Withdrawal of Life-supporting Treatment in Severe Traumatic Brain Injury

Predictive Models of Long-Term Outcome in Patients with Moderate to Severe Traumatic Brain Injury are Biased Toward Mortality Prediction

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.

Influence of health insurance on withdrawal of life sustaining treatment for patients with isolated traumatic brain injury: a retrospective multi-center observational cohort study

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.

Bioethics and Neurosurgery: An Overview of Existing and Emerging Topics for the Practicing Neurosurgeon

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.

Limitation of life sustaining therapy in disorders of consciousness: ethics and practice

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.

Traumatic Brain Injury as an Independent Predictor of Futility in the Early Resuscitation of Patients in Hemorrhagic Shock

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.

Prognostication in Neurocritical Care

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.

Evaluation of ChatGPT in Predicting 6-Month Outcomes After Traumatic Brain Injury

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.

Effect of PCC on outcomes of severe traumatic brain injury patients on preinjury anticoagulation

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.

Recovery Potential in Patients Who Died After Withdrawal of Life-Sustaining Treatment: A TRACK-TBI Propensity Score Analysis

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.

Machine Learning Identifies Variation in Timing of Palliative Care Consultations Among Traumatic Brain Injury Patients

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.

Comparative Analysis of Clinical Severity and Outcomes in Penetrating Versus Blunt Traumatic Brain Injury Propensity Matched Cohorts

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.

Guidelines for Neuroprognostication in Critically Ill Adults with Moderate-Severe Traumatic Brain Injury

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.

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

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.

Timing of withdrawal of life-sustaining therapy in traumatic brain injury: exploring indicators of poor prognosis in adult and geriatric populations

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.

Vision Transformer-based Decision Support for Neurosurgical Intervention in Acute Traumatic Brain Injury: Automated Surgical Intervention Support Tool

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.

Withdrawal of Life-Sustaining Treatment for Pediatric Patients With Severe Traumatic Brain Injury

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.

Resting-State Functional Magnetic Resonance Imaging Network Association With Mortality, Epilepsy, Cognition, and Motor Two-Year Outcomes in Suspected Severe Neonatal Acute Brain Injury

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.

Prognostic Value of Frailty for Outcome Following Traumatic Brain Injury: A Systematic Review and Meta-Analysis

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.

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

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.

Factors influencing withdrawal of life-supporting treatment in cervical spinal cord injury: a large multicenter observational cohort study

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.

Caring for Ourselves, Supporting Anti-Racist Programming in Medicine

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.

The Variation of Withdrawal of Life Sustaining Therapy in Older Adults With Traumatic Brain Injury

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.

Ethical Considerations in Neuroprognostication Following Acute Brain Injury

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.

Prognostic Language in Critical Neurologic Illness: A Multicenter Mixed-Methods Study

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.

The final decision among the injured elderly, to stop or to continue? Predictors of withdrawal of life supporting treatment

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.

Predictors of In-Hospital Mortality and Home Discharge in Patients with Aneurysmal Subarachnoid Hemorrhage: A 4-Year Retrospective Analysis

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.

Definitely, Maybe: Helping Patients Make Decisions about Surgery When Prognosis Is Uncertain

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.

Performance of CRASH and IMPACT Prognostic Models for Traumatic Brain Injury at 12 and 24 Months Post-Injury

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.

Traumatic brain injury: progress and challenges in prevention, clinical care, and research

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.

The Characteristics of Withdrawal or Withholding of Life-Sustaining Treatment in Severe Traumatic Brain Injury: A Single Japanese Institutional Study

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.

Predictors for Withdrawal of Life-Sustaining Therapies in Patients With Traumatic Brain Injury: A Retrospective Trauma Quality Improvement Program Database Study

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.

Palliative Care Consultations in Patients with Severe Traumatic Brain Injury: Who Receives Palliative Care Consultations and What Does that Mean for Utilization?

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.

Race and insurance status outcome disparities following splenectomy in trauma patients are reduced in larger hospitals. A cross-sectional study

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.

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Mortality is less frequent in white patients, and more frequent in uninsured patients.

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Black patients were more likely to experience major complications following splenectomy.

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In hospitals with greater than 600 beds, there were no associations between race and mortality following splenectomy.

Prognostication and shared decision making in neurocritical care

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.

Decoding health status transitions of over 200 000 patients with traumatic brain injury from preceding injury to the injury event

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.

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

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.

The Curing Coma Campaign International Survey on Coma Epidemiology, Evaluation, and Therapy (COME TOGETHER)

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.

Factors Affecting Neurosurgeons' Decisions to Forgo Life-Sustaining Treatments After Traumatic Brain Injury

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.

Neurologic Outcome Prediction in the Intensive Care Unit

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.

Functional Outcomes Over the First Year After Moderate to Severe Traumatic Brain Injury in the Prospective, Longitudinal TRACK-TBI Study

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.

Treating Traumatic Brain Injuries with Electroceuticals: Implications for the Neuroanatomy of Consciousness

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.

Frequency of Withdrawal of Life-Sustaining Therapy for Perceived Poor Neurologic Prognosis

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.

Proceedings of the First Curing Coma Campaign NIH Symposium: Challenging the Future of Research for Coma and Disorders of Consciousness

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.

Opinion & Special Articles: Shared Decision-Making During the COVID-19 Pandemic: Three Bullets in 3 Hemispheres

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.

Clinical Factors Influencing End-of-Life Care in a Chinese Pediatric Intensive Care Unit: A Retrospective, post-hoc Study

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.