | - Alexander Younsi
- Department of Neurosurgery, Heidelberg University Hospital, Heidelberg, Germany
| | - John K Yue
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
| | - Esther L Yuh
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Frederick A Zeiler
- Departments of Surgery, Human Anatomy and Cell Science, and Biomedical Engineering, Rady Faculty of Health Sciences and Price Faculty of Engineering, University of Manitoba, Winnipeg, MB, Canada
| | - Marina Zeldovich
- Institute of Medical Psychology and Medical Sociology, University Medical Center Goettingen, Goettingen, Germany
| | - Roger Zemek
- Departments of Pediatrics and Emergency Medicine, University of Ottawa, Children’s Hospital of Eastern Ontario, ON, Canada
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Tanizaki S, Toma Y, Miyashita K, Maeda S. The Characteristics of Withdrawal or Withholding of Life-Sustaining Treatment in Severe Traumatic Brain Injury: A Single Japanese Institutional Study. World Neurosurg X 2022; 17:100144. [PMID: 36353247 PMCID: PMC9637969 DOI: 10.1016/j.wnsx.2022.100144] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 09/27/2022] [Indexed: 11/22/2022] Open
Abstract
OBJECTIVES There is little evidence on the factors influencing the decision to withdraw or continue life-sustaining treatment in the setting of severe traumatic brain injury in Japanese institutions. We investigated the factors associated with the withdrawal or withholding of life-sustaining treatment (WLST) for severe traumatic brain injury at a single Japanese institution. METHODS A total of 161 patients with severe traumatic brain injury were retrospectively reviewed. Patient characteristics and injury types were compared between patients with and without the WLST. RESULTS Of the 161 patients, 87 (54%) died and 52 (32%) decided to undergo WLST. In 98% of the WLST cases, the decision was made within 24 h of admission. The mean duration between WLST and death was 2 days. The predicted probabilities for mortality and unfavorable outcomes were highest in patients with WLST within 24 h. Patients with WLST were older and had a higher frequency of falls on the ground, ischemic heart disease, and acute subdural hemorrhage than those without WLST. CONCLUSIONS The decisions of almost all WLST cases were made within 24 h of admission for severe traumatic brain injury in a Japanese institution because of Japanese patients' religious and cultural backgrounds.
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Affiliation(s)
- Shinsuke Tanizaki
- Department of Emergency Medicine, Fukui Prefectural Hospital, Fukui, Japan,To whom correspondence should be addressed: Shinsuke Tanizaki, M.D.
| | - Yasuo Toma
- Department of Neurosurgery, Fukui Prefectural Hospital, Fukui, Japan
| | | | - Shigenobu Maeda
- Department of Emergency Medicine, Fukui Prefectural Hospital, Fukui, Japan
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Brandmeir N, Sieg EP. Commentary: Time to Follow Commands in Severe Traumatic Brain Injury Survivors With Favorable Recovery at 2 Years. Neurosurgery 2022; 91:e105-e106. [PMID: 35951728 DOI: 10.1227/neu.0000000000002101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 06/27/2022] [Indexed: 02/04/2023] Open
Affiliation(s)
- Nicholas Brandmeir
- Department of Neurosurgery, Rockefeller Neuroscience Institute, West Virginia University, Morgantown, West Virginia, USA
| | - Emily P Sieg
- Department of Neurological Surgery, University of Louisville, Louisville, Kentucky, USA
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DeMario BS, Stanley SP, Truong EI, Ladhani HA, Brown LR, Ho VP, Kelly ML. Predictors for Withdrawal of Life-Sustaining Therapies in Patients With Traumatic Brain Injury: A Retrospective Trauma Quality Improvement Program Database Study. Neurosurgery 2022; 91:e45-e50. [PMID: 35471648 PMCID: PMC9514740 DOI: 10.1227/neu.0000000000002020] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 03/05/2022] [Indexed: 12/21/2022] Open
Abstract
Many patients with severe traumatic brain injuries (TBIs) undergo withdrawal of life-sustaining therapies (WLSTs) or transition to comfort measures, but noninjury factors that influence this decision have not been well characterized. We hypothesized that WLST would be associated with institutional and geographic noninjury factors. All patients with a head Abbreviated Injury Scale score ≥3 were identified from 2016 Trauma Quality Improvement Program data. We analyzed factors that might be associated with WLST, including procedure type, age, sex, race, insurance, Glasgow Coma Scale score, mechanism of injury, geographic region, and institutional size and teaching status. Adjusted logistic regression was performed to examine factors associated with WLST. Sixty-nine thousand fifty-three patients were identified: 66% male, 77% with isolated TBI, and 7.8% had WLST. The median age was 56 years (34-73). A positive correlation was found between increasing age and WLST. Women were less likely to undergo WLST than men (odds ratio 0.91 [0.84-0.98]) and took more time to for WLST (3 vs 2 days, P < .001). African Americans underwent WLST at a significantly lower rate (odds ratio 0.66 [0.58-0.75]). Variations were also discovered based on US region, hospital characteristics, and neurosurgical procedures. WLST in severe TBI is independently associated with noninjury factors such as sex, age, race, hospital characteristics, and geographic region. The effect of noninjury factors on these decisions is poorly understood; further study of WLST patterns can aid health care providers in decision making for patients with severe TBI.
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Affiliation(s)
| | - Samuel P. Stanley
- Department of Surgery, MetroHealth Medical Center, Cleveland, Ohio, USA
| | - Evelyn I. Truong
- Department of Surgery, MetroHealth Medical Center, Cleveland, Ohio, USA
| | - Husayn A. Ladhani
- Department of Surgery, MetroHealth Medical Center, Cleveland, Ohio, USA
| | - Laura R. Brown
- Department of Surgery, MetroHealth Medical Center, Cleveland, Ohio, USA
| | - Vanessa P. Ho
- Department of Surgery, MetroHealth Medical Center, Cleveland, Ohio, USA
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
| | - Michael L. Kelly
- Department of Neurological Surgery, Case Western Reserve University School of Medicine, MetroHealth Medical Center, Cleveland, Ohio, USA
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Young M, Peterson AH. Neuroethics across the Disorders of Consciousness Care Continuum. Semin Neurol 2022; 42:375-392. [PMID: 35738293 DOI: 10.1055/a-1883-0701] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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35
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Williamson TL, Adil SM, Shalita C, Charalambous LT, Mitchell T, Yang Z, Parente BA, Lee HJ, Ubel PA, Lemmon ME, Galanos AN, Lad SP, Komisarow JM. Palliative Care Consultations in Patients with Severe Traumatic Brain Injury: Who Receives Palliative Care Consultations and What Does that Mean for Utilization? Neurocrit Care 2022; 36:781-790. [PMID: 34988887 PMCID: PMC9117411 DOI: 10.1007/s12028-021-01366-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 09/24/2021] [Indexed: 10/19/2022]
Abstract
BACKGROUND Palliative care has the potential to improve goal-concordant care in severe traumatic brain injury (sTBI). Our primary objective was to illuminate the demographic profiles of patients with sTBI who receive palliative care encounters (PCEs), with an emphasis on the role of race. Secondary objectives were to analyze PCE usage over time and compare health care resource utilization between patients with or without PCEs. METHODS The National Inpatient Sample database was queried for patients age ≥ 18 who had a diagnosis of sTBI, defined by using International Classification of Diseases, 9th Revision codes. PCEs were defined by using International Classification of Diseases, 9th Revision code V66.7 and trended from 2001 to 2015. To assess factors associated with PCE in patients with sTBI, we performed unweighted generalized estimating equations regression. PCE association with decision making was modeled via its effect on rate of percutaneous endoscopic gastrostomy (PEG) tube placement. To quantify differences in PCE-related decisions by race, race was modeled as an effect modifier. RESULTS From 2001 to 2015, the proportion of palliative care usage in patients with sTBI increased from 1.5 to 36.3%, with 41.6% White, 22.3% Black, and 25% Hispanic patients with sTBI having a palliative care consultation in 2015, respectively. From 2008 to 2015, we identified 17,673 sTBI admissions. White and affluent patients were more likely to have a PCE than Black, Hispanic, and low socioeconomic status patients. Across all races, patients receiving a PCE resulted in a lower rate of PEG tube placement; however, White patients exhibited a larger reduction of PEG tube placement than Black patients. Patients using palliative care had lower total hospital costs (median $16,368 vs. $26,442, respectively). CONCLUSIONS Palliative care usage for sTBI has increased dramatically this century and it reduces resource utilization. This is true across races, however, its usage rate and associated effect on decision making are race-dependent, with White patients receiving more PCE and being more likely to decline the use of a PEG tube if they have had a PCE.
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Affiliation(s)
- Theresa L Williamson
- Department of Neurosurgery, Duke University Medical Center, Box 3807, Durham, NC, 27710, USA.
| | - Syed M Adil
- Department of Neurosurgery, Duke University Medical Center, Box 3807, Durham, NC, 27710, USA
| | - Chidyaonga Shalita
- Department of Neurosurgery, Duke University Medical Center, Box 3807, Durham, NC, 27710, USA
| | - Lefko T Charalambous
- Department of Neurosurgery, Duke University Medical Center, Box 3807, Durham, NC, 27710, USA
| | - Taylor Mitchell
- Department of Neurosurgery, Duke University Medical Center, Box 3807, Durham, NC, 27710, USA
| | - Zidanyue Yang
- Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, 27710, USA
| | - Beth A Parente
- Department of Neurosurgery, Duke University Medical Center, Box 3807, Durham, NC, 27710, USA
| | - Hui-Jie Lee
- Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, 27710, USA
| | - Peter A Ubel
- Fuqua School of Business, Duke University, Durham, NC, 27710, USA
| | - Monica E Lemmon
- Department of Pediatrics, Duke University Medical Center, Durham, NC, 27710, USA
| | - Anthony N Galanos
- Division of Palliative Care, Department of Medicine, Duke University Medical Center, Durham, NC, 27710, USA
| | - Shivanand P Lad
- Department of Neurosurgery, Duke University Medical Center, Box 3807, Durham, NC, 27710, USA
| | - Jordan M Komisarow
- Department of Neurosurgery, Duke University Medical Center, Box 3807, Durham, NC, 27710, USA
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Kaplan HJ, Leitman IM. Race and insurance status outcome disparities following splenectomy in trauma patients are reduced in larger hospitals. A cross-sectional study. Ann Med Surg (Lond) 2022; 77:103516. [PMID: 35638010 PMCID: PMC9142383 DOI: 10.1016/j.amsu.2022.103516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 03/14/2022] [Accepted: 03/26/2022] [Indexed: 11/24/2022] Open
Abstract
Background Splenectomy, still a commonly performed treatment for splenic injury in trauma patients, has been shown to have a high rate of complications. The purpose of this study was to identify predictors, including race and insurance status, associated with adverse outcomes post-splenectomy in trauma patients. We discuss possible explanations and methods for reducing these disparities. Methods The American College of Surgeons – Trauma Quality Improvement Program (ACS-TQIP) participant user database was queried from 2010 to 2015 and patients who underwent total splenectomy were identified. All mechanisms of injury, including both blunt and penetrating trauma, were included. Patients with advance directives limiting care or aged under 18 were excluded. Propensity score matching was used to control for age, preexisting medical conditions, and the severity of the traumatic injury. A chi-squared test was used to find significant associations between available predictors and outcomes for this cross-sectional study. Results The post-splenectomy mortality rate was 9.2% (n = 1047), 8.0% (n = 918) of patients had three or more complications, and 20.3% (n = 2315) had major complications. A primary race of white (OR 0.7, 95% Confidence Interval (CI) 0.6–0.9, p < 0.01) and private insurance (OR 0.5, 95%CI 0.4–0.6, p < 0.01) were associated with lower risks of mortality A primary race of neither Black nor white (OR 1.3, 95%CI 1.03–1.7, p = 0.03) and a lack of health insurance (“self-pay”) (OR 1.6, 95%CI 1.3–1.9, p < 0.01) were both correlated with mortality. When limited to hospitals of 600+ beds, there were no associations between race and mortality. Conclusion The post-splenectomy mortality rate after trauma remains high. In U.S. trauma centers, a primary race of Black and payment status of “self-pay” are associated with adverse outcomes after splenectomy following a traumatic injury. These disparities are reduced when limiting analysis to larger hospitals. Efforts to reduce disparities in outcomes among trauma patients requiring a splenectomy should focus on improving resource availability and quality in smaller hospitals. The post-splenectomy mortality rate in trauma patients remains high. Mortality is less frequent in white patients, and more frequent in uninsured patients. Black patients were more likely to experience major complications following splenectomy. In hospitals with greater than 600 beds, there were no associations between race and mortality following splenectomy.
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Goostrey K, Muehlschlegel S. Prognostication and shared decision making in neurocritical care. BMJ 2022; 377:e060154. [PMID: 35696329 DOI: 10.1136/bmj-2021-060154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Prognostication is crucial in the neurological intensive care unit (neuroICU). Patients with severe acute brain injury (SABI) are unable to make their own decisions because of the insult itself or sedation needs. Surrogate decision makers, usually family members, must make decisions on the patient's behalf. However, many are unprepared for their role as surrogates owing to the sudden and unexpected nature of SABI. Surrogates rely on clinicians in the neuroICU to provide them with an outlook (prognosis) with which to make substituted judgments and decide on treatments and goals of care on behalf of the patient. Therefore, how a prognostic estimate is derived, and then communicated, is extremely important. Prognostication in the neuroICU is highly variable between clinicians and institutions, and evidence based guidelines are lacking. Shared decision making (SDM), where surrogates and clinicians arrive together at an individualized decision based on patient values and preferences, has been proposed as an opportunity to improve clinician-family communication and ensure that patients receive treatments they would choose. This review outlines the importance and current challenges of prognostication in the neuroICU and how prognostication and SDM intersect, based on relevant research and expert opinion.
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Affiliation(s)
- Kelsey Goostrey
- Department of neurology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Susanne Muehlschlegel
- Department of neurology, University of Massachusetts Chan Medical School, Worcester, MA, USA
- Department of anesthesiology/critical care, University of Massachusetts Chan Medical School, Worcester, MA, USA
- Department of surgery, University of Massachusetts Chan Medical School, Worcester, MA, USA
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Mollayeva T, Tran A, Chan V, Colantonio A, Sutton M, Escobar MD. Decoding health status transitions of over 200 000 patients with traumatic brain injury from preceding injury to the injury event. Sci Rep 2022; 12:5584. [PMID: 35379824 PMCID: PMC8980052 DOI: 10.1038/s41598-022-08782-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 02/28/2022] [Indexed: 11/17/2022] Open
Abstract
For centuries, the study of traumatic brain injury (TBI) has been centred on historical observation and analyses of personal, social, and environmental processes, which have been examined separately. Today, computation implementation and vast patient data repositories can enable a concurrent analysis of personal, social, and environmental processes, providing insight into changes in health status transitions over time. We applied computational and data visualization techniques to categorize decade-long health records of 235,003 patients with TBI in Canada, from preceding injury to the injury event itself. Our results highlighted that health status transition patterns in TBI emerged along with the projection of comorbidity where many disorders, social and environmental adversities preceding injury are reflected in external causes of injury and injury severity. The strongest associations between health status preceding TBI and health status at the injury event were between multiple body system pathology and advanced age-related brain pathology networks. The interwoven aspects of health status on a time continuum can influence post-injury trajectories and should be considered in TBI risk analysis to improve prevention, diagnosis, and care.
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Bonow RH, Vavilala MS. Disparities in neurosurgical care for traumatic brain injury. Lancet Neurol 2022; 21:398-399. [DOI: 10.1016/s1474-4422(22)00094-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 02/18/2022] [Accepted: 02/26/2022] [Indexed: 11/30/2022]
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Variability of Prognostic Communication in Critically Ill Neurologic Patients: A Pilot Multicenter Mixed-Methods Study. Crit Care Explor 2022; 4:e0640. [PMID: 35224505 PMCID: PMC8863127 DOI: 10.1097/cce.0000000000000640] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
IMPORTANCE: Withdrawal-of-life-sustaining treatments (WOLST) rates vary widely among critically ill neurologic patients (CINPs) and cannot be solely attributed to patient and family characteristics. Research in general critical care has shown that clinicians prognosticate to families with high variability. Little is known about how clinicians disclose prognosis to families of CINPs, and whether any associations exist with WOLST. OBJECTIVES: Primary: to demonstrate feasibility of audio-recording clinician-family meetings for CINPs at multiple centers and characterize how clinicians communicate prognosis during these meetings. Secondary: to explore associations of 1) clinician, family, or patient characteristics with clinicians’ prognostication approaches and 2) prognostication approach and WOLST. DESIGN, SETTING, AND PARTICIPANTS: Forty-three audio-recorded clinician-family meetings during which prognosis was discussed from seven U.S. centers for 39 CINPs with 88 family members and 27 clinicians. MAIN OUTCOMES AND MEASURES: Two investigators qualitatively coded transcripts using inductive methods (inter-rater reliability > 80%) to characterize how clinicians prognosticate. We then applied univariate and multivariable multinomial and binomial logistic regression. RESULTS: Clinicians used four distinct prognostication approaches: Authoritative (21%; recommending treatments without discussing values and preferences); Informational (23%; disclosing just the prognosis without further discussions); advisory (42%; disclosing prognosis followed by discussion of values and preferences); and responsive (14%; eliciting values and preferences, then disclosing prognosis). Before adjustment, prognostication approach was associated with center (p < 0.001), clinician specialty (neurointensivists vs non-neurointensivists; p = 0.001), patient age (p = 0.08), diagnosis (p = 0.059), and meeting length (p = 0.03). After adjustment, only clinician specialty independently predicted prognostication approach (p = 0.027). WOLST decisions occurred in 41% of patients and were most common under the advisory approach (56%). WOLST was more likely in older patients (p = 0.059) and with more experienced clinicians (p = 0.07). Prognostication approach was not independently associated with WOLST (p = 0.198). CONCLUSIONS AND RELEVANCE: It is feasible to audio-record sensitive clinician-family meetings about CINPs in multiple ICUs. We found that clinicians prognosticate with high variability. Our data suggest that larger studies are warranted in CINPs to examine the role of clinicians’ variable prognostication in WOLST decisions.
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Helbok R, Rass V, Beghi E, Bodien YG, Citerio G, Giacino JT, Kondziella D, Mayer SA, Menon D, Sharshar T, Stevens RD, Ulmer H, Venkatasubba Rao CP, Vespa P, McNett M, Frontera J. The Curing Coma Campaign International Survey on Coma Epidemiology, Evaluation, and Therapy (COME TOGETHER). Neurocrit Care 2022; 37:47-59. [PMID: 35141860 PMCID: PMC9283177 DOI: 10.1007/s12028-021-01425-8] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 12/14/2021] [Indexed: 11/29/2022]
Abstract
Background Although coma is commonly encountered in critical care, worldwide variability exists in diagnosis and management practices. We aimed to assess variability in coma definitions, etiologies, treatment strategies, and attitudes toward prognosis. Methods As part of the Neurocritical Care Society Curing Coma Campaign, between September 2020 and January 2021, we conducted an anonymous, international, cross-sectional global survey of health care professionals caring for patients with coma and disorders of consciousness in the acute, subacute, or chronic setting. Survey responses were solicited by sequential emails distributed by international neuroscience societies and social media. Fleiss κ values were calculated to assess agreement among respondents. Results The survey was completed by 258 health care professionals from 41 countries. Respondents predominantly were physicians (n = 213, 83%), were from the United States (n = 141, 55%), and represented academic centers (n = 231, 90%). Among eight predefined items, respondents identified the following cardinal features, in various combinations, that must be present to define coma: absence of wakefulness (81%, κ = 0.764); Glasgow Coma Score (GCS) ≤ 8 (64%, κ = 0.588); failure to respond purposefully to visual, verbal, or tactile stimuli (60%, κ = 0.552); and inability to follow commands (58%, κ = 0.529). Reported etiologies of coma encountered included medically induced coma (24%), traumatic brain injury (24%), intracerebral hemorrhage (21%), and cardiac arrest/hypoxic-ischemic encephalopathy (11%). The most common clinical assessment tools used for coma included the GCS (94%) and neurological examination (78%). Sixty-six percent of respondents routinely performed sedation interruption, in the absence of contraindications, for clinical coma assessments in the intensive care unit. Advanced neurological assessment techniques in comatose patients included quantitative electroencephalography (EEG)/connectivity analysis (16%), functional magnetic resonance imaging (7%), single-photon emission computerized tomography (6%), positron emission tomography (4%), invasive EEG (4%), and cerebral microdialysis (4%). The most commonly used neurostimulants included amantadine (51%), modafinil (37%), and methylphenidate (28%). The leading determinants for prognostication included etiology of coma, neurological examination findings, and neuroimaging. Fewer than 20% of respondents reported routine follow-up of coma survivors after hospital discharge; however, 86% indicated interest in future research initiatives that include postdischarge outcomes at six (85%) and 12 months (65%). Conclusions There is wide heterogeneity among health care professionals regarding the clinical definition of coma and limited routine use of advanced coma assessment techniques in acute care settings. Coma management practices vary across sites, and mechanisms for coordinated and sustained follow-up after acute treatment are inconsistent. There is an urgent need for the development of evidence-based guidelines and a collaborative, coordinated approach to advance both the science and the practice of coma management globally. Supplementary Information The online version contains supplementary material available at 10.1007/s12028-021-01425-8.
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Affiliation(s)
- Raimund Helbok
- Department of Neurology, Neuro-Intensive Care Unit, Medical University of Innsbruck, Anichstrasse 35, 6020, Innsbruck, Austria.
| | - Verena Rass
- Department of Neurology, Neuro-Intensive Care Unit, Medical University of Innsbruck, Anichstrasse 35, 6020, Innsbruck, Austria
| | - Ettore Beghi
- Department of Neuroscience, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Yelena G Bodien
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Harvard Medical School, Harvard University, Boston, MA, USA.,Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Giuseppe Citerio
- Neuro-Intensive Care, ASST Di Monza, Monza, Italy.,School of Medicine and Surgery, Università Milano Bicocca, Milan, Italy
| | - Joseph T Giacino
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Harvard Medical School, Harvard University, Boston, MA, USA
| | - Daniel Kondziella
- Department of Neurology, Rigshospitalet, Copenhagen University Hospital and Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Stephan A Mayer
- Department of Neurology, New York Medical College, Valhalla, NY, USA
| | - David Menon
- Division of Anaesthesia, University of Cambridge, Cambridge, UK
| | - Tarek Sharshar
- Neuro-Intensive Care Medicine, Sainte-Anne Hospital, University of Paris, GHU-Psychiatry & Neurosciences, Paris, France
| | - Robert D Stevens
- Departments of Anesthesiology and Critical Care Medicine, Neurology, and Neurosurgery, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Hanno Ulmer
- Director Department of Medical Statistic, Informatics and Health Economics, Medical University of Innsbruck, Innsbruck, Austria
| | - Chethan P Venkatasubba Rao
- Division of Vascular Neurology and Neurocritical Care, Baylor College of Medicine and CHI Baylor St Luke's Medical Center, Houston, TX, USA
| | - Paul Vespa
- Departments of Neurology and Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Molly McNett
- College of Nursing, The Ohio State University, Columbus, OH, USA
| | - Jennifer Frontera
- Department of Neurology, Grossman School of Medicine, New York University, New York, NY, USA
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Bozkurt I, Umana GE, Deora H, Wellington J, Karakoc E, Chaurasia B. Factors Affecting Neurosurgeons' Decisions to Forgo Life-Sustaining Treatments After Traumatic Brain Injury. World Neurosurg 2021; 159:e311-e323. [PMID: 34933149 DOI: 10.1016/j.wneu.2021.12.056] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2021] [Revised: 12/13/2021] [Accepted: 12/14/2021] [Indexed: 10/19/2022]
Abstract
BACKGROUND Traumatic brain injury (TBI) is a multifaceted condition that causes mortality and disability worldwide. Limited data are available on the factors associated with the decision for the withdrawal of life-sustaining treatment (WLST) for patients with TBI. In the present study, we aimed to determine the risk factors and attitudes affecting neurosurgeons when deciding on WLST for patients with TBI using a multicenter survey. METHODS An online questionnaire was applied worldwide and shared using social media platforms and electronic mail to ∼5000 neurosurgeons. The social media group "Neurosurgery Cocktail" was used to post a link to the questionnaire. In addition, randomly chosen neurosurgery clinics around the world were sent the survey via electronic mail. RESULTS Of the participants, 17.22% had decided on WLST after TBI for >26 patients. Neurosurgeons with more WLST decisions were older, had had more clinical experience and intensive care unit (ICU) training, and were better prepared to involve the family members of TBI patients in their decision-making compared with those with fewer WLST decisions. The respondents stated that the patient's family, ICU consultants, and themselves played the most influential role in the WLST decisions, with the hospital administration, social workers, spiritual caregivers, and nurses having lesser roles. The current and presenting Glasgow coma scale scores, pupillary response, advanced patient age, candidates for a vegetative state, and impaired neurological function were significant factors associated with the WLST decision. CONCLUSIONS To the best of our knowledge, the present study is the first to evaluate neurosurgeons concerning their opinions and behaviors regarding WLST decisions after TBI. Increased patient age, Glasgow coma scale score, pupillary response, the presence of comorbidities, candidacy for a vegetative state, and impaired neurological function were the main factors contributing to the decision for WLST. We also found that the family, ICU consultants, and the attending neurosurgeon had the most effective roles in the decisions regarding WLST.
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Affiliation(s)
- Ismail Bozkurt
- Department of Neurosurgery, Cankiri State Hospital, Cankiri, Turkey.
| | - Giuseppe E Umana
- Department of Neurosurgery, Trauma Center, Gamma Knife Center, Cannizzaro Hospital, Catania, Italy
| | - Harsh Deora
- Department of Neurosurgery, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Jack Wellington
- School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Ebru Karakoc
- Clinic of Anesthesiology and Reanimation and Intensive Care, Cankiri State Hospital, Cankiri, Turkey
| | - Bipin Chaurasia
- Department of Neurosurgery, Neurosurgery Clinic, Birgunj, Nepal
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Maciel CB. Neurologic Outcome Prediction in the Intensive Care Unit. Continuum (Minneap Minn) 2021; 27:1405-1429. [PMID: 34618766 DOI: 10.1212/con.0000000000001053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
PURPOSE OF REVIEW The burden of severe and disabling neurologic injury on survivors, families, and society can be profound. Neurologic outcome prediction, or neuroprognostication, is a complex undertaking with many important ramifications. It allows patients with good prognoses to be supported aggressively, survive, and recover; conversely, it avoids inappropriate prolonged and costly care in those with devastating injuries. RECENT FINDINGS Striving to maintain a high prediction performance during prognostic assessments encompasses acknowledging the shortcomings of this task and the challenges created by advances in medicine, which constantly shift the natural history of neurologic conditions. Embracing the unknowns of outcome prediction and the boundaries of knowledge surrounding neurologic recovery and plasticity is a necessary step toward refining neuroprognostication practices and improving the accuracy of prognostic impressions. The pillars of modern neuroprognostication include comprehensive characterization of neurologic injury burden (primary and secondary injuries), gauging cerebral resilience and estimated neurologic reserve, and tying it all together with individual values surrounding the acceptable extent of disability and the difficulties of an arduous convalescence journey. SUMMARY Comprehensive multimodal frameworks of neuroprognostication using different prognostic tools to portray the burden of neurologic injury coupled with the characterization of individual values and the degree of cerebral reserve and resilience are the cornerstone of modern outcome prediction.
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McCrea MA, Giacino JT, Barber J, Temkin NR, Nelson LD, Levin HS, Dikmen S, Stein M, Bodien YG, Boase K, Taylor SR, Vassar M, Mukherjee P, Robertson C, Diaz-Arrastia R, Okonkwo DO, Markowitz AJ, Manley GT, Adeoye O, Badjatia N, Bullock MR, Chesnut R, Corrigan JD, Crawford K, Duhaime AC, Ellenbogen R, Feeser VR, Ferguson AR, Foreman B, Gardner R, Gaudette E, Goldman D, Gonzalez L, Gopinath S, Gullapalli R, Hemphill JC, Hotz G, Jain S, Keene CD, Korley FK, Kramer J, Kreitzer N, Lindsell C, Machamer J, Madden C, Martin A, McAllister T, Merchant R, Ngwenya LB, Noel F, Nolan A, Palacios E, Perl D, Puccio A, Rabinowitz M, Rosand J, Sander A, Satris G, Schnyer D, Seabury S, Sherer M, Toga A, Valadka A, Wang K, Yue JK, Yuh E, Zafonte R. Functional Outcomes Over the First Year After Moderate to Severe Traumatic Brain Injury in the Prospective, Longitudinal TRACK-TBI Study. JAMA Neurol 2021; 78:982-992. [PMID: 34228047 DOI: 10.1001/jamaneurol.2021.2043] [Citation(s) in RCA: 114] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Importance Moderate to severe traumatic brain injury (msTBI) is a major cause of death and disability in the US and worldwide. Few studies have enabled prospective, longitudinal outcome data collection from the acute to chronic phases of recovery after msTBI. Objective To prospectively assess outcomes in major areas of life function at 2 weeks and 3, 6, and 12 months after msTBI. Design, Setting, and Participants This cohort study, as part of the Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) study, was conducted at 18 level 1 trauma centers in the US from February 2014 to August 2018 and prospectively assessed longitudinal outcomes, with follow-up to 12 months postinjury. Participants were patients with msTBI (Glasgow Coma Scale scores 3-12) extracted from a larger group of patients with mild, moderate, or severe TBI who were enrolled in TRACK-TBI. Data analysis took place from October 2019 to April 2021. Exposures Moderate or severe TBI. Main Outcomes and Measures The Glasgow Outcome Scale-Extended (GOSE) and Disability Rating Scale (DRS) were used to assess global functional status 2 weeks and 3, 6, and 12 months postinjury. Scores on the GOSE were dichotomized to determine favorable (scores 4-8) vs unfavorable (scores 1-3) outcomes. Neurocognitive testing and patient reported outcomes at 12 months postinjury were analyzed. Results A total of 484 eligible patients were included from the 2679 individuals in the TRACK-TBI study. Participants with severe TBI (n = 362; 283 men [78.2%]; median [interquartile range] age, 35.5 [25-53] years) and moderate TBI (n = 122; 98 men [80.3%]; median [interquartile range] age, 38 [25-53] years) were comparable on demographic and premorbid variables. At 2 weeks postinjury, 36 of 290 participants with severe TBI (12.4%) and 38 of 93 participants with moderate TBI (41%) had favorable outcomes (GOSE scores 4-8); 301 of 322 in the severe TBI group (93.5%) and 81 of 103 in the moderate TBI group (78.6%) had moderate disability or worse on the DRS (total score ≥4). By 12 months postinjury, 142 of 271 with severe TBI (52.4%) and 54 of 72 with moderate TBI (75%) achieved favorable outcomes. Nearly 1 in 5 participants with severe TBI (52 of 270 [19.3%]) and 1 in 3 with moderate TBI (23 of 71 [32%]) reported no disability (DRS score 0) at 12 months. Among participants in a vegetative state at 2 weeks, 62 of 79 (78%) regained consciousness and 14 of 56 with available data (25%) regained orientation by 12 months. Conclusions and Relevance In this study, patients with msTBI frequently demonstrated major functional gains, including recovery of independence, between 2 weeks and 12 months postinjury. Severe impairment in the short term did not portend poor outcomes in a substantial minority of patients with msTBI. When discussing prognosis during the first 2 weeks after injury, clinicians should be particularly cautious about making early, definitive prognostic statements suggesting poor outcomes and withdrawal of life-sustaining treatment in patients with msTBI.
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Affiliation(s)
- Michael A McCrea
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee
| | - Joseph T Giacino
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Charlestown, Massachusetts.,Department of Physical Medicine and Rehabilitation, Massachusetts General Hospital, Boston.,Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, Massachusetts
| | - Jason Barber
- Department of Neurological Surgery, University of Washington, Seattle
| | - Nancy R Temkin
- Department of Neurological Surgery, University of Washington, Seattle
| | - Lindsay D Nelson
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee
| | - Harvey S Levin
- Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, Texas
| | - Sureyya Dikmen
- Department of Neurological Surgery, University of Washington, Seattle
| | - Murray Stein
- Department of Family Medicine and Public Health, University of California, San Diego, San Diego
| | - Yelena G Bodien
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Charlestown, Massachusetts.,Department of Physical Medicine and Rehabilitation, Massachusetts General Hospital, Boston.,Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, Massachusetts
| | - Kim Boase
- Department of Neurological Surgery, University of Washington, Seattle
| | - Sabrina R Taylor
- Neurological Surgery, University of California, San Francisco, San Francisco
| | - Mary Vassar
- Neurological Surgery, University of California, San Francisco, San Francisco
| | - Pratik Mukherjee
- Neurological Surgery, University of California, San Francisco, San Francisco
| | - Claudia Robertson
- Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, Texas
| | | | - David O Okonkwo
- Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Amy J Markowitz
- Neurological Surgery, University of California, San Francisco, San Francisco
| | - Geoffrey T Manley
- Neurological Surgery, University of California, San Francisco, San Francisco
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Sonia Jain
- University of California, San Diego, La Jolla
| | | | | | - Joel Kramer
- University of California, San Francisco, San Francisco
| | | | | | | | | | | | | | | | | | | | - Amber Nolan
- University of California, San Francisco, San Francisco
| | - Eva Palacios
- University of California, San Francisco, San Francisco
| | - Daniel Perl
- Uniformed Services University, Bethesda, Maryland
| | - Ava Puccio
- University of Pittsburgh, Pittsburgh, Pennsylvania
| | | | | | | | | | | | | | | | - Arthur Toga
- University of Southern California, Los Angeles
| | | | | | - John K Yue
- University of California, San Francisco, San Francisco
| | - Esther Yuh
- University of California, San Francisco, San Francisco
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Treating Traumatic Brain Injuries with Electroceuticals: Implications for the Neuroanatomy of Consciousness. NEUROSCI 2021. [DOI: 10.3390/neurosci2030018] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
According to the Centers for Disease Control and Prevention (CDC), traumatic brain injury (TBI) is the leading cause of loss of consciousness, long-term disability, and death in children and young adults (age 1 to 44). Currently, there are no United States Food and Drug Administration (FDA) approved pharmacological treatments for post-TBI regeneration and recovery, particularly related to permanent disability and level of consciousness. In some cases, long-term disorders of consciousness (DoC) exist, including the vegetative state/unresponsive wakefulness syndrome (VS/UWS) characterized by the exhibition of reflexive behaviors only or a minimally conscious state (MCS) with few purposeful movements and reflexive behaviors. Electroceuticals, including non-invasive brain stimulation (NIBS), vagus nerve stimulation (VNS), and deep brain stimulation (DBS) have proved efficacious in some patients with TBI and DoC. In this review, we examine how electroceuticals have improved our understanding of the neuroanatomy of consciousness. However, the level of improvements in general arousal or basic bodily and visual pursuit that constitute clinically meaningful recovery on the Coma Recovery Scale-Revised (CRS-R) remain undefined. Nevertheless, these advancements demonstrate the importance of the vagal nerve, thalamus, reticular activating system, and cortico-striatal-thalamic-cortical loop in the process of consciousness recovery.
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Frequency of Withdrawal of Life-Sustaining Therapy for Perceived Poor Neurologic Prognosis. Crit Care Explor 2021; 3:e0487. [PMID: 34278317 PMCID: PMC8280080 DOI: 10.1097/cce.0000000000000487] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Supplemental Digital Content is available in the text. OBJECTIVES: To measure the frequency of withdrawal of life-sustaining therapy for perceived poor neurologic prognosis among decedents in hospitals of different sizes and teaching statuses. DESIGN: We performed a multicenter, retrospective cohort study. SETTING: Four large teaching hospitals, four affiliated small teaching hospitals, and nine affiliated nonteaching hospitals in the United States. PATIENTS: We included a sample of all adult inpatient decedents between August 2017 and August 2019. MEASUREMENTS AND MAIN RESULTS: We reviewed inpatient notes and categorized the immediately preceding circumstances as withdrawal of life-sustaining therapy for perceived poor neurologic prognosis, withdrawal of life-sustaining therapy for nonneurologic reasons, limitations or withholding of life support or resuscitation, cardiac death despite full treatment, or brain death. Of 2,100 patients, median age was 71 years (interquartile range, 60–81 yr), median hospital length of stay was 5 days (interquartile range, 2–11 d), and 1,326 (63%) were treated at four large teaching hospitals. Withdrawal of life-sustaining therapy for perceived poor neurologic prognosis occurred in 516 patients (25%) and was the sole contributing factor to death in 331 (15%). Withdrawal of life-sustaining therapy for perceived poor neurologic prognosis was common in all hospitals: 30% of deaths at large teaching hospitals, 19% of deaths in small teaching hospitals, and 15% of deaths at nonteaching hospitals. Withdrawal of life-sustaining therapy for perceived poor neurologic prognosis happened frequently across all hospital units. Withdrawal of life-sustaining therapy for perceived poor neurologic prognosis contributed to one in 12 deaths in patients without a primary neurologic diagnosis. After accounting for patient and hospital characteristics, significant between-hospital variability in the odds of withdrawal of life-sustaining therapy for perceived poor neurologic prognosis persisted. CONCLUSIONS: A quarter of inpatient deaths in this cohort occurred after withdrawal of life-sustaining therapy for perceived poor neurologic prognosis. The rate of withdrawal of life-sustaining therapy for perceived poor neurologic prognosis occurred commonly in all type of hospital settings. We observed significant unexplained variation in the odds of withdrawal of life-sustaining therapy for perceived poor neurologic prognosis across participating hospitals.
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Claassen J, Akbari Y, Alexander S, Bader MK, Bell K, Bleck TP, Boly M, Brown J, Chou SHY, Diringer MN, Edlow BL, Foreman B, Giacino JT, Gosseries O, Green T, Greer DM, Hanley DF, Hartings JA, Helbok R, Hemphill JC, Hinson HE, Hirsch K, Human T, James ML, Ko N, Kondziella D, Livesay S, Madden LK, Mainali S, Mayer SA, McCredie V, McNett MM, Meyfroidt G, Monti MM, Muehlschlegel S, Murthy S, Nyquist P, Olson DM, Provencio JJ, Rosenthal E, Sampaio Silva G, Sarasso S, Schiff ND, Sharshar T, Shutter L, Stevens RD, Vespa P, Videtta W, Wagner A, Ziai W, Whyte J, Zink E, Suarez JI. Proceedings of the First Curing Coma Campaign NIH Symposium: Challenging the Future of Research for Coma and Disorders of Consciousness. Neurocrit Care 2021; 35:4-23. [PMID: 34236619 PMCID: PMC8264966 DOI: 10.1007/s12028-021-01260-x] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 04/15/2021] [Indexed: 01/04/2023]
Abstract
Coma and disorders of consciousness (DoC) are highly prevalent and constitute a burden for patients, families, and society worldwide. As part of the Curing Coma Campaign, the Neurocritical Care Society partnered with the National Institutes of Health to organize a symposium bringing together experts from all over the world to develop research targets for DoC. The conference was structured along six domains: (1) defining endotype/phenotypes, (2) biomarkers, (3) proof-of-concept clinical trials, (4) neuroprognostication, (5) long-term recovery, and (6) large datasets. This proceedings paper presents actionable research targets based on the presentations and discussions that occurred at the conference. We summarize the background, main research gaps, overall goals, the panel discussion of the approach, limitations and challenges, and deliverables that were identified.
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Affiliation(s)
- Jan Claassen
- Department of Neurology, Columbia University and New York-Presbyterian Hospital, 177 Fort Washington Avenue, MHB 8 Center, Room 300, New York City, NY, 10032, USA.
| | - Yama Akbari
- Departments of Neurology, Neurological Surgery, and Anatomy & Neurobiology and Beckman Laser Institute and Medical Clinic, University of California, Irvine, Irvine, CA, USA
| | - Sheila Alexander
- Acute and Tertiary Care, School of Nursing and Critical Care Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Kathleen Bell
- Department of Physical Medicine and Rehabilitation, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Thomas P Bleck
- Davee Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Melanie Boly
- Department of Neurology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Jeremy Brown
- Office of Emergency Care Research, Division of Clinical Research, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Sherry H-Y Chou
- Departments of Critical Care Medicine, Neurology, and Neurosurgery, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Michael N Diringer
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Brian L Edlow
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Harvard University, Boston, MA, USA
| | - Brandon Foreman
- Departments of Neurology and Rehabilitation Medicine, College of Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Joseph T Giacino
- Department of Physical Medicine and Rehabilitation, Harvard Medical School, Harvard University, Boston, MA, USA
| | - Olivia Gosseries
- GIGA Consciousness After Coma Science Group, University of Liege, Liege, Belgium
| | - Theresa Green
- School of Nursing, Queensland University of Technology, Kelvin Grove, QLD, Australia
| | - David M Greer
- Department of Neurology, School of Medicine, Boston University, Boston, MA, USA
| | - Daniel F Hanley
- Division of Brain Injury Outcomes, Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Jed A Hartings
- Department of Neurosurgery, College of Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Raimund Helbok
- Neurocritical Care Unit, Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - J Claude Hemphill
- Department of Neurology, Weill Institute for Neurosciences, School of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - H E Hinson
- Department of Neurology, School of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Karen Hirsch
- Department of Neurology, Stanford University, Palo Alto, CA, USA
| | - Theresa Human
- Department of Pharmacy, Barnes Jewish Hospital, St. Louis, MO, USA
| | - Michael L James
- Departments of Anesthesiology and Neurology, Duke University, Durham, NC, USA
| | - Nerissa Ko
- Department of Neurology, Weill Institute for Neurosciences, School of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Daniel Kondziella
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Department of Neurology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Sarah Livesay
- College of Nursing, Rush University, Chicago, IL, USA
| | - Lori K Madden
- Center for Nursing Science, University of California, Davis, Sacramento, CA, USA
| | - Shraddha Mainali
- Department of Neurology, The Ohio State University, Columbus, OH, USA
| | - Stephan A Mayer
- Department of Neurology, New York Medical College, Valhalla, NY, USA
| | - Victoria McCredie
- Interdepartmental Division of Critical Care, Department of Respirology, University of Toronto, Toronto, ON, Canada
| | - Molly M McNett
- College of Nursing, The Ohio State University, Columbus, OH, USA
| | - Geert Meyfroidt
- Department of Intensive Care Medicine, University Hospitals Leuven and University of Leuven, Leuven, Belgium
| | - Martin M Monti
- Departments of Neurosurgery and Psychology, Brain Injury Research Center, University of California, Los Angeles, Los Angeles, CA, USA
| | - Susanne Muehlschlegel
- Departments of Neurology, Anesthesiology/Critical Care, and Surgery, Medical School, University of Massachusetts, Worcester, MA, USA
| | - Santosh Murthy
- Department of Neurology, Weill Cornell Medical College, New York City, NY, USA
| | - Paul Nyquist
- Division of Neurosciences Critical Care, Departments of Anesthesiology and Critical Care Medicine, Neurology, and Neurosurgery, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - DaiWai M Olson
- Departments of Neurology and Neurosurgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - J Javier Provencio
- Departments of Neurology and Neuroscience, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Eric Rosenthal
- Department of Neurology, Harvard Medical School, Harvard University, Boston, MA, USA
| | - Gisele Sampaio Silva
- Department of Neurology, Albert Einstein Israelite Hospital and Universidade Federal de São Paulo, São Paulo, Brazil
| | - Simone Sarasso
- Department of Biomedical and Clinical Sciences "L. Sacco", Università degli Studi di Milano, Milan, Italy
| | - Nicholas D Schiff
- Department of Neurology and Brain Mind Research Institute, Weill Cornell Medicine, Cornell University, New York City, NY, USA
| | - Tarek Sharshar
- Department of Intensive Care, Paris Descartes University, Paris, France
| | - Lori Shutter
- Departments of Critical Care Medicine, Neurology, and Neurosurgery, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Robert D Stevens
- Division of Neurosciences Critical Care, Departments of Anesthesiology and Critical Care Medicine, Neurology, and Neurosurgery, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Paul Vespa
- Departments of Neurosurgery and Neurology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Walter Videtta
- National Hospital Alejandro Posadas, Buenos Aires, Argentina
| | - Amy Wagner
- Department of Physical Medicine and Rehabilitation, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Wendy Ziai
- Division of Neurosciences Critical Care, Departments of Anesthesiology and Critical Care Medicine, Neurology, and Neurosurgery, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - John Whyte
- Moss Rehabilitation Research Institute, Elkins Park, PA, USA
| | - Elizabeth Zink
- Division of Neurosciences Critical Care, Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Jose I Suarez
- Division of Neurosciences Critical Care, Departments of Anesthesiology and Critical Care Medicine, Neurology, and Neurosurgery, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
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Giacino JT, Bodien YG, Zuckerman D, Henderson J, Schiff ND, Fins JJ. Empiricism and Rights Justify the Allocation of Health Care Resources to Persons with Disorders of Consciousness. AJOB Neurosci 2021; 12:169-171. [PMID: 33960891 DOI: 10.1080/21507740.2021.1904055] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Affiliation(s)
| | - Yelena G Bodien
- Harvard Medical School.,Spaulding Rehabilitation Hospital.,Massachusetts General Hospital
| | | | | | | | - Joseph J Fins
- Weill Cornell Medical College.,The Rockefeller University.,Yale Law School
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Azad TD. Opinion & Special Articles: Shared Decision-Making During the COVID-19 Pandemic: Three Bullets in 3 Hemispheres. Neurology 2021; 96:e2558-e2560. [PMID: 33692167 DOI: 10.1212/wnl.0000000000011811] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Patients with traumatic brain injury may be dependent on the decision-making of their families. Restrictive visitation policies implemented during the coronavirus disease 2019 (COVID-19) pandemic disproportionately affect these patients and their families. This narrative aims to illustrate this phenomenon and catalyze discussions regarding the need for careful evaluation of restrictive family visitation policies and exceptions that may be required for patients with brain injuries.
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Affiliation(s)
- Tej D Azad
- From the Department of Neurosurgery, Johns Hopkins Hospital, Baltimore, MD.
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Zhu Y, Zhu X, Xu L, Deng M. Clinical Factors Influencing End-of-Life Care in a Chinese Pediatric Intensive Care Unit: A Retrospective, post-hoc Study. Front Pediatr 2021; 9:601782. [PMID: 33898354 PMCID: PMC8058173 DOI: 10.3389/fped.2021.601782] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Accepted: 03/15/2021] [Indexed: 11/13/2022] Open
Abstract
Objective: End-of-life(EOL) care decision-making for infants and children is a painful experience. The study aimed to explore the clinical factors influencing the EOL care to withhold/withdraw life-sustaining treatment (WLST) in Chinese pediatric intensive care unit (PICU). Methods: A 14-year retrospective study (2006-2019) for pediatric patients who died in PICU was conducted. Based on the mode of death, patients were classified into WLST group (death after WLST) and fCPR group (death after full intervention, including cardiopulmonary resuscitation). Intergroup differences in the epidemiological and clinical factors were determined. Results: There were 715 patients enrolled in this study. Of these patients, 442 (61.8%) died after WLST and 273 (38.2%) died after fCPR. Patients with previous hospitalizations or those who had been transferred from other hospitals more frequently chose WLST than fCPR (both P < 0.01), and the mean PICU stay duration was significantly longer in the WLST group (P < 0.05). WLST patients were more frequently complicated with chronic underlying disease, especially tumor (P < 0.01). Sepsis, diarrhea, and cardiac attack (all P < 0.05) were more frequent causes of death in the fCPR group, whereas tumor as a direct cause of death was more frequently seen in the WLST group. Logistic regression analysis demonstrated that previous hospitalization and underlying diseases diagnosed before admission were strongly associated with EOL care with WLST decision (OR: 1.6; P < 0.05 and OR: 1.6; P < 0.01, respectively). Conclusions: Pediatric patients with previous hospitalization and underlying diseases diagnosed before admission were associated with the EOL care to WLST.
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Affiliation(s)
- Yueniu Zhu
- Department of Pediatric Critical Care Medicine, Xinhua Hospital, Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Xiaodong Zhu
- Department of Pediatric Critical Care Medicine, Xinhua Hospital, Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Lili Xu
- Department of Pediatric Critical Care Medicine, Xinhua Hospital, Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Mengyan Deng
- Department of Pediatric Critical Care Medicine, Xinhua Hospital, Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
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