Gap Analysis Regarding Prognostication in Neurocritical Care: A Joint Statement from the German Neurocritical Care Society and the Neurocritical Care Society

Genetic Variants ε2 and ε4 of APOE Predict Mortality and Poor Outcome Independently in Spontaneous Intracerebral Hemorrhage Within the Chinese Han Population

The heightened mortality and disability rates, coupled with restricted neurological recovery post intracerebral hemorrhage (ICH), have sparked considerable attention toward its treatment and results. Simultaneously, the influence of the APOE gene on ICH prognosis has been well-documented. This research aimed to explore the relationship between specific APOE alleles in the present cohort and the incidences of mortality, recurrence, and adverse prognosis, as determined by neurological function assessments in ICH patients. Data on patients diagnosed with ICH and hospitalized in the Department of Neurology at our institution from October 2021 to March 2022 were collected, including determining their APOE genotypes. A 1-year follow-up was conducted to evaluate mortality, ICH recurrence, and modified Rankin Scale (mRS) scores at 3 and 12 months. Poor prognosis was defined as an mRS score of ≥ 3. Initially, we analyzed the relationships between different APOE alleles and mortality, recurrence, and poor prognosis. Subsequently, we explored additional factors influencing each prognostic outcome and conducted multivariate analysis to identify independent risk factors. An analysis was conducted on 289 patients diagnosed with ICH. The presence of the ε2 allele was found to be a significant independent predictor for unfavorable outcomes at both 3 months (p = 0.022, OR = 2.138, 95% CI [2.041, 3.470]) and 1 year (p = 0.020, OR = 5.116, 95% CI [5.044, 5.307]). Moreover, the ε4 allele was established as an independent risk factor for ICH recurrence within 1 year (p = 0.025, OR = 2.326, 95% CI [1.163, 2.652]), as well as for mortality at 3 months (p = 0.037, OR = 4.250, 95% CI [4.068, 4.920]) and 1 year (p = 0.023, OR = 4.109, 95% CI [4.016, 4.739]). In conclusions, Both APOE ε2 and ε4 variants independently heighten mortality risk, recurrence, and poor prognosis after ICH. The substantial influence underscores the need for additional investigation into the impact of APOE genotype on ICH prognosis.

Research Priorities in Neuropalliative Care: A Consensus Statement From the International Neuropalliative Care Society

Importance

The integration of palliative care in neurology, or neuropalliative care, is an emerging area of practice focused on holistically improving quality of life and reducing the burden of suffering for people living with serious neurologic disease and their care partners. Major neurology and palliative care societies have recognized the need to advance primary and specialty palliative care services for people with neurologic disease. However, research to support this work is in its early stages.

Observations

The International Neuropalliative Care Society Research Committee convened an interdisciplinary panel of experts, including clinicians, scientists, people with neurologic disease, and care partners, to identify priority research areas for the advancement of neuropalliative care as a field. Three priority areas highlighted in this review include (1) patient- and care partner-centered symptoms and outcomes specific to neurologic illness and tools for their assessment, (2) development of effective neuropalliative care interventions and delivery models, and (3) methods to support the ability to foster, deliver, and measure goal-concordant care over time.

Conclusions and Relevance

This Special Communication outlines some of the most pressing neuropalliative care research needs, the advancement of which will best serve patients of all ages living with serious neurologic diseases and their care partners. Research funding mechanisms are needed to support and sustain impactful work in this field.

Timing of neuroprognostication in the ICU

PURPOSE OF REVIEW

Neuroprognostication after acute brain injury (ABI) is complex. In this review, we examine the threats to accurate neuroprognostication, discuss strategies to mitigate the self-fulfilling prophecy, and how to approach the indeterminate prognosis.

RECENT FINDINGS

The goal of neuroprognostication is to provide a timely and accurate prediction of a patient's neurologic outcome so treatment can proceed in accordance with a patient's values and preferences. Neuroprognostication should be delayed until at least 72 h after injury and/or only when the necessary prognostic data is available to avoid early withdraw life-sustaining treatment on patients who may otherwise survive with a good outcome. Clinicians should be aware of the limitations of available predictors and prognostic models, the role of flawed heuristics and the self-fulfilling prophecy, and the influence of surrogate decision-maker bias on end-of-life decisions.

SUMMARY

The approach to neuroprognostication after ABI should be systematic, use highly reliable multimodal data, and involve experts to minimize the risk of erroneous prediction and perpetuating the self-fulfilling prophecy. Even when such standards are rigorously upheld, the prognosis may be indeterminate. In such cases, clinicians should engage in shared decision-making with surrogates and consider the use of a time-limited trial.

Prognostic biomarkers of intracerebral hemorrhage identified using targeted proteomics and machine learning algorithms

Early prognostication of patient outcomes in intracerebral hemorrhage (ICH) is critical for patient care. We aim to investigate protein biomarkers' role in prognosticating outcomes in ICH patients. We assessed 22 protein biomarkers using targeted proteomics in serum samples obtained from the ICH patient dataset (N = 150). We defined poor outcomes as modified Rankin scale score of 3-6. We incorporated clinical variables and protein biomarkers in regression models and random forest-based machine learning algorithms to predict poor outcomes and mortality. We report Odds Ratio (OR) or Hazard Ratio (HR) with 95% Confidence Interval (CI). We used five-fold cross-validation and bootstrapping for internal validation of prediction models. We included 149 patients for 90-day and 144 patients with ICH for 180-day outcome analyses. In multivariable logistic regression, UCH-L1 (adjusted OR 9.23; 95%CI 2.41-35.33), alpha-2-macroglobulin (aOR 5.57; 95%CI 1.26-24.59), and Serpin-A11 (aOR 9.33; 95%CI 1.09-79.94) were independent predictors of 90-day poor outcome; MMP-2 (aOR 6.32; 95%CI 1.82-21.90) was independent predictor of 180-day poor outcome. In multivariable Cox regression models, IGFBP-3 (aHR 2.08; 95%CI 1.24-3.48) predicted 90-day and MMP-9 (aOR 1.98; 95%CI 1.19-3.32) predicted 180-day mortality. Machine learning identified additional predictors, including haptoglobin for poor outcomes and UCH-L1, APO-C1, and MMP-2 for mortality prediction. Overall, random forest models outperformed regression models for predicting 180-day poor outcomes (AUC 0.89), and 90-day (AUC 0.81) and 180-day mortality (AUC 0.81). Serum biomarkers independently predicted short-term poor outcomes and mortality after ICH. Further research utilizing a multi-omics platform and temporal profiling is needed to explore additional biomarkers and refine predictive models for ICH prognosis.

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.

Emergent Management of Spontaneous Subarachnoid Hemorrhage

OBJECTIVE

Spontaneous subarachnoid hemorrhage (SAH) carries high morbidity and mortality rates, and the emergent management of this disease can make a large impact on patient outcome. The purpose of this article is to provide a pragmatic overview of the emergent management of SAH.

LATEST DEVELOPMENTS

Recent trials have influenced practice around the use of antifibrinolytics, the timing of aneurysm securement, the recognition of cerebral edema and focus on avoiding a lower limit of perfusion, and the detection and prevention of delayed cerebral ischemia. Much of the acute management of SAH can be protocolized, as demonstrated by two updated guidelines published by the American Heart Association/American Stroke Association and the Neurocritical Care Society in 2023. However, the gaps in evidence lead to clinical equipoise in some aspects of critical care management.

ESSENTIAL POINTS

In acute management, there is an urgency to differentiate the etiology of SAH and take key emergent actions including blood pressure management and coagulopathy reversal. The critical care management of SAH is similar to that of other acute brain injuries, with the addition of detecting and treating delayed cerebral ischemia. Strategies for the detection and treatment of delayed cerebral ischemia are limited by disordered consciousness and may be augmented by monitoring and imaging technology.

Emergent Management of Hypoxic-Ischemic Brain Injury

OBJECTIVE

This article outlines interventions used to improve outcomes for patients with hypoxic-ischemic brain injury after cardiac arrest.

LATEST DEVELOPMENTS

Emergent management of patients after cardiac arrest requires prevention and treatment of primary and secondary brain injury. Primary brain injury is minimized by excellent initial resuscitative efforts. Secondary brain injury prevention requires the detection and correction of many pathophysiologic processes that may develop in the hours to days after the initial arrest. Key physiologic parameters important to secondary brain injury prevention include optimization of mean arterial pressure, cerebral perfusion, oxygenation and ventilation, intracranial pressure, temperature, and cortical hyperexcitability. This article outlines recent data regarding the treatment and prevention of secondary brain injury. Different patients likely benefit from different treatment strategies, so an individualized approach to treatment and prevention of secondary brain injury is advisable. Clinicians must use multimodal sources of data to prognosticate outcomes after cardiac arrest while recognizing that all prognostic tools have shortcomings.

ESSENTIAL POINTS

Neurologists should be involved in the postarrest care of patients with hypoxic-ischemic brain injury to improve their outcomes. Postarrest care requires nuanced and patient-centered approaches to the prevention and treatment of primary and secondary brain injury and neuroprognostication.

Clinicians' approach to predicting post-cardiac arrest outcomes for patients enrolled in a United States clinical trial

PURPOSE

Perceived poor prognosis can lead to withdrawal of life-sustaining therapies (WLST) in patients who might otherwise recover. We characterized clinicians' approach to post-arrest prognostication in a multicenter clinical trial.

METHODS

Semi-structured interviews were conducted with clinicians who treated a comatose post-cardiac arrest patient enrolled in the Influence of Cooling Duration on Efficacy in Cardiac Arrest Patients (ICECAP) trial (NCT04217551). Two authors independently analyzed each interview using inductive and deductive coding. The clinician reported how they arrived at a prognosis for the specific patient. We summarized the frequency with which clinicians reported using objective diagnostics to formulate their prognosis, and compared the reported approaches to established guidelines. Each respondent provided demographic information and described local neuroprognostication practices.

RESULTS

We interviewed 30 clinicians at 19 US hospitals. Most claimed adherence to local hospital neuroprognostication protocols (n = 19). Prognostication led to WLST for perceived poor neurological prognosis in 15/30 patients, of whom most showed inconsistencies with guidelines or trial recommendations, respectively. In 10/15 WLST cases, clinicians reported relying on multimodal testing. A prevalent theme was the use of "clinical gestalt," defined as prognosticating based on a patient's overall appearance or a subjective impression in the absence of objective data. Many clinicians (21/30) reported using clinical gestalt for initial prognostication, with 9/21 expressing high confidence initially.

CONCLUSION

Clinicians in our study state they follow neuroprognostication guidelines in general but often do not do so in actual practice. They reported clinical gestalt frequently informed early, highly confident prognostic judgments, and few objective tests changed initial impressions. Subjective prognostication may undermine well-designed trials.

Contemporary management of aneurysmal subarachnoid haemorrhage. An update for the intensivist

Aneurysmal subarachnoid haemorrhage (aSAH) is a rare yet profoundly debilitating condition associated with high global case fatality and morbidity rates. The key determinants of functional outcome include early brain injury, rebleeding of the ruptured aneurysm and delayed cerebral ischaemia. The only effective way to reduce the risk of rebleeding is to secure the ruptured aneurysm quickly. Prompt diagnosis, transfer to specialized centers, and meticulous management in the intensive care unit (ICU) significantly improved the prognosis of aSAH. Recently, multimodality monitoring with specific interventions to correct pathophysiological imbalances has been proposed. Vigilance extends beyond intracranial concerns to encompass systemic respiratory and haemodynamic monitoring, as derangements in these systems can precipitate secondary brain damage. Challenges persist in treating aSAH patients, exacerbated by a paucity of robust clinical evidence, with many interventions showing no benefit when tested in rigorous clinical trials. Given the growing body of literature in this field and the issuance of contemporary guidelines, our objective is to furnish an updated review of essential principles of ICU management for this patient population. Our review will discuss the epidemiology, initial stabilization, treatment strategies, long-term prognostic factors, the identification and management of post-aSAH complications. We aim to offer practical clinical guidance to intensivists, grounded in current evidence and expert clinical experience, while adhering to a concise format.

Guidelines for Neuroprognostication in Critically Ill Adults with Intracerebral Hemorrhage

BACKGROUND

The objective of this document is to provide recommendations on the formal reliability of major clinical predictors often associated with intracerebral hemorrhage (ICH) neuroprognostication.

METHODS

A narrative systematic review was completed using the Grading of Recommendations Assessment, Development, and Evaluation methodology and the Population, Intervention, Comparator, Outcome, Timing, Setting questions. Predictors, which included both individual clinical variables and prediction models, were selected based on clinical relevance and attention in the literature. Following construction of the evidence profile and summary of findings, recommendations were based on Grading of Recommendations Assessment, Development, and Evaluation criteria. Good practice statements addressed essential principles of neuroprognostication that could not be framed in the Population, Intervention, Comparator, Outcome, Timing, Setting format.

RESULTS

Six candidate clinical variables and two clinical grading scales (the original ICH score and maximally treated ICH score) were selected for recommendation creation. A total of 347 articles out of 10,751 articles screened met our eligibility criteria. Consensus statements of good practice included deferring neuroprognostication-aside from the most clinically devastated patients-for at least the first 48-72 h of intensive care unit admission; understanding what outcomes would have been most valued by the patient; and counseling of patients and surrogates whose ultimate neurological recovery may occur over a variable period of time. Although many clinical variables and grading scales are associated with ICH poor outcome, no clinical variable alone or sole clinical grading scale was suggested by the panel as currently being reliable by itself for use in counseling patients with ICH and their surrogates, regarding functional outcome at 3 months and beyond or 30-day mortality.

CONCLUSIONS

These guidelines provide recommendations on the formal reliability of predictors of poor outcome in the context of counseling patients with ICH and surrogates and suggest broad principles of neuroprognostication. Clinicians formulating their judgments of prognosis for patients with ICH should avoid anchoring bias based solely on any one clinical variable or published clinical grading scale.

Indian Society of Critical Care Medicine and Indian Association of Palliative Care Expert Consensus and Position Statements for End-of-life and Palliative Care in the Intensive Care Unit

End-of-life care (EOLC) exemplifies the joint mission of intensive and palliative care (PC) in their human-centeredness. The explosion of technological advances in medicine must be balanced with the culture of holistic care. Inevitably, it brings together the science and the art of medicine in their full expression. High-quality EOLC in the ICU is grounded in evidence, ethical principles, and professionalism within the framework of the Law. Expert professional statements over the last two decades in India were developed while the law was evolving. Recent landmark Supreme Court judgments have necessitated a review of the clinical pathway for EOLC outlined in the previous statements. Much empirical and interventional evidence has accumulated since the position statement in 2014. This iteration of the joint Indian Society of Critical Care Medicine-Indian Association of Palliative Care (ISCCM-IAPC) Position Statement for EOLC combines contemporary evidence, ethics, and law for decision support by the bedside in Indian ICUs.

How to cite this article

Mani RK, Bhatnagar S, Butola S, Gursahani R, Mehta D, Simha S, et al. Indian Society of Critical Care Medicine and Indian Association of Palliative Care Expert Consensus and Position Statements for End-of-life and Palliative Care in the Intensive Care Unit. Indian J Crit Care Med 2024;28(3):200-250.

Multivariable Prediction Models for Traumatic Spinal Cord Injury: A Systematic Review

Background

Traumatic spinal cord injuries (TSCI) greatly affect the lives of patients and their families. Prognostication may improve treatment strategies, health care resource allocation, and counseling. Multivariable clinical prediction models (CPMs) for prognosis are tools that can estimate an absolute risk or probability that an outcome will occur.

Objectives

We sought to systematically review the existing literature on CPMs for TSCI and critically examine the predictor selection methods used.

Methods

We searched MEDLINE, PubMed, Embase, Scopus, and IEEE for English peer-reviewed studies and relevant references that developed multivariable CPMs to prognosticate patient-centered outcomes in adults with TSCI. Using narrative synthesis, we summarized the characteristics of the included studies and their CPMs, focusing on the predictor selection process.

Results

We screened 663 titles and abstracts; of these, 21 full-text studies (2009-2020) consisting of 33 distinct CPMs were included. The data analysis domain was most commonly at a high risk of bias when assessed for methodological quality. Model presentation formats were inconsistently included with published CPMs; only two studies followed established guidelines for transparent reporting of multivariable prediction models. Authors frequently cited previous literature for their initial selection of predictors, and stepwise selection was the most frequent predictor selection method during modelling.

Conclusion

Prediction modelling studies for TSCI serve clinicians who counsel patients, researchers aiming to risk-stratify participants for clinical trials, and patients coping with their injury. Poor methodological rigor in data analysis, inconsistent transparent reporting, and a lack of model presentation formats are vital areas for improvement in TSCI CPM research.

Predicting 30-day mortality in intensive care unit patients with ischaemic stroke or intracerebral haemorrhage

BACKGROUND

Stroke patients admitted to an intensive care unit (ICU) follow a particular survival pattern with a high short-term mortality, but if they survive the first 30 days, a relatively favourable subsequent survival is observed.

OBJECTIVES

The development and validation of two prognostic models predicting 30-day mortality for ICU patients with ischaemic stroke and for ICU patients with intracerebral haemorrhage (ICH), analysed separately, based on parameters readily available within 24 h after ICU admission, and with comparison with the existing Acute Physiology and Chronic Health Evaluation IV (APACHE-IV) model.

DESIGN

Observational cohort study.

SETTING

All 85 ICUs participating in the Dutch National Intensive Care Evaluation database.

PATIENTS

All adult patients with ischaemic stroke or ICH admitted to these ICUs between 2010 and 2019.

MAIN OUTCOME MEASURES

Models were developed using logistic regressions and compared with the existing APACHE-IV model. Predictive performance was assessed using ROC curves, calibration plots and Brier scores.

RESULTS

We enrolled 14 303 patients with stroke admitted to ICU: 8422 with ischaemic stroke and 5881 with ICH. Thirty-day mortality was 27% in patients with ischaemic stroke and 41% in patients with ICH. Important factors predicting 30-day mortality in both ischaemic stroke and ICH were age, lowest Glasgow Coma Scale (GCS) score in the first 24 h, acute physiological disturbance (measured using the Acute Physiology Score) and the application of mechanical ventilation. Both prognostic models showed high discrimination with an AUC 0.85 [95% confidence interval (CI), 0.84 to 0.87] for patients with ischaemic stroke and 0.85 (0.83 to 0.86) in ICH. Calibration plots and Brier scores indicated an overall good fit and good predictive performance. The APACHE-IV model predicting 30-day mortality showed similar performance with an AUC of 0.86 (95% CI, 0.85 to 0.87) in ischaemic stroke and 0.87 (0.86 to 0.89) in ICH.

CONCLUSION

We developed and validated two prognostic models for patients with ischaemic stroke and ICH separately with a high discrimination and good calibration to predict 30-day mortality within 24 h after ICU admission.

TRIAL REGISTRATION

Trial registration: Dutch Trial Registry ( https://www.trialregister.nl/ ); identifier: NTR7438.

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.

Clinical Grading Scales and Neuroprognostication in Acute Brain Injury

Prediction of neurological clinical outcome after acute brain injury is critical because it helps guide discussions with patients and families and informs treatment plans and allocation of resources. Numerous clinical grading scales have been published that aim to support prognostication after acute brain injury. However, the development and validation of clinical scales lack a standardized approach. This in turn makes it difficult for clinicians to rely on prognostic grading scales and to integrate them into clinical practice. In this review, we discuss quality measures of score development and validation and summarize available scales to prognosticate outcomes after acute brain injury. These include scales developed for patients with coma, cardiac arrest, ischemic stroke, nontraumatic intracerebral hemorrhage, subarachnoid hemorrhage, and traumatic brain injury; for each scale, we discuss available validation studies.

Cognitive Biases and Shared Decision Making in Acute Brain Injury

Many patients hospitalized after severe acute brain injury are comatose and require life-sustaining therapies. Some of these patients make favorable recoveries with continued intensive care, while others do not. In addition to providing medical care, clinicians must guide surrogate decision makers through high-stakes, emotionally charged decisions about whether to continue life-sustaining therapies. These consultations require clinicians first to assess a patient's likelihood of recovery given continued life-sustaining therapies (i.e., prognosticate), then to communicate that prediction to surrogates, and, finally, to elicit and interpret the patient's preferences. At each step, both clinicians and surrogates are vulnerable to flawed decision making. Clinicians can be imprecise, biased, and overconfident when prognosticating after brain injury. Surrogates can misperceive the choice and misunderstand or misrepresent a patient's wishes, which may never have been communicated clearly. These biases can undermine the ability to reach choices congruent with patients' preferences through shared decision making (SDM). Decision science has extensively studied these biases. In this article, we apply that research to improving SDM for patients who are comatose after acute brain injury. After introducing SDM and the medical context, we describe principal decision science results as they relate to neurologic prognostication and end-of-life decisions, by both clinicians and surrogates. Based on research regarding general processes that can produce imprecise, biased, and overconfident prognoses, we propose interventions that could improve SDM, supporting clinicians and surrogates in making these challenging decisions.

Early Shared Decision-Making for Older Adults with Traumatic Brain Injury: Using Time-Limited Trials and Understanding Their Limitations

Older adults account for a disproportionate share of the morbidity and mortality after traumatic brain injury (TBI). Predicting functional and cognitive outcomes for individual older adults after TBI is challenging in the acute phase of injury. Given that neurologic recovery is possible and uncertain, life-sustaining therapy may be pursued initially, even if for some, there is a risk of survival to an undesired level of disability or dependence. Experts recommend early conversations about goals of care after TBI, but evidence-based guidelines for these discussions or for the optimal method for communicating prognosis are limited. The time-limited trial (TLT) model may be an effective strategy for managing prognostic uncertainty after TBI. TLTs can provide a framework for early management: specific treatments or procedures are used for a defined period of time while monitoring for an agreed-upon outcome. Outcome measures, including signs of worsening and improvement, are defined at the outset of the trial. In this Viewpoint article, we discuss the use of TLTs for older adults with TBI, their potential benefits, and current challenges to their application. Three main barriers limit the implementation of TLTs in these scenarios: inadequate models for prognostication; cognitive biases faced by clinicians and surrogate decision-makers, which may contribute to prognostic discordance; and ambiguity regarding appropriate endpoints for the TLT. Further study is needed to understand clinician behaviors and surrogate preferences for prognostic communication and how to optimally integrate TLTs into the care of older adults with TBI.

Do Neuroprognostic Studies Account for Self-Fulfilling Prophecy Bias in Their Methodology? The SPIN Protocol for a Systematic Review

Self-fulfilling prophecy bias occurs when a perceived prognosis leads to treatment decisions that inherently modify outcomes of a patient, and thus, overinflate the prediction performance of prognostic methods. The goal of this series of systematic reviews is to characterize the extent to which neuroprognostic studies account for the potential impact of self-fulfilling prophecy bias in their methodology by assessing their adequacy of disclosing factors relevant to this bias.

Methods

Studies evaluating the prediction performance of neuroprognostic tools in cardiac arrest, malignant ischemic stroke, traumatic brain injury, subarachnoid hemorrhage, and spontaneous intracerebral hemorrhage will be identified through PubMed, Cochrane, and Embase database searches. Two reviewers blinded to each other's assessment will perform screening and data extraction of included studies using Distiller SR and following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We will abstract data pertinent to the methodology of the studies relevant to self-fulfilling prophecy bias.

Results

We will conduct a descriptive analysis of the data. We will summarize the reporting of mortality according to timing and mode of death, rates of exposure to withdrawal of life-sustaining therapy, reasoning behind limitations of supportive care, systematic use of standardized neuroprognostication algorithms and whether the tool being investigated is part of such assessments, and blinding of treatment team to results of neuroprognostic test being evaluated.

CONCLUSIONS

We will identify if neuroprognostic studies have been transparent in their methodology to factors that affect the self-fulfilling prophecy bias. Our results will serve as the foundation for standardization of neuroprognostic study methodologies by refining the quality of the data derived from such studies.

Neuroprognostication in the Post Cardiac Arrest Patient: A Canadian Cardiovascular Society Position Statement

Cardiac arrest (CA) is associated with a low rate of survival with favourable neurologic recovery. The most common mechanism of death after successful resuscitation from CA is withdrawal of life-sustaining measures on the basis of perceived poor neurologic prognosis due to underlying hypoxic-ischemic brain injury. Neuroprognostication is an important component of the care pathway for CA patients admitted to hospital but is complex, challenging, and often guided by limited evidence. Using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system to evaluate the evidence underlying factors or diagnostic modalities available to determine prognosis, recommendations were generated in the following domains: (1) circumstances immediately after CA; (2) focused neurologic exam; (3) myoclonus and seizures; (4) serum biomarkers; (5) neuroimaging; (6) neurophysiologic testing; and (7) multimodal neuroprognostication. This position statement aims to serve as a practical guide to enhance in-hospital care of CA patients and emphasizes the adoption of a systematic, multimodal approach to neuroprognostication. It also highlights evidence gaps.

The SLANT Score Predicts Poor Neurologic Outcome in Comatose Survivors of Cardiac Arrest: An External Validation Using a Retrospective Cohort

BACKGROUND

Hypoxic brain injury is the leading cause of death in comatose patients following resuscitation from cardiac arrest. Neurological outcome can be difficult to prognosticate following resuscitation, and goals of care discussions are often informed by multiple prognostic tools. One tool that has shown promise is the SLANT score, which encompasses five metrics including initial nonshockable rhythm, leukocyte count after targeted temperature management, total adrenaline dose during resuscitation, lack of bystander cardiopulmonary resuscitation, and time to return of spontaneous circulation. This cohort study aimed to provide an external validation of this score by using a database of comatose cardiac arrest survivors from our institution.

METHODS

We retrospectively queried our database of cardiac arrest survivors, selecting for patients with coma, sustained return of spontaneous circulation, and use of targeted temperature management to have a comparable sample to the index study. We calculated SLANT scores for each patient and separated them into risk levels, both according to the original study and according to a Youden index analysis. The primary outcome was poor neurologic outcome (defined by a cerebral performance category score of 3 or greater at discharge), and the secondary outcome was in-hospital mortality. Univariable and multivariable analyses, as well as a receiver operator characteristic curve, were used to assess the SLANT score for independent predictability and diagnostic accuracy for poor outcomes.

RESULTS

We demonstrate significant association between a SLANT group with increased risk and poor neurologic outcome on univariable (p = 0.005) and multivariable analysis (odds ratio 1.162, 95% confidence interval 1.003-1.346, p = 0.046). A receiver operating characteristic analysis indicates that SLANT scoring is a fair prognostic test for poor neurologic outcome (area under the curve 0.708, 95% confidence interval 0.536-0.879, p = 0.024). Among this cohort, the most frequent SLANT elements were initial nonshockable rhythm (84.5%) and total adrenaline dose ≥ 5 mg (63.9%). There was no significant association between SLANT score and in-hospital mortality (p = 0.064).

CONCLUSIONS

The SLANT score may independently predict poor neurologic outcome but not in-hospital mortality. Including the SLANT score as part of a multimodal approach may improve our ability to accurately prognosticate comatose survivors of cardiac arrest.

Predicting mortality in moderate-severe TBI patients without early withdrawal of life-sustaining treatments including ICU complications: The MYSTIC-score

PURPOSE

To develop and internally validate the MortalitY in Moderate-Severe TBI plus ICU Complications (MYSTIC)-Score to predict in-hospital mortality of msTBI patients without early (<24 h) withdrawal-of-life-sustaining treatments.

METHODS

We analyzed data from a Neuro-Trauma Intensive Care Unit prospectively collected between 11/2009-5/2019. Consecutive adult msTBI patients were included if Glasgow Coma Scale≤12, and neither died nor had withdrawal-of-life-sustaining treatments within 24 h of admission (n = 485). Using univariate and multivariable logistic regression in a random-split cohort approach (2/3 derivation;1/3 validation), we identified independent predictors of in-hospital mortality while adjusting for validated predictors of mortality (IMPACT-variables). We constructed the MYSTIC-Score and examined discrimination and calibration.

RESULTS

The MYSTIC-Score included the ICU complications brain edema, herniation, systemic inflammatory response syndrome, sepsis, acute kidney injury, cardiac arrest, and urinary tract infection. In the derivation cohort(n = 324), discrimination and calibration were excellent (area-under-the-receiver-operating-curve [AUC-ROC] = 0.95;Hosmer-Lemeshow p-value = 0.09, with p > 0.05 indicating good calibration). Internal validation revealed an AUC-ROC = 0.93 and Hosmer-Lemeshow-p-value = 0.76 (n = 161).

CONCLUSIONS

Certain ICU complications are independent predictors of in-hospital mortality and strengthen outcome prediction in msTBI when combined with validated admission predictors of mortality. However, external validation is needed to determine robustness and practical applicability of our model given the high potential for residual confounders.

External validation of the Glasgow coma scale-pupils in low- to middle-income country patients with traumatic brain injury: Could “motor score-pupil” have higher prognostic value?

Background:

The objective of this study is to validate the admission Glasgow coma scale (GCS) associated with pupil response (GCS-P) to predict traumatic brain injury (TBI) patient’s outcomes in a low- to middle-income country and to compare its performance with that of a simplified model combining the better motor response of the GCS and the pupilar response (MS-P).

Methods:

This is a prospective cohort of patients with TBI in a tertiary trauma reference center in Brazil. Predictive values of the GCS, GCS-P, and MS-P were evaluated and compared for 14 day and in-hospital mortality outcomes and length of hospital stay (LHS).

Results:

The study enrolled 447 patients. MS-P demonstrated better discriminative ability than GCS to predict mortality (AUC 0.736 × 0.658; P < 0.001) and higher AUC than GCS-P (0.736 × 0.704, respectively; P = 0.073). For hospital mortality, MS-P demonstrated better discrimination than GCS (AUC, 0.750 × 0.682; P < 0.001) and higher AUC than GCS-P (0.750 × 0.714; P = 0.027). Both scores were good predictors of LHS (r2 = 0.084 [GCS-P] × 0.079 [GCS] × 0.072 [MS-P]).

Conclusion:

The predictive value of the GCS, GCS-P, and MS-P scales was demonstrated, thus contributing to its external validation in low- to middle-income country.

Ethics and the 2018 Practice Guideline on Disorders of Consciousness: A Framework for Responsible Implementation

The 2018 practice guideline on disorders of consciousness marks an important turning point in the care of patients with severe brain injury. As clinicians and health systems implement the guideline in practice, several ethical challenges will arise in assessing the benefits, harms, feasibility, and cost of recommended interventions. We provide guidance for clinicians when interpreting these recommendations and call on professional societies to develop an ethical framework to complement the guideline as it is implemented in clinical practice.

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.

Prognostication in Acute Neurological Emergencies

BACKGROUND

For patients with acute, serious neurological conditions presenting to the emergency department (ED), prognostication is typically based on clinical experience, scoring systems and patient co-morbidities. Because estimating a poor prognosis influences caregiver decisions to withdraw life-sustaining therapy, we investigated the consistency of prognostication across a spectrum of neurology physicians.

METHODS

Five acute neurological presentations (2 with large hemispheric infarction; 1 with brainstem infarction, 1 with lobar hemorrhage, and 1 with hypoxic-ischemic encephalopathy) were selected for a department-wide prognostication simulation exercise. All had presented to our tertiary care hospital's ED, where a poor outcome was predicted by the ED neurology team within 24 hours of onset. Relevant clinical, laboratory and imaging data available before ED prognostication were presented on a web-based platform to 120 providers blinded to the actual outcome. The provider was requested to rank-order, from most to least likely, the predicted 90-day modified Rankin Scale (mRS) score. To determine the accuracy of individual outcome predictions we compared the patient's the actual 90-day mRS score to highest ranked predicted mRS score. Additionally, the group's "weighted" outcomes, accounting for the entire spectrum of mRS scores ranked by all respondents, were compared to the actual outcome for each case. Consistency was compared between pre-specified provider roles: neurology trainees versus faculty; non-vascular versus vascular faculty.

RESULTS

Responses ranged from 106-110 per case. Individual predictions were highly variable, with predictions matching the actual mRS scores in as low as 2% of respondents in one case and 95% in another case. However, as a group, the weighted outcome matched the actual mRS score in 3 of 5 cases (60%). There was no significant difference between subgroups based on expertise (stroke/neurocritical care versus other) or experience (faculty versus trainee) in 4 of 5 cases.

CONCLUSION

Acute neuro-prognostication is highly variable and often inaccurate among neurology providers. Significant differences are not attributable to experience or subspecialty expertise. The mean outcome prediction from group of providers ("the wisdom of the crowd") may be superior to that of individual providers.

The intersection of prognostication and code status in patients with severe brain injury

Accurately estimating the prognosis of brain injury patients can be difficult, especially early in their course. Prognostication is important because it largely determines the care level we provide, from aggressive treatment for patients we predict could have a good outcome to withdrawal of treatment for those we expect will have a poor outcome. Accurate prognostication is required for ethical decision-making. However, several studies have shown that prognostication is frequently inaccurate and variable. Overly optimistic prognostication can lead to false hope and futile care. Overly pessimistic prognostication can lead to therapeutic nihilism. Overlapping is the powerful effect that cognitive biases, in particular code status, can play in shaping our perceptions and the care level we provide. The presence of Do Not Resuscitate orders has been shown to be associated with increased mortality. Based on a comprehensive search of peer-reviewed journals using a wide range of key terms, including prognostication, critical illness, brain injury, cognitive bias, and code status, the following is a review of prognostic accuracy and the effect of code status on outcome. Because withdrawal of treatment is the most common cause of death in the ICU, a clearer understanding of this intersection of prognostication and code status is needed.

Withholding or withdrawing life support in long-term neurointensive care patients: a single-centre, prospective, observational pilot study

PURPOSE

Scarce evidence exists regarding end-of-life decision (EOLD) in neurocritically ill patients. We investigated the factors associated with EOLD making, including the group and individual characteristics of involved healthcare professionals, in a multiprofessional neurointensive care unit (NICU) setting.

MATERIALS AND METHODS

A prospective, observational pilot study was conducted between 2013 and 2014 in a 10-bed NICU. Factors associated with EOLD in long-term neurocritically ill patients were evaluated using an anonymised survey based on a standardised questionnaire.

RESULTS

8 (25%) physicians and 24 (75%) nurses participated in the study by providing their 'treatment decisions' for 14 patients at several time points. EOLD was 'made' 44 (31%) times, while maintenance of life support 98 (69%) times. EOLD patterns were not significantly different between professional groups. The individual characteristics of the professionals (age, gender, religion, personal experience with death of family member and NICU experience) had no significant impact on decisions to forgo or maintain life-sustaining therapy. EOLD was patient-specific (intraclass correlation coefficient: 0.861), with the presence of acute life-threatening disease (OR (95% CI): 18.199 (1.721 to 192.405), p=0.038) and low expected patient quality of life (OR (95% CI): 9.276 (1.131 to 76.099), p=0.016) being significant and independent determinants for withholding or withdrawing life-sustaining treatment.

CONCLUSIONS

Our findings suggest that EOLD in NICU relies mainly on patient prognosis and not on the characteristics of the healthcare professionals.

Prognostication in neurology

Prognosticating is central to primary palliative care in neurology. Many neurologic diseases carry a high burden of troubling symptoms, and many individuals consider health states due to neurologic disease worse than death. Many patients and families report high levels of need for information at all disease stages, including information about prognosis. There are many barriers to communicating prognosis including prognostic uncertainty, lack of training and experience, fear of destroying hope, and not enough time. Developing the right mindset, tools, and skills can improve one's ability to formulate and communicate prognosis. Prognosticating is subject to many biases which can dramatically affect the quality of patient care; it is important for providers to recognize and reduce them. Patients and surrogates often do not hear what they are told, and even when they hear correctly, they form their own opinions. With practice and self-reflection, one can improve their prognostic skills, help patients and families create honest roadmaps of the future, and deliver high-quality person-centered care.

The potential of prediction models of functioning remains to be fully exploited: A scoping review in the field of spinal cord injury rehabilitation

OBJECTIVE

The study aimed to explore existing prediction models of functioning in spinal cord injury (SCI).

STUDY DESIGN AND SETTING

The databases PubMed, EBSCOhost CINAHL Complete, and IEEE Xplore were searched for relevant literature. The search strategy included published search filters for prediction model and impact studies, index terms and keywords for SCI, and relevant outcome measures able to assess functioning as reflected in the International Classification of Functioning, Disability and Health (ICF). The search was completed in October 2020.

RESULTS

We identified seven prediction model studies reporting twelve prediction models of functioning. The identified prediction models were mainly envisioned to be used for rehabilitation planning, however, also other possible applications were stated. The method predominantly used was regression analysis and the investigated predictors covered mainly the ICF components of body functions and activities and participation, next to characteristics of the health condition and health interventions.

CONCLUSION

Findings suggest that the development of prediction models of functioning for use in clinical practice remains to be fully exploited. By providing a comprehensive overview of what has been done, this review informs future research on prediction models of functioning in SCI and contributes to an efficient use of research evidence.

End-of-Life Care Decision-Making in Stroke

Stroke is one of the leading causes of death and long-term disability in the United States. Though advances in interventions have improved patient survival after stroke, prognostication of long-term functional outcomes remains challenging, thereby complicating discussions of treatment goals. Stroke patients who require intensive care unit care often do not have the capacity themselves to participate in decision making processes, a fact that further complicates potential end-of-life care discussions after the immediate post-stroke period. Establishing clear, consistent communication with surrogates through shared decision-making represents best practice, as these surrogates face decisions regarding artificial nutrition, tracheostomy, code status changes, and withdrawal or withholding of life-sustaining therapies. Throughout decision-making, clinicians must be aware of a myriad of factors affecting both provider recommendations and surrogate concerns, such as cognitive biases. While decision aids have the potential to better frame these conversations within intensive care units, aids specific to goals-of-care decisions for stroke patients are currently lacking. This mini review highlights the difficulties in decision-making for critically ill ischemic stroke and intracerebral hemorrhage patients, beginning with limitations in current validated clinical scales and clinician subjectivity in prognostication. We outline processes for identifying patient preferences when possible and make recommendations for collaborating closely with surrogate decision-makers on end-of-life care decisions.

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

Coma trajectories are characterized by quick awakening or protracted awakening. Outcome is bookended by restored functionality or permanent cognitively and physically debilitated states. Given the stakes, prognostication cannot be easily questioned as a judgment call, and a scientific underpinning is elemental. Conventional wisdom in determining coma-outcome trajectories posits that (1) predictive models are better than personal experiences, (2) self-fulfilling prophesy is unchecked and driven by nihilism, with little regard for prior probability outcomes, and (3) recovery is impacted by patients’ prior wishes and preexisting medical conditions—but also by what families are told about the patient’s state and anticipated clinical course. Moreover, a predicted good outcome can be offset by a major subsequent complication, or a predicted poor outcome can be offset by aggressive care. This article examines some of these concepts, including how we decide on aggressiveness of care, how we judge quality of life, and the impact on outcome. Most patients who awaken quickly do well and can resume their pretrauma injury lives. In worse off, slow-to-awaken patients, outcomes are a mixed bag of limited innate resilience, depleted cognitive and physical reserves, and adjusted quality of life. Bias and noise are factors not easily measured in outcome prediction, but their influence on recovery trajectories raises some troubling issues.

Early clinical predictors of functional recovery following traumatic spinal cord injury: a population-based study of 143 patients

BACKGROUND

Traumatic spinal cord injuries (TSCI) are associated with uncertainty regarding the prognosis of functional recovery. The aim of the present study was to evaluate the potential of early clinical variables to predict the degree of functional independence assessed by Spinal Cord Independence Measure III (SCIM-III) up to 1 year after injury.

METHODS

Prospectively collected data from 143 SCI patients treated in Western Denmark during 2012-2019 were retrospectively analysed. Data analysis involved univariate methods and multivariable linear regression modelling total SCIM-III scores against age, gender, body mass index (BMI), comorbidity, American Spinal Injury Association (ASIA) Impairment Scale (AIS) grades A-B and C-D, ASIA Motor Score (AMS), timing of surgical treatment and occurrence of medical complications. Statistical significance was set at p < .05.

RESULTS

Univariate analyses indicated that variables significantly associated with decreased functional independence included increased age (p = .023), increased BMI (p = .012), pre-existing comorbidity (p = .001), AIS grades A-B (p < .001), decreased AMS (p < .001) and occurrence of medical complications (p < .001). However, in the multivariable regression model were pre-existing comorbidity (p = .010), AIS grades A-B (p < .001), low AMS (p < .001) and late surgical treatment (p = .018) significant predictors of decreased functional independence 1 year after injury.

CONCLUSION

TSCI patients with greatest potential for functional recovery up to 1 year after injury seem to be patients that immediately after trauma present with few or no comorbidities, who sustain motor-incomplete injuries and undergo early decompressive surgery.

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.

Acute Coma

An acutely comatose patient constitutes a medical emergency until proved otherwise. Managing these emergencies requires organized teamwork to recognize and treat life-threatening situations and reversible causes of coma. Once vital functions have been stabilized, information from the history and physical examination should be used to rationally guide subsequent testing. Identifying causes of coma for which emergency treatment is possible should be the priority. The treatment and prognosis depend on the cause.

Prognostication after intracerebral hemorrhage: a review

Background

Approximately half of patients with spontaneous intracerebral hemorrhage (ICH) die within 1 year. Prognostication in this context is of great importance, to guide goals of care discussions, clinical decision-making, and risk stratification. However, available prognostic scores are hardly used in clinical practice. The purpose of this review article is to identify existing outcome prediction scores for spontaneous intracerebral hemorrhage (ICH) discuss their shortcomings, and to suggest how to create and validate more useful scores.

Main text

Through a literature review this article identifies existing ICH outcome prediction models. Using the Essen-ICH-score as an example, we demonstrate a complete score validation including discrimination, calibration and net benefit calculations. Score performance is illustrated in the Erlangen UKER-ICH-cohort (NCT03183167). We identified 19 prediction scores, half of which used mortality as endpoint, the remainder used disability, typically the dichotomized modified Rankin score assessed at variable time points after the index ICH. Complete score validation by our criteria was only available for the max-ICH score. Our validation of the Essen-ICH-score regarding prediction of unfavorable outcome showed good discrimination (area under the curve 0.87), fair calibration (calibration intercept 1.0, slope 0.84), and an overall net benefit of using the score as a decision tool. We discuss methodological pitfalls of prediction scores, e.g. the withdrawal of care (WOC) bias, physiological predictor variables that are often neglected by authors of clinical scores, and incomplete score validation. Future scores need to integrate new predictor variables, patient-reported outcome measures, and reduce the WOC bias. Validation needs to be standardized and thorough. Lastly, we discuss the integration of current ICH scoring systems in clinical practice with the awareness of their shortcomings.

Conclusion

Presently available prognostic scores for ICH do not fulfill essential quality standards. Novel prognostic scores need to be developed to inform the design of research studies and improve clinical care in patients with ICH.

Supplementary Information

The online version contains supplementary material available at 10.1186/s42466-021-00120-5.

Neuro-Oncologic Emergencies

Cancer and cancer therapies have the potential to affect the nervous system in a host of different ways. Cerebral edema, increased intracranial pressure, cerebrovascular events, status epilepticus, and epidural spinal cord compression are among those most often presenting as emergencies. Neurologic side-effects of cancer therapies are often mild, but occasionally result in serious illness. Immunotherapies cause autoimmune-related neurologic side-effects that are generally responsive to immunosuppressive therapies. Emergency management of neuro-oncologic problems benefits from early identification and close collaboration among interdisciplinary team members and patients or surrogate decision-makers.

IL-33 as a Novel Serum Prognostic Marker of Intracerebral Hemorrhage

Objective

Interleukin 33 (IL-33) is a key cytokine involved in inflammation and oxidative stress. The significance of serum IL-33 levels on the prognosis of patients with intracerebral hemorrhage (ICH) has not been well studied. The purpose of this study is to determine whether there is a relationship between the serum IL-33 level and the prognosis of patients with ICH upon admission.

Methods

A total of 402 patients with confirmed ICH were included in this study. Their demographic data, medical history, laboratory data, imaging data, and clinical scores on admission were collected. At the same time, enzyme-linked immunoassay (ELISA) was used to detect the serum IL-33 levels of patients. The prognosis of patients was evaluated by mRS scale after 3 months, and mRS > 2 was defined as poor prognosis.

Results

Among 402 patients with ICH, the number of patients with good prognosis and poor prognosis after 3 months was 148 and 254, respectively. Compared with the ICH group with poor prognosis, the ICH group with good prognosis had lower baseline NHISS scores (p = 0.039) and hematoma volume (p = 0.025) and higher GCS scores (p < 0.001) and serum IL-33 levels (p < 0.001). The results of linear correlation analysis showed that serum IL-33 levels were significantly negatively correlated with baseline NHISS scores (r = −0.224, p = 0.033) and hematoma volume (r = −0.253, p = 0.046) but were significantly positively correlated with baseline GCS scores (r = 0.296, p = 0.020). The receiver operating characteristic curve (ROC) analysis showed that the sensitivity and specificity of serum IL-33 level in evaluating the prognosis of ICH were 72.1% and 74.3%, respectively. A cut-off value of serum IL-33 level < 109.3 pg/mL may indicate a poor prognosis for ICH.

Conclusions

Serum IL-33 level on admission may be a prognostic indicator of ICH, and its underlying mechanism needs further study.

Adapting a Traumatic Brain Injury Goals-of-Care Decision Aid for Critically Ill Patients to Intracerebral Hemorrhage and Hemispheric Acute Ischemic Stroke

OBJECTIVES

Families in the neurologic ICU urgently request goals-of-care decision support and shared decision-making tools. We recently developed a goals-of-care decision aid for surrogates of critically ill traumatic brain injury patients using a systematic development process adherent to the International Patient Decision Aid Standards. To widen its applicability, we adapted this decision aid to critically ill patients with intracerebral hemorrhage and large hemispheric acute ischemic stroke.

DESIGN

Prospective observational study.

SETTING

Two academic neurologic ICUs.

SUBJECTS

Twenty family members of patients in the neurologic ICU were recruited from July 2018 to October 2018.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We reviewed the existing critically ill traumatic brain injury patients decision aid for content and changed: 1) the essential background information, 2) disease-specific terminology to "hemorrhagic stroke" and "ischemic stroke", and 3) disease-specific prognosis tailored to individual patients. We conducted acceptability and usability testing using validated scales. All three decision aids contain information from validated, disease-specific outcome prediction models, as recommended by international decision aid standards, including careful emphasis on their uncertainty. We replaced the individualizable icon arrays graphically depicting probabilities of a traumatic brain injury patient's prognosis with icon arrays visualizing intracerebral hemorrhage and hemispheric acute ischemic stroke prognostic probabilities using high-quality disease-specific data. We selected the Intracerebral Hemorrhage Score with validated 12-month outcomes, and for hemispheric acute ischemic stroke, the 12-month outcomes from landmark hemicraniectomy trials. Twenty family members participated in acceptability and usability testing (n = 11 for the intracerebral hemorrhage decision aid; n = 9 for the acute ischemic stroke decision aid). Median usage time was 22 minutes (interquartile range, 16-26 min). Usability was excellent (median System Usability Scale = 84/100 [interquartile range, 61-93; with > 68 indicating good usability]); 89% of participants graded the decision aid content as good or excellent, and greater than or equal to 90% rated it favorably for information amount, balance, and comprehensibility.

CONCLUSIONS

We successfully adapted goals-of-care decision aids for use in surrogates of critically ill patients with intracerebral hemorrhage and hemispheric acute ischemic stroke and found excellent usability and acceptability. A feasibility trial using these decision aids is currently ongoing to further validate their acceptability and test their feasibility for use in busy neurologic ICUs.

The prediction value of Glasgow coma scale-pupils score in neurocritical patients: a retrospective study

BACKGROUND

External validation is necessary before  its clinical recommendation in new setting. The aim is to externally validate Glasgow Coma Scale-pupils score (GCS-P) in neurocritical patients and to compare its performances with Glasgow Coma Scale (GCS) and its derivatives.

METHODS

GCS-P at admission was calculated for individual based on the model developed by Brennan et al. Area under the receiver operating characteristic curves (AUCs), Nagelkerke's R² and Brier scores were used to assess external validity of GCS-P to predict mortality in neurocritical patients and to compare predictive performance with GCS and its derivatives.

SUBJECTS

4372 neurocritical patients from intensive care units of Beth Israel Deaconess Medical Center, United States between 2001 and 2012.

RESULTS

GCS-P showed good discrimination (AUC 0.847 for in-hospital mortality and 0.774 for ninety-day mortality), modest calibration (Nagelkerke's R2 33.1% for in-hospital mortality and 23.3% for ninety-day mortality). Predictive performances of GCS and its derivatives was inferior to GCS-P.

CONCLUSIONS

GCP-P discriminated well in between death in neurocritical patients. GCP-P improved predictive performance for short-term mortality over GCS and its derivatives in neurocritical patients. It would be a simple, early and reasonable daily routine option for prognosis assessment in neurocritical setting.

Life Support Limitations in Mechanically Ventilated Stroke Patients

Supplemental Digital Content is available in the text.

Objectives:

The determinants of decisions to limit life support (withholding or withdrawal) in ventilated stroke patients have been evaluated mainly for patients with intracranial hemorrhages. We aimed to evaluate the frequency of life support limitations in ventilated ischemic and hemorrhagic stroke patients compared with a nonbrain-injured population and to determine factors associated with such decisions.

Design:

Multicenter prospective French observational study.

Setting:

Fourteen ICUs of the French OutcomeRea network.

PATIENTS:

From 2005 to 2016, we included stroke patients and nonbrain-injured patients requiring invasive ventilation within 24 hours of ICU admission.

INTERVENTION:

None.

MEASUREMENTS AND MAIN RESULTS:

We identified 373 stroke patients (ischemic, n = 167 [45%]; hemorrhagic, n = 206 [55%]) and 5,683 nonbrain-injured patients. Decisions to limit life support were taken in 41% of ischemic stroke cases (vs nonbrain-injured patients, subdistribution hazard ratio, 3.59 [95% CI, 2.78–4.65]) and in 33% of hemorrhagic stroke cases (vs nonbrain-injured patients, subdistribution hazard ratio, 3.9 [95% CI, 2.97–5.11]). Time from ICU admission to the first limitation was longer in ischemic than in hemorrhagic stroke (5 [3–9] vs 2 d [1–6] d; p < 0.01). Limitation of life support preceded ICU death in 70% of ischemic strokes and 45% of hemorrhagic strokes (p < 0.01). Life support limitations in ischemic stroke were increased by a vertebrobasilar location (vs anterior circulation, subdistribution hazard ratio, 1.61 [95% CI, 1.01–2.59]) and a prestroke modified Rankin score greater than 2 (2.38 [1.27–4.55]). In hemorrhagic stroke, an age greater than 70 years (2.29 [1.43–3.69]) and a Glasgow Coma Scale score less than 8 (2.15 [1.08–4.3]) were associated with an increased risk of limitation, whereas a higher nonneurologic admission Sequential Organ Failure Assessment score was associated with a reduced risk (per point, 0.89 [0.82–0.97]).

Conclusions:

In ventilated stroke patients, decisions to limit life support are more than three times more frequent than in nonbrain-injured patients, with different timing and associated risk factors between ischemic and hemorrhagic strokes.

Findings Predictive of Poor Outcome in Grade 5 Subarachnoid Hemorrhage: A Cohort Study

BACKGROUND

Most patients with World Federation of Neurological Surgeons (WFNS) grade 5 subarachnoid hemorrhage (SAH) have poor outcomes. Accurate assessment of prognosis is important for treatment decisions and conversations with families regarding goals of care. Unjustified pessimism may lead to "self-fulfilling prophecy," where withdrawal of life-sustaining measures (WLSM) is invariably followed by death.

METHODS

We performed a cohort study involving consecutive patients with WFNS grade 5 SAH to identify variables with >= 90% and >= 95% positive predictive value (PPV) for poor outcome (1-year modified Rankin Score >= 4), as well as findings predictive of WLSM.

RESULTS

Of 140 patients, 38 (27%) had favorable outcomes. Predictors with >= 95% PPV for poor outcome included unconfounded 72-hour Glasgow Coma Scale motor score <= 4, absence of >= 1 pupillary light reflex (PLR) at 24 hours, and intraventricular hemorrhage (IVH) score of >= 20 (volume >= 54.6 ml). Intracerebral hemorrhage (ICH) volume >= 53 ml had PPV of 92%. Variables associated with WLSM decisions included a poor motor score (p < 0.0001) and radiographic evidence of infarction (p = 0.02).

CONCLUSIONS

We identified several early predictors with high PPV for poor outcome. Of these, lack of improvement in motor score during the initial 72 hours had the greatest potential for confounding from "self-fulfilling prophecy." Absence of PLR at 24 hours, IVH score >= 20, and ICH volume >= 53 ml predicted poor outcome without a statistically significant effect on WLSM decisions. More research is needed to validate prognostic variables in grade 5 SAH, especially among patients who do not undergo WLSM.

Outcome prediction in aneurysmal subarachnoid hemorrhage: a comparison of machine learning methods and established clinico-radiological scores

Reliable prediction of outcomes of aneurysmal subarachnoid hemorrhage (aSAH) based on factors available at patient admission may support responsible allocation of resources as well as treatment decisions. Radiographic and clinical scoring systems may help clinicians estimate disease severity, but their predictive value is limited, especially in devising treatment strategies. In this study, we aimed to examine whether a machine learning (ML) approach using variables available on admission may improve outcome prediction in aSAH compared to established scoring systems. Combined clinical and radiographic features as well as standard scores (Hunt & Hess, WFNS, BNI, Fisher, and VASOGRADE) available on patient admission were analyzed using a consecutive single-center database of patients that presented with aSAH (n = 388). Different ML models (seven algorithms including three types of traditional generalized linear models, as well as a tree bosting algorithm, a support vector machine classifier (SVMC), a Naive Bayes (NB) classifier, and a multilayer perceptron (MLP) artificial neural net) were trained for single features, scores, and combined features with a random split into training and test sets (4:1 ratio), ten-fold cross-validation, and 50 shuffles. For combined features, feature importance was calculated. There was no difference in performance between traditional and other ML applications using traditional clinico-radiographic features. Also, no relevant difference was identified between a combined set of clinico-radiological features available on admission (highest AUC 0.78, tree boosting) and the best performing clinical score GCS (highest AUC 0.76, tree boosting). GCS and age were the most important variables for the feature combination. In this cohort of patients with aSAH, the performance of functional outcome prediction by machine learning techniques was comparable to traditional methods and established clinical scores. Future work is necessary to examine input variables other than traditional clinico-radiographic features and to evaluate whether a higher performance for outcome prediction in aSAH can be achieved.

A Triage Model for Interhospital Transfers of Low Risk Intracerebral Hemorrhage Patients

OBJECTIVES

Intracerebral hemorrhage comprises a large proportion of inter-hospital transfers to comprehensive stroke centers from centers without comprehensive stroke center resources despite lack of mortality benefit and low comprehensive stroke center resource utilization. The subset of patients who derive the most benefit from inter-hospital transfers is unclear. Here, we create a triage model to identify patients who can safely avoid transfer to a comprehensive stroke center.

MATERIALS AND METHODS

A retrospective cohort of spontaneous intracerebral hemorrhage patients transferred to our comprehensive stroke center from surrounding centers was used. Patients with early discharge from the Neuroscience Intensive Care Unit without use of comprehensive stroke center resources were identified as low risk, non-utilizers. Variables associated with this designation were used to develop and validate a triage model.

RESULTS

The development and replication cohorts comprised 358 and 99 patients respectively, of whom 78 (22%) and 26 (26%) were low risk, non-utilizers. Initial Glasgow Coma Scale and baseline hemorrhage volume were associated with low risk, non-utilizers in multivariate analysis. Initial Glasgow Coma Scale >13, intracerebral hemorrhage volume <15ml, absence of intraventricular hemorrhage, and supratentorial location had an area under curve, specificity, and sensitivity of 0.72, 91.4%, 52.6%, respectively, for identifying low risk, non-utilizers, and 0.75, 84.9%, 65.4%, respectively, in the replication cohort.

CONCLUSIONS

Spontaneous intracerebral hemorrhage patients with Glasgow Coma Scale >13, intracerebral hemorrhage volume <15 ml, absence of intraventricular hemorrhage, and supratentorial location might safely avoid inter-hospital transfer to a comprehensive stroke center. Validation in a prospective, multicenter cohort is warranted.

Proceedings from the Neurotherapeutics Symposium on Neurological Emergencies: Shaping the Future of Neurocritical Care

Effective treatment options for patients with life-threatening neurological disorders are limited. To address this unmet need, high-impact translational research is essential for the advancement and development of novel therapeutic approaches in neurocritical care. "The Neurotherapeutics Symposium 2019-Neurological Emergencies" conference, held in Rochester, New York, in June 2019, was designed to accelerate translation of neurocritical care research via transdisciplinary team science and diversity enhancement. Diversity excellence in the neuroscience workforce brings innovative and creative perspectives, and team science broadens the scientific approach by incorporating views from multiple stakeholders. Both are essential components needed to address complex scientific questions. Under represented minorities and women were involved in the organization of the conference and accounted for 30-40% of speakers, moderators, and attendees. Participants represented a diverse group of stakeholders committed to translational research. Topics discussed at the conference included acute ischemic and hemorrhagic strokes, neurogenic respiratory dysregulation, seizures and status epilepticus, brain telemetry, neuroprognostication, disorders of consciousness, and multimodal monitoring. In these proceedings, we summarize the topics covered at the conference and suggest the groundwork for future high-yield research in neurologic emergencies.

Neurological Prognostication in Children After Cardiac Arrest

Early after pediatric cardiac arrest, families and care providers struggle with the uncertainty of long-term neurological prognosis. Cardiac arrest characteristics such as location, intra-arrest factors, and postarrest events have been associated with outcome. We paid particular attention to postarrest modalities that have been shown to predict neurological outcome. These modalities include neurological examination, somatosensory evoked potentials, electroencephalography, and neuroimaging. There is no one modality that accurately predicts neurological prognosis. Thus, a multimodal approach should be undertaken by both neurologists and intensivists to present a clear and consistent message to families. Methods used for the prediction of long-term neurological prognosis need to be specific enough to identify indivuals with a poor outcome. We review the evidence evaluating children with coma, each with various etiologies of cardiac arrest, outcome measures, and timing of follow-up.