Neuroprognostication Practices in Postcardiac Arrest Patients: An International Survey of Critical Care Providers

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.

The Recovery of Consciousness via Evidence-Based Medicine and Research (RECOVER) Program: A Paradigm for Advancing Neuroprognostication

Background

Neuroprognostication for disorders of consciousness (DoC) after severe acute brain injury is a major challenge, and the conventional clinical approach struggles to keep pace with a rapidly evolving literature. Lacking specialization, and fragmented between providers, conventional neuroprognostication is variable, frequently incongruent with guidelines, and prone to error, contributing to avoidable mortality and morbidity.

Recent Findings

We review the limitations of the conventional approach to neuroprognostication and DoC care, and propose a paradigm entitled the Recovery of Consciousness Via Evidence-Based Medicine and Research (RECOVER) program to address them. The aim of the RECOVER program is to provide specialized, comprehensive, and longitudinal care that synthesizes interdisciplinary perspectives, provides continuity to patients and families, and improves the future of DoC care through research and education.

Implications for Practice

This model, if broadly adopted, may help establish neuroprognostication as a new subspecialty that improves the care of this vulnerable patient population.

A practical magnetic-resonance imaging score for outcome prediction in comatose cardiac arrest survivors

AIM

Magnetic Resonance Imaging (MRI) is an important prognostic tool in cardiac arrest (CA) survivors given its sensitivity for detecting hypoxic-ischemic brain injury (HIBI), however, it is limited by poorly defined objective thresholds. To address this limitation, we evaluated a qualitative MRI score for predicting neurological outcome in CA survivors.

METHODS

Adult comatose CA survivors who underwent MRI were retrospectively identified at a single academic medical center. Two blinded neurointensivists qualitatively scored HIBI amongst 12 MRI brain regions. Scores were summated to form four distinct score groups: cortex, deep grey nuclei (DGN), cortex-DGN combined, and total (cortex, DGN, brainstem, and cerebellum). Poor neurological outcome was defined as Cerebral Performance Category (CPC) score 3-5 at hospital discharge. Inter-rater reliability was tested using intra-class correlation (ICC) and discrimination of poor neurological outcome assessed using area under the receiver operating curve (AUC).

RESULTS

Our cohort included 219 patients with median time to MRI of 96 (IQR 81-110) hours. ICC (95% CI) was good to excellent across all MRI scores: cortex 0.92 (0.89-0.94), DGN 0.88 (0.80-0.92), cortex-DGN 0.94 (0.92-0.95), and total 0.93 (0.91-0.95). AUC (95% CI) for poor outcome was good across all MRI scores: cortex 0.84 (0.78-0.90), DGN 0.83 (0.77-0.89), cortex-DGN 0.83 (0.77-0.89), and total 0.83 (0.77-0.88).

CONCLUSION

A simplified, qualitative MRI score had excellent reliability and good discrimination for poor neurologic outcome. Further work is necessary to externally validate our findings in an independent, ideally prospective, cohort.

Assessing palliative care practices in intensive care units and interpreting them using the lens of appropriate care concepts. An umbrella review

PURPOSE

Intensive care units (ICUs) have significant palliative care needs but lack a reliable care framework. This umbrella review addresses them by synthesising palliative care practices provided at end-of-life to critically ill patients and their families before, during, and after ICU admission.

METHODS

Seven databases were systematically searched for systematic reviews, and the umbrella review was conducted according to the guidelines laid out by the Joanna Briggs Institute (JBI).

RESULTS

Out of 3122 initial records identified, 40 systematic reviews were included in the synthesis. Six key themes were generated that reflect the palliative and end-of-life care practices in the ICUs and their outcomes. Effective communication and accurate prognostications enabled families to make informed decisions, cope with uncertainty, ease distress, and shorten ICU stays. Inter-team discussions and agreement on a plan are essential before discussing care goals. Recording care preferences prevents unnecessary end-of-life treatments. Exceptional end-of-life care should include symptom management, family support, hydration and nutrition optimisation, avoidance of unhelpful treatments, and bereavement support. Evaluating end-of-life care quality is critical and can be accomplished by seeking family feedback or conducting a survey.

CONCLUSION

This umbrella review encapsulates current palliative care practices in ICUs, influencing patient and family outcomes and providing insights into developing an appropriate care framework for critically ill patients needing end-of-life care and their families.

Utility and rationale for continuous EEG monitoring: a primer for the general intensivist

This review offers a comprehensive guide for general intensivists on the utility of continuous EEG (cEEG) monitoring for critically ill patients. Beyond the primary role of EEG in detecting seizures, this review explores its utility in neuroprognostication, monitoring neurological deterioration, assessing treatment responses, and aiding rehabilitation in patients with encephalopathy, coma, or other consciousness disorders. Most seizures and status epilepticus (SE) events in the intensive care unit (ICU) setting are nonconvulsive or subtle, making cEEG essential for identifying these otherwise silent events. Imaging and invasive approaches can add to the diagnosis of seizures for specific populations, given that scalp electrodes may fail to identify seizures that may be detected by depth electrodes or electroradiologic findings. When cEEG identifies SE, the risk of secondary neuronal injury related to the time-intensity "burden" often prompts treatment with anti-seizure medications. Similarly, treatment may be administered for seizure-spectrum activity, such as periodic discharges or lateralized rhythmic delta slowing on the ictal-interictal continuum (IIC), even when frank seizures are not evident on the scalp. In this setting, cEEG is utilized empirically to monitor treatment response. Separately, cEEG has other versatile uses for neurotelemetry, including identifying the level of sedation or consciousness. Specific conditions such as sepsis, traumatic brain injury, subarachnoid hemorrhage, and cardiac arrest may each be associated with a unique application of cEEG; for example, predicting impending events of delayed cerebral ischemia, a feared complication in the first two weeks after subarachnoid hemorrhage. After brief training, non-neurophysiologists can learn to interpret quantitative EEG trends that summarize elements of EEG activity, enhancing clinical responsiveness in collaboration with clinical neurophysiologists. Intensivists and other healthcare professionals also play crucial roles in facilitating timely cEEG setup, preventing electrode-related skin injuries, and maintaining patient mobility during monitoring.

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.

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.

Postarrest Neuroprognostication: Practices and Opinions of Canadian Physicians

BACKGROUND

Objective, evidence-based neuroprognostication of postarrest patients is crucial to avoid inappropriate withdrawal of life-sustaining therapies or prolonged, invasive, and costly therapies that could perpetuate suffering when there is no chance of an acceptable recovery. Postarrest prognostication guidelines exist; however, guideline adherence and practice variability are unknown.

OBJECTIVE

To investigate Canadian practices and opinions regarding assessment of neurological prognosis in postarrest patients.

METHODS

An anonymous electronic survey was distributed to physicians who care for adult postarrest patients.

RESULTS

Of the 134 physicians who responded to the survey, 63% had no institutional protocols for neuroprognostication. While the use of targeted temperature management did not affect the timing of neuroprognostication, an increasing number of clinical findings suggestive of a poor prognosis affected the timing of when physicians were comfortable concluding patients had a poor prognosis. Variability existed in what factors clinicians' thought were confounders. Physicians identified bilaterally absent pupillary light reflexes (85%), bilaterally absent corneal reflexes (80%), and status myoclonus (75%) as useful in determining poor prognosis. Computed tomography, magnetic resonance imaging, and spot electroencephalography were the most useful and accessible tests. Somatosensory evoked potentials were useful, but logistically challenging. Serum biomarkers were unavailable at most centers. Most (79%) physicians agreed ≥2 definitive findings on neurologic exam, electrophysiologic tests, neuroimaging, and/or biomarkers are required to determine a poor prognosis with a high degree of certainty. Distress during the process of neuroprognostication was reported by 70% of physicians and 51% request a second opinion from an external expert.

CONCLUSION

Significant variability exists in post-cardiac arrest neuroprognostication practices among Canadian physicians.

A Novel Approach to Screen for Somatosensory Evoked Potentials in Critical Care

BACKGROUND

Somatosensory evoked potentials (SSEPs) help prognostication, particularly in patients with diffuse brain injury. However, use of SSEP is limited in critical care. We propose a novel, low-cost approach allowing acquisition of screening SSEP using widely available intensive care unit (ICU) equipment, specifically a peripheral "train-of-four" stimulator and standard electroencephalograph.

METHODS

The median nerve was stimulated using a train-of-four stimulator, and a standard 21-channel electroencephalograph was recorded to generate the screening SSEP. Generation of the SSEP was supported by visual inspection, univariate event-related potentials statistics, and a multivariate support vector machine (SVM) decoding algorithm. This approach was validated in 15 healthy volunteers and validated against standard SSEPs in 10 ICU patients. The ability of this approach to predict poor neurological outcome, defined as death, vegetative state, or severe disability at 6 months, was tested in an additional set of 39 ICU patients.

RESULTS

In each of the healthy volunteers, both the univariate and the SVM methods reliably detected SSEP responses. In patients, when compared against the standard SSEP method, the univariate event-related potentials method matched in nine of ten patients (sensitivity = 94%, specificity = 100%), and the SVM had 100% sensitivity and specificity when compared with the standard method. For the 49 ICU patients, we performed both the univariate and the SVM methods: a bilateral absence of short latency responses (n = 8) predicted poor neurological outcome with 0% FPR (sensitivity = 21%, specificity = 100%).

CONCLUSIONS

Somatosensory evoked potentials can reliably be recorded using the proposed approach. Given the very good but slightly lower sensitivity of absent SSEPs in the proposed screening approach, confirmation of absent SSEP responses using standard SSEP recordings is advised.

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.

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.

Brain imaging with portable low-field MRI

The advent of portable, low-field MRI (LF-MRI) heralds new opportunities in neuroimaging. Low power requirements and transportability have enabled scanning outside the controlled environment of a conventional MRI suite, enhancing access to neuroimaging for indications that are not well suited to existing technologies. Maximizing the information extracted from the reduced signal-to-noise ratio of LF-MRI is crucial to developing clinically useful diagnostic images. Progress in electromagnetic noise cancellation and machine learning reconstruction algorithms from sparse k-space data as well as new approaches to image enhancement have now enabled these advancements. Coupling technological innovation with bedside imaging creates new prospects in visualizing the healthy brain and detecting acute and chronic pathological changes. Ongoing development of hardware, improvements in pulse sequences and image reconstruction, and validation of clinical utility will continue to accelerate this field. As further innovation occurs, portable LF-MRI will facilitate the democratization of MRI and create new applications not previously feasible with conventional systems.

Value of EEG in outcome prediction of hypoxic-ischemic brain injury in the ICU: A narrative review

Prognostication of comatose patients after cardiac arrest aims to identify patients with a large probability of favourable or unfavouble outcome, usually within the first week after the event. Electroencephalography (EEG) is a technique that is increasingly used for this purpose and has many advantages, such as its non-invasive nature and the possibility to monitor the evolution of brain function over time. At the same time, use of EEG in a critical care environment faces a number of challenges. This narrative review describes the current role and future applications of EEG for outcome prediction of comatose patients with postanoxic encephalopathy.

Prognostication after cardiac arrest: how EEG and evoked potentials may improve the challenge

About 80% of patients resuscitated from CA are comatose at ICU admission and nearly 50% of survivors are still unawake at 72 h. Predicting neurological outcome of these patients is important to provide correct information to patient's relatives, avoid disproportionate care in patients with irreversible hypoxic-ischemic brain injury (HIBI) and inappropriate withdrawal of care in patients with a possible favorable neurological recovery. ERC/ESICM 2021 algorithm allows a classification as "poor outcome likely" in 32%, the outcome remaining "indeterminate" in 68%. The crucial question is to know how we could improve the assessment of both unfavorable but also favorable outcome prediction. Neurophysiological tests, i.e., electroencephalography (EEG) and evoked-potentials (EPs) are a non-invasive bedside investigations. The EEG is the record of brain electrical fields, characterized by a high temporal resolution but a low spatial resolution. EEG is largely available, and represented the most widely tool use in recent survey examining current neuro-prognostication practices. The severity of HIBI is correlated with the predominant frequency and background continuity of EEG leading to "highly malignant" patterns as suppression or burst suppression in the most severe HIBI. EPs differ from EEG signals as they are stimulus induced and represent the summated activities of large populations of neurons firing in synchrony, requiring the average of numerous stimulations. Different EPs (i.e., somato sensory EPs (SSEPs), brainstem auditory EPs (BAEPs), middle latency auditory EPs (MLAEPs) and long latency event-related potentials (ERPs) with mismatch negativity (MMN) and P300 responses) can be assessed in ICU, with different brain generators and prognostic values. In the present review, we summarize EEG and EPs signal generators, recording modalities, interpretation and prognostic values of these different neurophysiological tools. Finally, we assess the perspective for futures neurophysiological investigations, aiming to reduce prognostic uncertainty in comatose and disorders of consciousness (DoC) patients after CA.

Bedside monitoring of hypoxic ischemic brain injury using low-field, portable brain magnetic resonance imaging after cardiac arrest

BACKGROUND

Assessment of brain injury severity is critically important after survival from cardiac arrest (CA). Recent advances in low-field MRI technology have permitted the acquisition of clinically useful bedside brain imaging. Our objective was to deploy a novel approach for evaluating brain injury after CA in critically ill patients at high risk for adverse neurological outcome.

METHODS

This retrospective, single center study involved review of all consecutive portable MRIs performed as part of clinical care for CA patients between September 2020 and January 2022. Portable MR images were retrospectively reviewed by a blinded board-certified neuroradiologist (S.P.). Fluid-inversion recovery (FLAIR) signal intensities were measured in select regions of interest.

RESULTS

We performed 22 low-field MRI examinations in 19 patients resuscitated from CA (68.4% male, mean [standard deviation] age, 51.8 [13.1] years). Twelve patients (63.2%) had findings consistent with HIBI on conventional neuroimaging radiology report. Low-field MRI detected findings consistent with HIBI in all of these patients. Low-field MRI was acquired at a median (interquartile range) of 78 (40-136) hours post-arrest. Quantitatively, we measured FLAIR signal intensity in three regions of interest, which were higher amongst patients with confirmed HIBI. Low-field MRI was completed in all patients without disruption of intensive care unit equipment monitoring and no safety events occurred.

CONCLUSION

In a critically ill CA population in whom MR imaging is often not feasible, low-field MRI can be deployed at the bedside to identify HIBI. Low-field MRI provides an opportunity to evaluate the time-dependent nature of MRI findings in CA survivors.

Top Ten Tips Palliative Care Clinicians Should Know About Disorders of Consciousness: A Focus on Traumatic and Anoxic Brain Injury

Palliative care (PC) teams commonly encounter patients with disorders of consciousness (DOC) following anoxic or traumatic brain injury (TBI). Primary teams may consult PC to help surrogates in making treatment choices for these patients. PC clinicians must understand the complexity of predicting neurologic outcomes, address clinical nihilism, and appropriately guide surrogates in making decisions that are concordant with patients' goals. The purpose of this article was to provide PC providers with a better understanding of caring for patients with DOC, specifically following anoxic or TBI. Many of the tips acknowledge the uncertainty of DOC and provide strategies to help tackle this dilemma.

Physicians' cognitive approach to prognostication after cardiac arrest

OBJECTIVE

Elucidate how physicians formulate a neurological prognosis after cardiac arrest and compare differences between experts and general providers.

METHODS

We performed semi-structured interviews with experts in post-arrest care and general physicians. We created an initial model and interview guide based on professional society guidelines. Two authors independently coded interviews based on this initial model, then identified new topics not included in it. To describe individual physicians' cognitive approach to prognostication, we created a graphical representation. We summarized these individual "mental models" into a single overall model, as well as two models stratified by expertise.

RESULTS

We performed 36 interviews (17 experts and 19 generalists), most of whom practice in Europe (23) or North America (12). Participants described their approach to prognosis formulation as complex and iterative, with sequential and repeated data acquisition, interpretation, and prognosis formulation. Eventually, this cycle results in a final prognosis and treatment recommendation. Commonly mentioned factors were diagnostic test performance, time from arrest, patient characteristics. Participants also discussed factors rarely discussed in prognostication research including physician and hospital characteristics. We found no substantial differences between experts and general physicians.

CONCLUSION

Physicians' cognitive approach to neurologic prognostication is complex and influenced by many factors, including some rarely considered in current research. Understanding these processes better could inform interventions designed to aid physicians in prognostication.

Documentation of neurological status in patients admitted to an intensive care unit after cardiac arrest: A 10-year cohort study

OBJECTIVE

The objective of this study was to describe the documented neurological assessment and investigations for neuroprognostication in patients after cardiac arrest.

DESIGN, SETTING, AND PARTICIPANTS

This was a retrospective cohort study of adult patients after cardiac arrest, admitted to a tertiary intensive care unit (ICU), between January 2009 and December 2018.

MAIN OUTCOME MEASURES

The main outcome measures were the proportion of patients with a documented Glasgow Coma Scale (GCS) score and investigations for neuroprognostication.

RESULTS

Four hundred twenty-seven patients formed the study cohort. The GCS score was documented for 267 (63%) patients at some time during their ICU stay. The proportion of patients with the GCS score documented decreased each day of ICU stay (59% at day 1, 20% at day 5). Pupil reflex to light was recorded in 352 (82%), corneal reflex in 155 (36%), and limb reflexes in 216 (51%) patients. Twenty-eight (6.6%) patients underwent brain magnetic resonance imaging, 10 (2.3%) an electroencephalogram, and two somatosensory evoked potentials. Withdrawal of life-sustaining treatments occurred in 166 (39%) patients, and 221 (52%) patients died in hospital.

CONCLUSIONS

In this single-centre study of patients admitted to the ICU after cardiac arrest, the GCS score was inconsistently documented, and investigations for neuroprognostication were infrequent.

Prognostication of patients in coma after cardiac arrest: Public perspectives

AIM

To elicit preferences for prognostic information, attitudes towards withdrawal of life-sustaining treatment (WLST) and perspectives on acceptable quality of life after post-anoxic coma within the adult general population of Germany, Italy, the Netherlands and the United States of America.

METHODS

A web-based survey, consisting of questions on respondent characteristics, perspectives on quality of life, communication of prognostic information, and withdrawal of life-sustaining treatment, was taken by adult respondents recruited from four countries. Statistical analysis included descriptive analysis and chi2-tests for differences between countries.

RESULTS

In total, 2012 respondents completed the survey. In each country, at least 84% indicated they would prefer to receive early prognostic information. If a poor outcome was predicted with some uncertainty, 37-54% of the respondents indicated that WLST was not to be allowed. A conscious state with severe physical and cognitive impairments was perceived as acceptable quality of life by 17-44% of the respondents. Clear differences between countries exist, including respondents from the U.S. being more likely to allow WLST than respondents from Germany (OR = 1.99, p < 0.001) or the Netherlands (OR = 1.74, p < 0.001) and preferring to stay alive in a conscious state with severe physical and cognitive impairments more than respondents from Italy (OR = 3.76, p < 0.001), Germany (OR = 2.21, p < 0.001), or the Netherlands (OR = 2.39, p < 0.001).

CONCLUSIONS

Over one-third of the respondents considered WLST unacceptable when there is any remaining prognostic uncertainty. Respondents had a more positive perspective on acceptable quality of life after coma than what is currently considered acceptable in medical literature. This indicates a need for a closer look at the practice of WLST based on prognostic information, to ensure responsible use of novel prognostic tests.

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.

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.

European Resuscitation Council and European Society of Intensive Care Medicine guidelines 2021: post-resuscitation care

The European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM) have collaborated to produce these post-resuscitation care guidelines for adults, which are based on the 2020 International Consensus on Cardiopulmonary Resuscitation Science with Treatment Recommendations. The topics covered include the post-cardiac arrest syndrome, diagnosis of cause of cardiac arrest, control of oxygenation and ventilation, coronary reperfusion, haemodynamic monitoring and management, control of seizures, temperature control, general intensive care management, prognostication, long-term outcome, rehabilitation and organ donation.

European Resuscitation Council and European Society of Intensive Care Medicine Guidelines 2021: Post-resuscitation care

The European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM) have collaborated to produce these post-resuscitation care guidelines for adults, which are based on the 2020 International Consensus on Cardiopulmonary Resuscitation Science with Treatment Recommendations. The topics covered include the post-cardiac arrest syndrome, diagnosis of cause of cardiac arrest, control of oxygenation and ventilation, coronary reperfusion, haemodynamic monitoring and management, control of seizures, temperature control, general intensive care management, prognostication, long-term outcome, rehabilitation, and organ donation.

Postcardiac Arrest Neuroprognostication Practices: A Survey of Brazilian Physicians

Supplemental Digital Content is available in the text.

End-of-life care and decisions on withdrawal of life-sustaining therapies vary across countries, which may affect the feasibility of future multicenter cardiac arrest trials. In Brazil, withdrawal of life-sustaining therapy is reportedly uncommon, allowing the natural history of postcardiac arrest hypoxic-ischemic brain injury to present itself. We aimed to characterize approaches to neuroprognostication of cardiac arrest survivors among physicians in Brazil.

Neurologic prognostication after resuscitation from cardiac arrest

Out-of-hospital cardiac arrest remains a leading cause of mortality in the United States, and the majority of patients who die after achieving return of spontaneous circulation die from withdrawal of care due to a perceived poor neurologic prognosis. Unfortunately, withdrawal of care often occurs during the first day of admission and research suggests this early withdrawal of care may be premature and result in unnecessary deaths for patients who would have made a full neurologic recovery. In this review, we explore the evidence for neurologic prognostication in the emergency department for patients who achieve return of spontaneous circulation after an out-of-hospital cardiac arrest.

Brain MR imaging and spectroscopy for outcome prognostication after pediatric cardiac arrest

AIM

Children surviving cardiac arrest are at high risk of neurological morbidity and mortality; however, there is a lack of validated prognostic biomarkers. We aimed to evaluate brain magnetic resonance imaging (MRI) and spectroscopy (MRS) as predictors of death and disability. Secondly, we evaluated whether MRI/S by randomized group.

METHODS

This single center study analyzed clinically indicated brain MRI/S data from children enrolled in a randomized controlled trial of 24 vs. 72 h of hypothermia following cardiac arrest. Two pediatric radiologists scored conventional MRIs. Lactate and N-acetyl-aspartate (NAA) concentrations (mmol/kg) were determined from spectra acquired from the basal ganglia, thalamus, parietal white matter and parietooccipital gray matter. Mortality and neurological outcomes (favorable = Pediatric Cerebral Performance Category [PCPC] 1, 2, 3 or increase < 2) were assessed at hospital discharge. Non-parametric tests were used to test for associations between MRI/S biomarkers and outcome and randomized group.

RESULTS

23 children with (median [interquartile range]) age of 1.5 (0.3-4.0) years. Ten (44%) had favorable outcome. There were more T2 brain lesions in the lentiform nuclei in children with unfavorable 12 (92%) vs. favorable 3 (33%) outcome, p = 0.007. Increased lactate and decreased NAA concentrations in the parietooccipital gray matter and decreased NAA in the parietal white matter were associated with unfavorable outcome (p's < 0.05). There were no differences for any biomarker by randomized group.

CONCLUSION

Regional cerebral and metabolic MRI/S biomarkers are predictive of neurological outcomes at hospital discharge in pediatric cardiac arrest and should undergo validation testing in a large sample.

Are providers overconfident in predicting outcome after cardiac arrest?

AIM

To quantify the accuracy of health care providers' predictions of survival and function at hospital discharge in a prospective cohort of patients resuscitated from cardiac arrest. To test whether self-reported confidence in their predictions was associated with increased accuracy and whether this relationship varied across providers.

METHODOLOGY

We presented critical care and neurology providers with clinical vignettes using real data from post-arrest patients. We asked providers to predict survival, function at discharge, and report their confidence in these predictions. We used mixed effects models to explore predictors of confidence, accuracy, and the relationship between the two.

RESULTS

We completed 470 assessments of 62 patients with 65 providers. Of patients, 49 (78%) died and 9 (15%) had functionally favourable survival. Providers accurately predicted survival in 308/470 (66%) assessments. In most errors (146/162, 90%), providers incorrectly predicted survival. Providers accurately predicted function in 349/470 (74%) assessments. In most errors (114/121, 94%), providers incorrectly predicted favourable functional recovery. Providers were confident (median confidence predicting survival 80 [IQR 60-90]; median confidence predicting function 80 [IQR 60-95]). Confidence explained 9% and 18% of variation in accuracy predicting survival and function, respectively. We observed significant between-provider variability in accuracy (median odds ratio (MOR) for predicting survival 2.93, 95%CI 1.94-5.52; MOR for predicting function 5.42, 95%CI 3.01-13.2).

CONCLUSIONS

Providers varied in accuracy predicting post-arrest outcomes and most errors were optimistic. Self-reported confidence explained little variation in accuracy.