Standards for Studies of Neurological Prognostication in Comatose Survivors of Cardiac Arrest: A Scientific Statement From the American Heart Association

Alpha-band activity in density spectral array predictive for neurological outcome in patients with hypoxic-ischemic encephalopathy

BACKGROUND

In patients with hypoxic-ischemic encephalopathy (HIE), EEG is used to predict outcomes. However, a clear threshold for EEG findings associated with favorable outcomes remains unestablished. This study evaluates the predictive value of density spectral array (DSA)-based background activity in HIE patients.

METHODS

Forty-four consecutive HIE patients with disturbance of consciousness (2010-2023) were retrospectively assessed and categorized into highly malignant, malignant, or benign EEG patterns according to the conventional EEG classification. The presence of alpha-band activity, defined as an increase in alpha (or theta) frequency band power visible in the DSA, was also assessed. The relationship among conventional EEG classification, alpha-band activity, and neurological outcomes was evaluated.

RESULTS

All patients with highly malignant EEG lacked alpha-band activity and experienced poor outcomes, whereas those with less severe patterns occasionally exhibited alpha-band activity (14 % in the malignant vs. 60 % in the benign, p = 0.021), and demonstrated various outcomes. Recovery of consciousness until discharge was more prominent in patients with alpha-band activity compared to those without (100 % vs. 39 %, p < 0.001).

CONCLUSIONS

DSA-based evaluations provide a simple and valuable tool for predicting favorable neurological outcomes.

System for Predicting Neurological Outcomes Following Cardiac Arrest Based on Clinical Predictors Using a Machine Learning Method: The Neurological Outcomes After Cardiac Arrest Method

BACKGROUND

A multimodal approach may prove effective for predicting clinical outcomes following cardiac arrest (CA). We aimed to develop a practical predictive model that incorporates clinical factors related to CA and multiple prognostic tests using machine learning methods.

METHODS

The neurological outcomes after CA (NOCA) method for predicting poor outcomes were developed using data from 390 patients with CA between May 2018 and June 2023. The outcome was poor neurological outcome, defined as a Cerebral Performance Category score of 3-5 at discharge. We analyzed 31 variables describing the circumstances at CA, demographics, comorbidities, and prognostic studies. The prognostic method was developed based on an extreme gradient-boosting algorithm with threefold cross-validation and hyperparameter optimization. The performance of the predictive model was evaluated using the receiver operating characteristic curve analysis and calculating the area under the curve (AUC).

RESULTS

Of the 390 total patients (mean age 64.2 years; 71.3% male), 235 (60.3%) experienced poor outcomes at discharge. We selected variables to predict poor neurological outcomes using least absolute shrinkage and selection operator regression. The Glasgow Coma Scale-M (best motor response), electroencephalographic features, the neurological pupil index, time from CA to return of spontaneous circulation, and brain imaging were found to be important key parameters in the NOCA score. The AUC of the NOCA method was 0.965 (95% confidence interval 0.941-0.976).

CONCLUSIONS

The NOCA score represents a simple method for predicting neurological outcomes, with good performance in patients with CA, using a machine learning analysis that incorporates widely available variables.

Cerebrospinal Creatine Kinase BB Isoenzyme: A Biomarker for Predicting Outcome After Cardiac Arrest

BACKGROUND

Cerebrospinal fluid creatine kinase BB isoenzyme (CSF CK-BB) after cardiac arrest (CA) has been shown to have a high positive predictive value for poor neurological outcome, but it has not been evaluated in the setting of targeted temperature management (TTM) and modern CA care. We aimed to evaluate CSF CK-BB as a prognostic biomarker after CA.

METHODS

We performed a retrospective cohort study of patients with CA admitted between 2010 and 2020 to a three-hospital health system who remained comatose and had CSF CK-BB assayed between 36 and 84 h after CA. We examined the proportion of patients at hospital discharge who achieved favorable or intermediate neurological outcome, defined as Cerebral Performance Category score of 1-3, compared with those with poor outcome (Cerebral Performance Category score 4-5) for various CSF CK-BB thresholds. We also evaluated additive value of bilateral absence of somatosensory evoked potentials (SSEPs).

RESULTS

Among 214 eligible patients, the mean age was 54.7 ± 4.8 years, 72% of patients were male, 33% were nonwhite, 17% had shockable rhythm, 90% were out-of-hospital CA, and 83% received TTM. A total of 19 (9%) awakened. CSF CK-BB ≥ 230 U/L predicted a poor outcome at hospital discharge, with a specificity of 100% (95% confidence interval [CI] 82-100%) and sensitivity of 69% (95% CI 62-76%). When combined with bilaterally absent N20 response on SSEP, specificity remained 100% while sensitivity increased to 80% (95% CI 73-85%). Discordant CK-BB and SSEP findings were seen in 13 (9%) patients.

CONCLUSIONS

Cerebrospinal fluid creatine kinase BB isoenzyme levels accurately predicted poor neurological outcome among CA survivors treated with TTM. The CSF CK-BB cutoff of 230 U/L optimizes sensitivity to 69% while maintaining a specificity of 100%. CSF CK-BB could be a useful addition to multimodal neurological prognostication after CA.

The role of accidental hypothermia in drowning patients with out-of-hospital cardiac arrest: A nationwide registry-based cohort study

AIM

This study aimed to investigate the associations between hypothermia and mortality or poor neurological outcome in a nationwide cohort of drowning patients with out-of-hospital cardiac arrest (OHCA).

METHODS

This nationwide, registry-based cohort study reported in-hospital data on drowning patients with OHCA following the Utstein Style For Drowning. Drowning patients with OHCA were identified in the Danish Cardiac Arrest Registry from 2016 to 2021. The primary outcome was the rate of mortality or poor neurological outcome (corresponding to a modified Rankin Scale [mRS] score > 3) at 180 days after the drowning incident in patients with OHCA and accidental hypothermia (<35 °C) vs normothermia (≥35 °C).

RESULTS

This study identified 118 drowning patients with OHCA and found an increased rate of mRS > 3 at 180 days after the drowning incident in the hypothermic group compared to the normothermic group (74% vs 18%, p < 0.001). The 180-day mortality (mRS = 6) was 69% in the hypothermic group compared to 16% in the normothermic group (p < 0.001). The hypothermic group had higher rates of ongoing CPR at hospital admission (45% vs 7%, p < 0.001), intensive care unit admission (70% vs 41%, p = 0.003), and mechanical ventilation during hospitalisation (78% vs 32%, p < 0.001) compared to the normothermic group.

CONCLUSION

Hypothermic drowning patients with OHCA had a higher risk of mortality or poor neurological outcome at 180 days compared to normothermic drowning patients with OHCA. This association may likely be explained by confounding factors such as prolonged submersion and cardiac arrest. Further research is warranted.

Prediction of good neurological outcome after return of circulation following paediatric cardiac arrest: A systematic review and meta-analysis

AIM

To evaluate the ability of blood-biomarkers, clinical examination, electrophysiology, or neuroimaging, assessed within 14 days from return of circulation to predict good neurological outcome in children following out- or in-hospital cardiac arrest.

METHODS

Medline, EMBASE and Cochrane Trials databases were searched (2010-2023). Sensitivity and false positive rates (FPR) for good neurological outcome (defined as either 'no, mild, moderate disability or minimal change from baseline') in paediatric survivors were calculated for each predictor. Risk of bias was assessed using the QUIPS tool.

RESULTS

Thirty-five studies (2974 children) were included. The presence of any of the following had a FPR < 30% for predicting good neurological outcome with moderate (50-75%) or high (>75%) sensitivity: bilateral reactive pupillary light response within 12 h; motor component ≥ 4 on the Glasgow Coma Scale score at 6 h; bilateral somatosensory evoked potentials at 24-72 h; sleep spindles, and continuous cortical activity on electroencephalography within 24 h; or a normal brain MRI at 4-6d. Early (≤12 h) normal lactate levels (<2mmol/L) or normal s100b, NSE or MBP levels predicted good neurological outcome with FPR rate < 30% and low (<50%) sensitivity. All studies had moderate to high risk of bias with timing of measurement, definition of test, use of multi-modal tests, or outcome assessment heterogeneity.

CONCLUSIONS

Clinical examination, electrophysiology, neuroimaging or blood-biomarkers as individual tests can predict good neurological outcome after cardiac arrest in children. However, evidence is often low quality and studies are heterogeneous. Use of a standardised, multimodal, prognostic algorithm should be studied and is likely of added value over single modality testing.

Elevated glycocalyx shedding components as the early predictors of unfavorable outcomes in patients after cardiac arrest: A single-center observational study

OBJECTIVE

To assess the association of serum glycocalyx shedding components (Heparan sulfate, HS; Hyaluronic acid, HA; Syndecan-1, Sdc-1) with outcomes after CA.

METHODS

Patients who were comatose for >24 h after CA in the intensive care unit (ICU) of the Affiliated Hospital of Xuzhou Medical University from 9/2021 to 04/2023 were enrolled. Serum samples were collected 24 h after CA to measure the concentrations of glycocalyx shedding components. The outcomes were the 30-day Cerebral Performance Categories (CPC) scale and 30-day mortality. The association of glycocalyx shedding with outcomes was examined by regression analysis. The area under the curve was used to evaluate the value of glycocalyx shedding for predicting outcomes. Sensitivity analysis and subgroup analysis were conducted.

RESULTS

111 patients were enrolled. The unfavorable group (CPC 3-5, n = 69) had significantly higher serum concentrations of HA and Sdc-1 than the favorable group (CPC 1-2, n = 42) (HA:149.7 ng/ml vs. 824.8 ng/ml, P < 0.001; Sdc-1: 303.8 ng/L vs. 447.0 ng/L, P = 0.026)but not HS. Elevated serum HA concentrations was an independent risk factor for unfavorable 30-day neurological function (OR = 2.485, 95 % CI = 1.656-3.729). For the 30-day mortality, the nonsurvivor group (n = 53) had significantly higher serum concentrations of HA, HS and Sdc-1 (HA: 177.3 ng/ml vs. 1106.7 ng/ml, P < 0.001; HS: 2403.7 ng/ml vs. 3383.3 ng/ml P = 0.030; Sdc-1: 352.1 ng/L vs. 487.8 ng/L, P = 0.005) than the survivor group (n = 58). However, only elevated serum HA and Sdc-1 concentrations are independent risk factors for 30-day mortality (HA: HR = 2.321, 95 % CI = 1.776-3.035; Sdc-1: HR = 1.702, 95 % CI = 1.038-2.792).

CONCLUSIONS

Elevated serum HA at 24 h after CA is an independent risk factor for 30-day unfavorable neurological function or mortality and elevated serum Sdc-1 concentrations is an independent risk factor for 30-day mortality. Our results suggested the potential value of serum glycocalyx shedding components as predictors for the outcomes in post-CA patients.

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 effect of thermoelectric craniocerebral cooling device on protecting brain functions in post-cardiac arrest syndrome

Aim

This study aimed to protect brain functions in patients who experienced in-hospital cardiac arrest through the application of local cerebral hypothermia. By utilizing a specialized thermal hypothermia device, this approach sought to mitigate ischemic brain injury associated with post-cardiac arrest syndrome, enhance survival rates, and improve neurological outcomes as measured by standardized scales.

Methods

A prospective, single-center cohort study was conducted involving patients aged ≥18 years who experienced in-hospital cardiac arrest and achieved return of spontaneous circulation (ROSC). Patients were cooled using a hypothermia helmet to achieve a target temperature of 32°C-34°C, maintained for 36-72 h, followed by controlled rewarming and normothermia for 72 h. Neurological recovery was assessed using the Cerebral Performance Category (CPC) scale, where CPC 1-2 denotes good recovery and CPC 3-5 indicates poor outcomes. Body temperature, hemodynamic parameters, biochemical changes, and survival data were meticulously recorded and analyzed. Statistical analysis included paired t-tests to compare pre- and post-treatment data.

Results

Of 116 cardiac arrest cases, 30 (25.86%) were in-hospital, and 16 (53.33%) of these achieved ROSC. Among the patients, 62.5% underwent emergency coronary angiography due to ST-elevation myocardial infarction (STEMI). The mean time to hypothermia initiation was 32.9 ± 13.5 min, with hypothermia maintained for 58 ± 6.4 h. Neurological outcomes were favorable, with 62.5% of patients achieving CPC scores of 1 or 2, indicating functional recovery and independence. In contrast, CPC scores of 3 or higher were observed in 37.5% of patients, reflecting varying degrees of disability. Biochemical analysis revealed significant decreases in sodium, potassium, calcium, and magnesium levels, alongside increased urea and creatinine concentrations. Hemodynamic improvements included elevated systolic blood pressure and heart rate, while left ventricular ejection fraction remained stable. Overall survival was 75%, and the majority (62.5%) of survivors were discharged without significant neurological deficits.

Conclusion

The findings suggest that early and targeted application of craniocerebral thermal hypothermia has the potential to improve survival and preserve neurological function in post-cardiac arrest syndrome. The high rates of favorable outcomes, as reflected by CPC scores, underscore the neuroprotective effects of localized hypothermia. Further large-scale, multicenter trials are recommended to validate these promising results and refine protocols for optimal clinical application.

Prognostic value of gray-white matter ratio measured by brain MRI-based CT structures in comatose patients after cardiac arrest

BACKGROUND

Post-cardiac arrest care advancements have improved resuscitation outcomes, but many survivors still face severe neurological deficits or death from brain injury. Herein, we propose a consistent prognosis prediction approach using magnetic resonance imaging (MRI) to analyze anatomical regions represented by the gray and white matter, and subsequently apply it on computed tomography (CT) to calculate the gray-white matter ratio (GWR). We compared this novel method with traditional measures to validate its ability to predict the prognosis of patients resuscitated after cardiac arrest.

METHODS

Conducted retrospectively at two South Korean tertiary university hospitals from January 2018 to December 2022, the study included adult cardiac arrest survivors treated with therapeutic target temperature management. Patients underwent brain CT within 2 h and brain MRI within 3 days of return of spontaneous circulation. The outcome was the neurological status at discharge. Statistical analyses included receiver operating characteristic curve analysis and determining cutoff values to predict poor neurological outcomes.

RESULTS

Overall, 51 of the 421 adult comatose cardiac arrest survivors examined met the inclusion criteria. Among these, 33 and 18 exhibited good and poor neurological outcomes, respectively. Demographic and cardiac arrest characteristics were compared between the two groups, revealing significant differences. Analyses of gray and white matter attenuation and GWR measurements highlighted significant differences between the good and poor outcome groups.

CONCLUSION

Our study introduces a novel method for measuring GWR using MRI-based brain CT, demonstrating superior prognostic accuracy in predicting neurological outcomes in patients with post-cardiac arrest syndrome compared to traditional methods.

Blood and cerebrospinal fluid biomarkers in disorders of consciousness

The study of blood and cerebrospinal fluid biomarkers is a promising and rapidly advancing field in the research of disorders of consciousness (DoC). The use of advanced biochemical and analytic techniques in biomarker research has improved our ability to identify new biomarkers that can aid in the diagnosis, prognosis, and treatment of patients with brain injury. However, the use of biomarkers in clinical practice is limited by several challenges, including the lack of standardization in test and research methodologies. Despite this, identifying the most promising biomarkers and supporting their findings with strong evidence can improve their clinical utility. This chapter discusses the most promising biomarkers for DoC, which fall into four categories: neuronal, glial, inflammatory, and metabolic biomarkers. Understanding the role of each category in DoC can provide valuable insights into the mechanisms of brain injury and inform the development of more effective diagnostic and treatment strategies. By integrating biomarker research with clinical practice, we can improve our understanding of DoC and provide better care for these patients.

Evoked potentials in patients with disorders of consciousness

Acute coma in the intensive care unit and persistent disorders of consciousness (DoC) in neuro-rehabilitation are frequent in patients with hypoxic-ischemic encephalopathy after cardiac arrest (CA), traumatic brain injury, intracranial hemorrhage, or ischemic stroke. Reliable prognostication of long-term neurologic outcomes cannot be made by clinical examination alone in the early phase for many patients, and thus, additional investigations are necessary. Evoked potentials provide inexpensive, real-time, high temporal resolution, bedside, quantifiable information on different sensory pathways into the brain including local and global cortical processing. Short-latency somatosensory evoked potentials can reliably predict poor neurologic long-term outcome in the early phase after CA and are recommended by guidelines as one investigation within an early multimodal assessment. Middle-latency and event-related or cognitive evoked potentials provide information on the integrity of more advanced cortical processing, some closely related to consciousness. This information can help to identify those comatose patients with a good prognosis in the acute phase and help to better understand their precise clinical state and the chances of further recovery in patients with persistent DoC in neuro-rehabilitation. Further studies are necessary to improve the applicability of research findings in the clinical sphere.

Electrophysiology in disorders of consciousness

Electroencephalography (EEG) has emerged as a powerful tool in the diagnosis, characterization, and prognostication of patients with disorders of consciousness (DoC). EEG is a well-established monitoring tool for the treatment of specific patient populations with impaired consciousness, such as those with status epilepticus and cardiac arrest. The interrogation of neuronal circuitry using evoked and event-related potentials adds prognostic information in comatose individuals. Novel paradigms integrating transcranial magnetic stimulation may provide insights into the underpinnings of arousal and awareness. Covert consciousness, or willful brain activation to motor commands in behaviorally unresponsive patients, may be diagnosed using EEG recordings and has been linked to better outcomes. These advanced EEG methods are increasingly being explored and integrated into the management of DoC patients.

Neurologic prognostication in coma and disorders of consciousness

Coma and disorders of consciousness (DoC) are clinical syndromes primarily resulting from severe acute brain injury, with uncertain recovery trajectories that often necessitate prolonged supportive care. This imposes significant socioeconomic burdens on patients, caregivers, and society. Predicting recovery in comatose patients is a critical aspect of neurocritical care, and while current prognostication heavily relies on clinical assessments, such as pupillary responses and motor movements, which are far from precise, contemporary prognostication has integrated more advanced technologies like neuroimaging and electroencephalogram (EEG). Nonetheless, neurologic prognostication remains fraught with uncertainty and significant inaccuracies and is impacted by several forms of prognostication biases, including self-fulfilling prophecy bias, affective forecasting, and clinician treatment biases, among others. However, neurologic prognostication in patients with disorders of consciousness impacts life-altering decisions including continuation of treatment interventions vs withdrawal of life-sustaining therapies (WLST), which have a direct influence on survival and recovery after severe acute brain injury. In recent years, advancements in neuro-monitoring technologies, artificial intelligence (AI), and machine learning (ML) have transformed the field of prognostication. These technologies have the potential to process vast amounts of clinical data and identify reliable prognostic markers, enhancing prediction accuracy in conditions such as cardiac arrest, intracerebral hemorrhage, and traumatic brain injury (TBI). For example, AI/ML modeling has led to the identification of new states of consciousness such as covert consciousness and cognitive motor dissociation, which may have important prognostic significance after severe brain injury. This chapter reviews the evolving landscape of neurologic prognostication in coma and DoC, highlights current pitfalls and biases, and summarizes the integration of clinical examination, neuroimaging, biomarkers, and neurophysiologic tools for prognostication in specific disease states. We will further discuss the future of neurologic prognostication, focusing on the integration of AI and ML techniques to deliver more individualized and accurate prognostication, ultimately improving patient outcomes and decision-making process in neurocritical care.

Cardiac arrest and disorders of consciousness

As the second most common cause of coma and disorders of consciousness, cardiac arrest is defined as a cessation of cardiac mechanical activity and absence of circulation. Cardiac arrest can happen due to an intrinsic cardiac condition or secondary to noncardiac causes such as respiratory, neurologic, metabolic causes or external causes such as toxic ingestion, asphyxia, drowning, trauma, and other environmental exposures. While cardiac arrest resuscitation research and practice has evolved over decades, the overall survival to hospital discharge remains low across different types of cardiac arrest (about 9%-29%). This chapter focuses on disorders of consciousness after cardiac arrest and how it is different from other etiologies. It also discusses advances and controversies in diagnosis, management, prognostication and research.

The Electrographic Effects of Ketamine on Patients With Refractory Status Epilepticus After Cardiac Arrest: A Single-Center Retrospective Cohort

PURPOSE

To investigate the effects of ketamine on patients with refractory status epilepticus after cardiac arrest.

METHODS

In this retrospective cohort, selected EEG segments from patients after cardiac arrest were classified into different EEG patterns (based on background continuity and burden of epileptiform discharges) and spectral profiles (based on the presence of frequency components). For patients who received ketamine, EEG data were compared before, during, and after ketamine infusion; for the no-ketamine group, EEG data were compared at three separated time points during recording. Ketamine usage was determined by clinical providers. Electrographic improvement in epileptiform activity was scored, and the odds ratio was calculated using the Fisher exact test. Functional outcome measures at time of discharge were also examined.

RESULTS

Of a total of 38 patients with postcardiac arrest refractory status epilepticus, 13 received ketamine and 25 did not. All patients were on ≥2 antiseizure medications including at least one sedative infusion (midazolam). For the ketamine group, eight patients had electrographic improvement, compared with only two patients in the no-ketamine group, with an odds ratio of 7.19 (95% confidence interval 1.16-44.65, P value of 0.0341) for ketamine versus no ketamine. Most of the patients who received ketamine had myoclonic status epilepticus, and overall neurologic outcomes were poor with no patients having a favorable outcome.

CONCLUSIONS

For postarrest refractory status epilepticus, ketamine use was associated with electrographic improvement, but with the available data, it is unclear whether ketamine use or EEG improvement can be linked to better functional recovery.

Electrophysiological Signatures in Global Cerebral Ischemia: Neuroprotection Via Chemogenetic Inhibition of CA1 Pyramidal Neurons in Rats

BACKGROUND

Although there has been limited research into the perturbation of electrophysiological activity in the brain after ischemia, the activity signatures during ischemia and reperfusion remain to be fully elucidated. We aim to comprehensively describe these electrophysiological signatures and interrogate their correlation with ischemic damage during global cerebral ischemia and reperfusion.

METHODS AND RESULTS

We used the 4-vessel occlusion method of inducing global cerebral ischemia in rats. We used in vivo electrophysiological techniques to simultaneously record single units, scalp electroencephalogram, and local field potentials in awake animals. Neuronal damage and astrocyte reactivation were examined by immunofluorescence, immunoblotting, and quantitative real-time reverse-transcription polymerase chain reaction under chemogenetic inhibition of glutamatergic neurons. Electroencephalogram/local field potentials power and phase-amplitude coupling of the theta and low-gamma bands were reduced during ischemia and the acute phase of reperfusion. The firing rate of single units was enhanced by ischemia-reperfusion, and the phase relationship between the local field potentials theta band and neuronal firing was altered. Precise inhibition of hippocampus CA1 pyramidal neuron hyperactivity by chemogenetics rescued the firing dysfunction, ischemic neuronal damage, and A1 astrocyte activation.

CONCLUSIONS

Our results provide a comprehensive description of the characteristics of electrophysiological activity that accompany ischemia-reperfusion and highlight the significance of this activity in ischemic damage.

Effect of hypercapnia on neurologic outcomes after cardiac arrest: A systematic review and meta-analysis

BACKGROUND

Brain injury often occurs after cardiac arrest, and the regulation of PaCO2 plays a crucial role in mediating cerebral blood flow. The current guidelines recommend maintaining normocapnia through ventilation in post-arrest patients. However, the effects of hypercapnia on neurological outcomes remain controversial. To address this issue, we undertook a meta-analysis to compare the effects of hypercapnia and normocapnia on the neurological outcomes in patients with cardiac arrest.

METHODS

As of December 5, 2023, we conducted a search on eligible studies, including EMBASE, PubMed, and WOS databases. Our primary outcome of interest was a good neurological outcome, and two authors independently screened the studies and extracted relevant data. For analysis, a fixed effects model was used when the I2 values were less than 50 %, whereas a random effects model was used for higher I2 values.

RESULTS

From the 2137 studies initially identified, seven studies involving 2770 patients were ultimately included. Compared with normocapnia, hypercapnia significantly improved the neurological outcomes of patients with cardiac arrest (OR 0.73; 95 % CI 0.56-0.96; P = 0.02). According to the subgroup analysis, the hypercapnic group achieved better neurological outcomes in the short-term than did the normocapnia group (OR 0.61; 95 % CI 0.42-0.88; P = 0.008), whereas no significant difference was observed in long-term (OR 0.91; 95 % CI 0.76-1.10; P = 0.35). Moreover, there was no significant difference in mortality between the two groups (OR 1.03; 95 % CI 0.65-1.63; P = 0.91).

CONCLUSION

Our results suggest that hypercapnia is associated with a good neurological prognosis, especially in the short-term setting. However, further well-powered randomized controlled trials are necessary to confirm the optimal PaCO2 targets.

PROSPERO

CRD42023457027. Registered 3 September 2023.

Application of multi-feature-based machine learning models to predict neurological outcomes of cardiac arrest

Cardiac arrest (CA) is a major disease burden worldwide and has a poor prognosis. Early prediction of CA outcomes helps optimize the therapeutic regimen and improve patients' neurological function. As the current guidelines recommend, many factors can be used to evaluate the neurological outcomes of CA patients. Machine learning (ML) has strong analytical abilities and fast computing speed; thus, it plays an irreplaceable role in prediction model development. An increasing number of researchers are using ML algorithms to incorporate demographics, arrest characteristics, clinical variables, biomarkers, physical examination findings, electroencephalograms, imaging, and other factors with predictive value to construct multi-feature prediction models for neurological outcomes of CA survivors. In this review, we explore the current application of ML models using multiple features to predict the neurological outcomes of CA patients. Although the outcome prediction model is still in development, it has strong potential to become a powerful tool in clinical practice.

The Pre-ECPR Score: Developing and Validating a Multivariable Prediction Model for Favorable Neurological Outcomes in Patients Undergoing Extracorporeal Cardiopulmonary Resuscitation

OBJECTIVES

Extracorporeal cardiopulmonary resuscitation (ECPR) can save patients with refractory cardiac arrest; however, according to recent meta-analyses, only 20% of patients achieve favorable outcomes (Modified Rankin Scale 0-3). We aimed to develop and validate an ECPR prediction model to improve patient selection.

DESIGN

Prognostic model development and internal validation study.

SETTING

Single-center study.

PARTICIPANTS

All 120 normothermic ECPR patients treated at Sahlgrenska University Hospital between January 2010 and October 2021.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Multivariable logistic regression was used to develop the PRognostic Evaluation of ECPR (Pre-ECPR) score. Model performance was assessed through the area under curve (AUC) and compared with the Extracorporeal Life Support Organization (ELSO) "Example of selection criteria for ECPR" for 1-year survival with favorable outcomes. The positive predictive value (PPV) was calculated. Favorable outcomes occurred in 27.5% of the patients. The Pre-ECPR score, incorporating age, no-flow/initial rhythm (a composite variable), total cardiac arrest time, signs of life, pupil dilation, regional cerebral oxygen saturation, arterial pH, and end-tidal CO2, demonstrated an AUC of 0.87 (95% confidence interval [CI] 0.77-0.93). In internal cross-validation, the AUC of 0.79 (95% CI 0.67-0.88) significantly outperformed the ELSO criteria AUC of 0.63 (95% CI 0.54-0.72, p = 0.012). Pre-ECPR score probabilities >6.4% showed 100% sensitivity and a PPV of 40.5% for favorable outcomes.

CONCLUSIONS

The Pre-ECPR score combines multiple weighted predictors to provide a single balanced probability of favorable outcomes in ECPR patient selection. In cross-validation, it demonstrated significantly more favorable discriminatory performance than that of the ELSO criteria.

Brain Dead or Alive: A Case Report of Inaccurate Neurological Prognostication

Although numerous definitions of brain death exist, the diagnosis and diagnostic process remain open to interpretation. We present the case of a 32-year-old male with systemic lupus erythematosus who presented to an outside hospital following a cardiac arrest while jogging. His electroencephalogram (EEG) showed abnormal contour in the posterior fields. Despite the patient's normal brain magnetic resonance imaging (MRI), the treating neurological team diagnosed him with anoxic brain injury based on his persistently comatose exam and abnormal EEG. With neurological guidance, the patient's family elected for terminal extubation and organ donation. He surprisingly survived the terminal extubation and was transferred to our hospital for prognostication. His EEG showed lateralized periodic discharges, prompting medication adjustments. He was also treated for multiple infections. With treatments, his EEG normalized, and he ultimately ambulated, conversed, and consented for this case report one year following discharge. The lack of uniformity on how to approach comatose patients with presumed irreversible neurologic injury can lead to inaccurate prognostication and guide life-or-death clinical decisions. This case of erroneous assessment highlights the marked limitations of the current legal framework for determining brain death and the need for standardized medical criteria.

Methods of Evaluating EEG Reactivity in Adult Intensive Care Units: A Review

PURPOSE

EEG reactivity (EEG-R) has become widely used in intensive care units for diagnosing and prognosticating patients with disorders of consciousness. Despite efforts toward standardization, including the establishment of terminology for critical care EEG in 2012, the processes of testing and interpreting EEG-R remain inconsistent.

METHODS

A review was conducted on PubMed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Inclusion criteria consisted of articles published between January 2012, and November 2022, testing EEG-R on adult intensive care unit patients. Exclusion criteria included articles focused on highly specialized stimulation equipment or animal, basic science, or small case report studies. The Quality In Prognostic Studies tool was used to assess risk of bias.

RESULTS

One hundred and five articles were identified, with 26 variables collected for each. EEG-R testing varied greatly, including the number of stimuli (range: 1-8; 26 total described), stimulus length (range: 2-30 seconds), length between stimuli (range: 10 seconds-5 minutes), frequency of stimulus application (range: 1-9), frequency of EEG-R testing (range: 1-3 times daily), EEG electrodes (range: 4-64), personnel testing EEG-R (range: neurophysiologists to nonexperts), and sedation protocols (range: discontinuing all sedation to no attempt). EEG-R interpretation widely varied, including EEG-R definitions and grading scales, personnel interpreting EEG-R (range: EEG specialists to nonneurologists), use of quantitative methods, EEG filters, and time to detect EEG-R poststimulation (range: 1-30 seconds).

CONCLUSIONS

This study demonstrates the persistent heterogeneity of testing and interpreting EEG-R over the past decade, and contributing components were identified. Further many institutional efforts must be made toward standardization, focusing on the reproducibility and unification of these methods, and detailed documentation in the published literature.

Systemically injected oxygen within rapidly dissolving microbubbles improves the outcomes of severe hypoxaemia in swine

Acute respiratory failure can cause profound hypoxaemia that leads to organ injury or death within minutes. When conventional interventions are ineffective, the intravenous administration of oxygen can rescue patients from severe hypoxaemia, but at the risk of microvascular obstruction and of toxicity of the carrier material. Here we describe polymeric microbubbles as carriers of high volumes of oxygen (350-500 ml of oxygen per litre of foam) that are stable in storage yet quickly dissolve following intravenous injection, reverting to their soluble and excretable molecular constituents. In swine with profound hypoxaemia owing to acute and temporary (12 min) upper-airway obstruction, the microbubble-mediated delivery of oxygen led to: the maintenance of critical oxygenation, lowered burdens of cardiac arrest, improved survival, and substantially improved neurologic and kidney function in surviving animals. Our findings underscore the importance of maintaining a critical threshold of oxygenation and the promise of injectable oxygen as a viable therapy in acute and temporary hypoxaemic crises.

Temperature Control Parameters Are Important: Earlier Preinduction Is Associated With Improved Outcomes Following Out-of-Hospital Cardiac Arrest

STUDY OBJECTIVE

Temperature control trials in cardiac arrest patients have not reliably conferred neuroprotective benefit but have been limited by inconsistent treatment parameters. To evaluate the presence of a time dependent treatment effect, we assessed the association between preinduction time and clinical outcomes.

METHODS

In this retrospective, single academic center study between 2014 and 2022, consecutive out-of-hospital cardiac arrest (OHCA) patients treated with temperature control were identified. Preinduction was defined as the time from hospital arrival to initiation of a closed-loop temperature feedback device [door to temperature control initiation time], and early door to temperature control device time was defined a priori as <3 hours. We assessed the association between good neurologic outcome (cerebral performance category 1 to 2) and door to temperature control device time using logistic regression. The proportion of patients who survived to hospital discharge was evaluated as a secondary outcome. A sensitivity analysis using inverse probability treatment weighting, created using a propensity score, was performed to minimize measurable confounding.

RESULTS

Three hundred and forty-seven OHCA patients were included; the early door to temperature control device cohort included 75 (21.6%) patients with a median (interquartile range) door to temperature control device time of 2.50 (2.03 to 2.75) hours, whereas the late door to temperature control device cohort included 272 (78.4%) patients with a median (interquartile range) door to temperature control device time of 5.18 (4.19 to 6.41) hours. In the multivariable logistic regression model, early door to temperature control device time was associated with improved good neurologic outcome and survival before [adjusted odds ratio (OR) (95% confidence interval) 2.36 (1.16 to 4.81) and 3.02 (1.54 to 6.02)] and after [adjusted OR (95% confidence interval) 1.95 (1.19 to 3.79) and 2.14 (1.33 to 3.36)] inverse probability of treatment weighting, respectively.

CONCLUSION

In our study of OHCA patients, a shorter preinduction time for temperature control was associated with improved good neurologic outcome and survival. This finding may indicate that early initiation in the emergency department will confer benefit. Our findings are hypothesis generating and need to be validated in future prospective trials.

EEG reactivity in neurologic prognostication in post-cardiac arrest patients: A narrative review

Electroencephalographic reactivity (EEG-R) is a promising early predictor of arousal in comatose patients after cardiac arrest. Despite recent guidelines advocating for the integration of EEG-R into the multimodal prognostication model, EEG-R testing methods remain heterogeneous across studies. While efforts towards standardization have been made to reduce interrater variability by the development of quantitative approaches and machine learning models, future validation studies are needed to increase clinical applicability. Furthermore, the specific neurophysiological mechanisms and neuroanatomical correlates underlying EEG-R are not fully understood. In this narrative review, we explore the value and possible mechanisms of EEG-R, focusing on post-cardiac arrest comatose patients. We aim to discuss the current standard of knowledge and future directions, as well as elucidate possible implications for patient care and research.

NSE and S100β as serum alarmins in predicting neurological outcomes after cardiac arrest

Cardiac arrest (CA) is a serious health concern that often results in mortality or severe neurological dysfunction in the case of survival. Our aim was to explore the neurological prognostic factors in patients with CA. This retrospective observational study included adult patients with CA. We investigated serum neuron-specific enolase (NSE), S100 calcium-binding protein β (S100β), and indices and parameters at 1, 3, 5, 7 and intensive care unit (ICU) discharge days after CA. The primary study endpoint was the Cerebral Performance Category (CPC) scale score at ICU discharge, which was dichotomized as good neurological outcome (CPC 1-2: full recovery or moderate disability) and poor neurological outcome (CPC 3-5: severe disability, vegetative state, or death). Of the 191 adult patients with CA, 42 (22%) had good neurological outcomes, and 149 (78%) had poor neurological outcomes. NSE at 1,3,5,7 and ICU discharge days showed excellent predictive accuracy for neurological outcomes (area under the curve [AUC]: 0.666, 0.716, 0.870, 0.739, and 0.901, respectively). However, S100β exhibited general predictive power (AUC: 0.666, 0.573, 0.607, 0.594, 0.727). Finally, the early warning model, which combined day 1 NSE, day 1 S100β, cardiac arrest time, SOFA scores, APACHE II scores, and age, was used to screen CA patients with poor neurological prognosis at early stages and had an AUC of 0.792. Serum concentrations of NSE and S100β were significantly elevated in CA patients and could be prognostic biomarkers to predict neurological outcomes. Day 1 NSE and S100β combined with multiple indicators could be a decent early warning model for poor neurological prognosis in patients with CA.

Optimal timing of ultra-early diffusion-weighted MRI in out-of-hospital cardiac arrest patients based on a retrospective multicenter cohort study

Diffusion-weighted magnetic resonance imaging (DW-MRI) performed before target temperature management, within 6 h of return of spontaneous circulation (ROSC), is defined as ultra-early DW-MRI. In previous studies, high-signal intensity (HSI) on ultra-early DW-MRI can predict poor neurological outcomes (Cerebral Performance Category 3-5 at 6-months post-ROSC). We aimed to assess the optimal-timing for ultra-early DW-MRI to avoid false-negative outcomes post out-of-hospital cardiac arrest, considering cardiopulmonary resuscitation (CPR) factors. The primary outcomes were HSI in the cerebral cortex or deep gray matter on ultra-early DW-MRI. The impact of CPR factors and ROSC to DW-MRI scan-interval on HSI-presence was assessed. Of 206 included patients, 108 exhibited HSI-presence, exclusively associated with poor neurological outcomes. In multivariate regression analysis, ROSC to DW-MRI scan-interval (adjusted odds ratio [aOR], 1.509; 95% confidence interval (CI): 1.113-2.046; P = 0.008), low-flow time (aOR, 1.176; 95%CI: 1.121-1.233; P < 0.001), and non-shockable rhythm (aOR, 9.974; 95%CI: 3.363-29.578; P < 0.001) were independently associated with HSI-presence. ROSC to DW-MRI scan-interval cutoff of ≥ 2.2 h was particularly significant in low-flow time ≤ 21 min or shockable rhythm group. In conclusion, short low-flow time and shockable rhythm require a longer ROSC to DW-MRI scan-interval. Prolonged low-flow time and non-shockable rhythm reduce the need to consider scan-interval.

The self-fulfilling prophecy in medicine

This article first describes the mechanism of any self-fulfilling prophecy through discussion of its four conditions: credibility, employment, employment sensitivity, and realization. Each condition is illustrated with examples specific to the medical context. The descriptive account ends with the definition of self-fulfilling prophecy and an expansion on collective self-fulfilling prophecies. Second, the normative account then discusses the moral relevance of self-fulfilling prophecies in medicine. A self-fulfilling prophecy is typically considered problematic when the prediction itself changes the predicted outcome to match the prediction (transformative self-fulfillment). I argue that also self-fulfilling prophecies that do not change the outcome but change the ways in which the outcome was realized (operative self-fulfillment), have significant ethical and epistemic ramifications. Because it is difficult to distinguish, retrospectively, between a transformative and an operative self-fulfilling prophecy, and thus between a false or true positive, it becomes equally difficult to catch mistakes. Moreover, since the prediction necessarily turns out true, there is never an error signal warning that a mistake might have been made. On the contrary, accuracy is seen as the standard for quality assurance. As such, self-fulfilling prophecies inhibit our ability to learn, inviting repetition and exacerbation of mistakes. With the rise of automated diagnostic and prognostic procedures and the increased use of machine learning and artificial intelligence for the development of predictive algorithms, attention to self-fulfilling feedback loops is especially warranted. This account of self-fulfilling prophecies is practically relevant for medical research and clinical practice. With it, researchers and practitioners can detect and analyze potential self-fulfilling mechanisms in any medical case and take responsibility for their ethical and epistemic implications.

Prognostic performance of gray-white matter ratio in adult out-of-hospital cardiac arrest patients after receiving extracorporeal cardiopulmonary resuscitation

BACKGROUND

Gray-to-white matter ratio (GWR), measured by computed tomography (CT), is commonly used to predict poor neurological outcomes after out-of-hospital cardiac arrest (OHCA). The prognostic performance of GWR in OHCA patients receiving extracorporeal cardiopulmonary resuscitation (ECPR) is not known.

METHODS

This study is a secondary analysis of data from the SAVE-J II registry, a retrospective, multicenter study. Participants were divided into four groups according to average GWR (aGWR) values ranging from 1.00 to 1.39, separated by 0.1 intervals. The aGWR values were calculated for bilateral basal ganglia, centrum semiovale, and high convexity obtained by head CT within 24 h after ECPR. Primary outcome was poor neurological outcomes at 30-day.

RESULTS

In total, 1,146 OHCA patients treated with ECPR were included in our analysis. Overall, participants with lower aGWR more likely had poor neurological outcomes, aGWR 1.00-1.09 (94.6%), aGWR 1.10-1-19 (87.8%), aGWR 1.20-1.29 (78.5%), and aGWR 1.30-1.39 (70.3%). Multivariable logistic regression showed that lower aGWR was associated with poor neurological outcome at 30-day, aGWR 1.30-1.39: reference, aGWR 1.00-1.09: adjusted odds ratio (aOR) 10.01 (95% confidence interval (CI) [3.58-27.99]), aGWR 1.10-1.19: aOR 4.83 (95% CI [2.31-10.12]), aGWR 1.20-1.29: aOR 2.16 (95% CI [1.02-4.55]). Receiver operating characteristic curve analysis revealed that the prognostic performance of aGWR had an area under the curve of 0.628, 95% CI [0.59-0.66]). The aGWR threshold of 1.005 for predicting poor neurological outcome reached 100% specificity with 0.1% sensitivity.

CONCLUSION

Early neuro-prognostication depending on GWR may not be sufficient after ECPR and requires a multimodal approach.

Myoclonus After Cardiac Arrest did not Correlate with Cortical Response on Somatosensory Evoked Potentials

PURPOSE

Myoclonus after anoxic brain injury is a marker of significant cerebral injury. Absent cortical signal (N20) on somatosensory evoked potentials (SSEPs) after cardiac arrest is a reliable predictor of poor neurological recovery when combined with an overall clinical picture consistent with severe widespread neurological injury. We evaluated a clinical question of if SSEP result could be predicted from other clinical and neurodiagnostic testing results in patients with post-anoxic myoclonus.

METHODS

Retrospective chart review of all adult patients with post-cardiac arrest myoclonus who underwent both electroencephalographic (EEG) monitoring and SSEPs for neuroprognostication. Myoclonus was categorized as "non-myoclonic movements," "myoclonus not captured on EEG," "myoclonus without EEG correlate," "myoclonus with EEG correlate," and "status myoclonus." SSEP results were categorized as all absent, all present, N18 and N20 absent bilaterally, and N20 only absent bilaterally. Cox proportional hazards with censoring was used to evaluate the association of myoclonus category, SSEP results, and confounding factors with survival.

RESULTS

In 56 patients, median time from arrest to either confirmed death or last follow up was 9 days. The category of myoclonus was not associated with SSEP result or length of survival. Absence of N20 s or N18 s was associated with shorter survival (N20 hazard ratio [HR] 4.4, p = 0.0014; N18 HR 5.5, p < 0.00001).

CONCLUSIONS

Category of myoclonus did not reliably predict SSEP result. SSEP result was correlated with outcome consistently, but goals of care transitioned to comfort measures only in all patients with present peripheral potentials and either absent N20 s only or absence of N18 s and N20 s. Our results suggest that SSEPs may retain prognostic value in patients with post-anoxic myoclonus.

Endogenous orexin and hyperacute autonomic responses after resuscitation in a preclinical model of cardiac arrest

Objectives

The study of autonomic responses to cardiac arrest (CA) resuscitation deserves attention due to the impact of autonomic function on survival and arousal. Orexins are known to modulate autonomic function, but the role of endogenous orexin in hyperacute recovery of autonomic function post-resuscitation is not well understood. We hypothesized that endogenous orexin facilitates hyperacute cardiovascular sympathetic activity post-resuscitation, and this response could be attenuated by suvorexant, a dual orexin receptor antagonist.

Methods

A well-established 7-min asphyxial CA rat model was studied. Heart rate (HR) and blood pressure were monitored from baseline to 90-min post-resuscitation. Autonomic function was evaluated by spectral analysis of HR variability, whereby the ratio of low- and high-frequency components (LF/HF ratio) represents the balance between sympathetic/parasympathetic activities. Plasma orexin-A levels and orexin receptors immunoreactivity in the rostral ventrolateral medulla (RVLM), the key central region for regulating sympathetic output, were measured post-resuscitation. Neurological outcome was assessed via neurologic-deficit score at 4-h post-resuscitation.

Key results

A significant increase in HR was found over 25-40 min post-resuscitation (p < 0.01 vs. baseline), which was attenuated by suvorexant significantly (p < 0.05). Increased HR (from 15-to 25-min post-resuscitation) was correlated with better neurological outcomes (rs = 0.827, p = 0.005). There was no evident increase in mean arterial pressure over 25-40 min post-resuscitation, while systolic pressure was reduced greatly by suvorexant (p < 0.05). The LF/HF ratio was higher in animals with favorable outcomes than in animals injected with suvorexant over 30-40 min post-resuscitation (p < 0.05). Plasma orexin-A levels elevated at 15-min and peaked at 30-min post-resuscitation (p < 0.01 vs. baseline). Activated orexin receptors-immunoreactive neurons were found co-stained with tyrosine hydroxylase-immunopositive cells in the RVLM at 2-h post-resuscitation.

Conclusion

Together, increased HR and elevated LF/HF ratio indicative of sympathetic arousal during a critical window (25-40 min) post-resuscitation are observed in animals with favorable outcomes. The orexin system appears to facilitate this hyperacute autonomic response post-CA.

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.

The Association between Disseminated Intravascular Coagulation Profiles and Neurologic Outcome in Patients with In-Hospital Cardiac Arrest

Background

The relationship between disseminated intravascular coagulation (DIC) profiles and survival or neurological outcomes in out-of-hospital cardiac arrest (OHCA) patients is well known. In contrast, the relationship between DIC profiles and neurological outcomes in patients with in-hospital cardiac arrest (IHCA) remains unclear. This study sought to examine the correlation between DIC profiles and neurological outcomes in IHCA patients.

Methods

A retrospective observational study was conducted on comatose adult IHCA patients treated with targeted temperature management between January 2017 and December 2022. DIC profiles were used to calculate the DIC score, and were measured immediately after the return of spontaneous circulation (ROSC). The primary endpoint was a poor neurological outcome at six months, defined by cerebral performance in categories 3, 4, or 5. Multivariate analysis was used to evaluate the association between DIC profiles and poor neurological outcomes.

Results

The study included 136 patients, of which 107 (78.7%) patients demonstrated poor neurological outcomes. These patients had higher fibrinogen (3.2 g/L vs. 2.3 g/L) and fibrin degradation product levels (50.7 mg/L vs. 30.1 mg/L) and lower anti-thrombin III (ATIII) levels (65.7% vs. 82.3%). The DIC score did not differ between the good and poor outcome groups. In multivariable analysis, fibrinogen (odds ratio [OR], 1.009; 95% confidence intervals [CI], 1.003-1.016) and ATIII levels (OR, 0.965; 95% CI, 0.942-0.989) were independently associated with poor neurological outcomes.

Conclusions

Decreased fibrinogen and ATIII levels after ROSC were an independent risk factor for unfavorable neurological outcomes in IHCA. The DIC score is unlikely to play a significant role in IHCA prognosis in contrast to OHCA.

Performance of the ERC/ESICM-recommendations for neuroprognostication after cardiac arrest: Insights from a prospective multicenter cohort

AIM

To investigate the performance of the 2021 ERC/ESICM-recommended algorithm for predicting poor outcome after cardiac arrest (CA) and potential tools for predicting neurological recovery in patients with indeterminate outcome.

METHODS

Prospective, multicenter study on out-of-hospital CA survivors from 28 ICUs of the AfterROSC network. In patients comatose with a Glasgow Coma Scale motor score ≤3 at ≥72 h after resuscitation, we measured: (1) the accuracy of neurological examination, biomarkers (neuron-specific enolase, NSE), electrophysiology (EEG and SSEP) and neuroimaging (brain CT and MRI) for predicting poor outcome (modified Rankin scale score ≥4 at 90 days), and (2) the ability of low or decreasing NSE levels and benign EEG to predict good outcome in patients whose prognosis remained indeterminate.

RESULTS

Among 337 included patients, the ERC-ESICM algorithm predicted poor neurological outcome in 175 patients, and the positive predictive value for an unfavourable outcome was 100% [98-100]%. The specificity of individual predictors ranged from 90% for EEG to 100% for clinical examination and SSEP. Among the remaining 162 patients with indeterminate outcome, a combination of 2 favourable signs predicted good outcome with 99[96-100]% specificity and 23[11-38]% sensitivity.

CONCLUSION

All comatose resuscitated patients who fulfilled the ERC-ESICM criteria for poor outcome after CA had poor outcome at three months, even if a self-fulfilling prophecy cannot be completely excluded. In patients with indeterminate outcome (half of the population), favourable signs predicted neurological recovery, reducing prognostic uncertainty.

Factors Associated with Favorable Outcomes in Cardiac Arrest and Target Temperature Management

Current guidelines strongly recommend providing targeted temperature management (TTM) after cardiac arrest, but hypothalamic dysregulation may confound TTM's impact on a patient's ultimate outcome. Although time to reach target temperature has largely been viewed as a process measure for TTM protocols, the difference between initial presenting temperature and target temperature (Δ-temperature) may be a potential surrogate marker of hypothalamic dysregulation. We performed a retrospective observational study to explore whether Δ-temperature was associated with neurologic outcomes and mortality. We included 86 patients (53 with out-of-hospital cardiac arrest [OHCA] and 33 with in-hospital cardiac arrest [IHCA]) in our analysis; more than half of the patients were cooled to 33°C (56.9% in OHCA and 57.6% in IHCA). In univariate logistic regression analysis, Δ-temperature alone did not appear to be statistically associated with mortality or neurologic outcomes regardless of target temperature. In exploratory analysis, longer time from TTM initiation-to-target was associated with worse neurological outcomes in the 33°C target (odds ratio = 0.996, 95% confidence interval = 0.992-1.000). Further research investigating the impact of hypothalamic dysregulation and Δ-temperature as well as the rate of cooling may be warranted to elucidate additional factors contributing to outcomes after cardiac arrest. In addition, our study population was noted to have a higher proportion of Asians and Native Hawaiians/Pacific Islanders, with a potential disparity in outcomes. Future studies may be warranted to ensure generalizability of TTM protocols and findings across populations.

Sonographic evaluation of intracranial hemodynamics and pressure after out-of-hospital cardiac arrest: An exploratory sub-study of the TAME trial

Objective

Targeted mild hypercapnia is a potential neuroprotective therapy after cardiac arrest. In this exploratory observational study, we aimed to explore the effects of targeted mild hypercapnia on cerebral microvascular resistance assessed by middle cerebral artery pulsatility index (MCA PI) and intracranial pressure estimated by optic nerve sheath diameter (ONSD) in resuscitated out-of-hospital cardiac arrest (OHCA) patients.

Design setting participants and interventions

Comatose adults resuscitated from OHCA were randomly allocated to targeted mild hypercapnia (PaCO2 50-55 mmHg) or targeted normocapnia (PaCO2 35-45 mmHg) for 24 h in the TAME trial.

Main outcome measures

Using transcranial Doppler and transorbital ultrasound, we obtained MCA PI and ONSD at 4, 24, and 48 h after randomization. Ultrasound parameters were compared between groups using a linear mixed effects model.

Results

Twelve consecutive patients were included, with seven patients in the mild hypercapnia group. MCA PI decreased from 4 to 24 h (p = 0.019) and was lower over the first 24 h in patients allocated to targeted mild hypercapnia compared with targeted normocapnia (p = 0.047). ONSD did not differ between groups or over time.

Conclusion

Cerebral microvascular resistance assessed by MCA PI decreased over 24 h and was lower in OHCA patients treated with targeted mild hypercapnia compared with targeted normocapnia. Targeted mild hypercapnia did not exert substantial effect on intracranial pressure as estimated by ONSD.

Extracerebral multiple organ dysfunction and interactions with brain injury after cardiac arrest

Cardiac arrest and successful resuscitation cause whole-body ischemia and reperfusion, leading to brain injury and extracerebral multiple organ dysfunction. Brain injury is the leading cause of death and long-term disability in resuscitated survivors, and was conceptualized and treated as an isolated injury, which has neglected the brain-visceral organ crosstalk. Extracerebral organ dysfunction is common and is significantly associated with mortality and poor neurological prognosis after resuscitation. However, detailed description of the characteristics of post-resuscitation multiple organ dysfunction is lacking, and the bidirectional interactions between brain and visceral organs need to be elucidated to explore new treatment for neuroprotection. This review aims to describe current concepts of post-cardiac arrest brain injury and specific characteristics of post-resuscitation dysfunction in cardiovascular, respiratory, renal, hepatic, adrenal, gastrointestinal, and neurohumoral systems. Additionally, we discuss the crosstalk between brain and extracerebral organs, especially focusing on how visceral organ dysfunction and other factors affect brain injury progression. We think that clarifying these interactions is of profound significance on how we treat patients for neural/systemic protection to improve outcome.

Epidemiology of Seizures and Association With Mortality in Adult Patients Undergoing ECMO: A Systematic Review and Meta-analysis

BACKGROUND AND OBJECTIVES

Extracorporeal membrane oxygenation (ECMO) provides lifesaving support to patients with cardiopulmonary failure. Although seizures increase mortality risks among critically ill patients broadly, studies specific to adult ECMO patients have largely been limited to single-center studies. Thus, we aimed to perform a systematic review and meta-analyses of seizure prevalence, mortality, and their associations in adult ECMO patients.

METHODS

PubMed, EMBASE, Cochrane trial registry, Web of Science, and SCOPUS were searched on August 5, 2023. Following the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines, we included studies of adults undergoing venovenous ECMO (VV-ECMO), venoarterial ECMO (VA-ECMO), or extracorporeal cardiopulmonary resuscitation (ECPR) that reported seizures during ECMO. The extracted data included study characteristics, patient demographics, ECMO support, EEG monitoring, and seizures, organized by ECMO types. Forest plot and meta-regression analyses were performed. Bias assessment was performed with the Egger test and Newcastle-Ottawa Scale.

RESULTS

Twenty-three studies (n = 40,420, mean age = 51.8 years, male = 62%) were included. Data were extracted by ECMO type as follows: VV-ECMO (n = 16,633), non-ECPR VA-ECMO (n = 11,082), ECPR (n = 3,369), combination of VA-ECMO and ECPR (n = 240), and combination of all types (n = 9,096). The pooled seizure prevalence for all ECMO types was 3.0%, not significantly different across ECMO types (VV-ECMO = 2.0% [95% CI 0.8-4.5]; VA-ECMO = 3.5% [95% CI 1.7-7.0]; ECPR = 4.9% [95% CI 1.3-17.2]). The pooled mortality was lower for VV-ECMO (46.2% [95% CI 39.3-53.2]) than VA-ECMO (63.4% [95% CI 56.6-69.6]) and ECPR (61.5% [95% CI 57.3-65.6]). Specifically, for VV-ECMO, the pooled mortality of patients with and without seizures was 55.1% and 36.7%, respectively (relative risk = 1.5 [95% CI 1.3-1.7]). Similarly, for VA-ECMO, the pooled mortality of patients with and without seizures was 74.4% and 56.1%, respectively (relative risk = 1.3 [95% CI 1.2-1.5]). Meta-regression analyses demonstrated that seizure prevalence was not associated with prior neurologic comorbidities, adjusted for ECMO type and study year.

DISCUSSION

Seizures are infrequent during ECMO support. However, they were associated with increased mortality when present. Multi-institutional, larger-scale studies using standardized EEG monitoring are necessary to further understand the risk factors of specific classes of seizures for individual ECMO types, and their effects on mortality. Limitations of our study include missing data for details on seizure types, sedating/antiseizure medications used during ECMO, other ECMO-related complications, and EEG recording protocols.

Alteration in early resting‑state functional MRI activity in comatose survivors of cardiac arrest: a prospective cohort study

BACKGROUND

This study aimed to explore the characteristics of abnormal regional resting-state functional magnetic resonance imaging (rs-fMRI) activity in comatose patients in the early period after cardiac arrest (CA), and to investigate their relationships with neurological outcomes. We also explored the correlations between jugular venous oxygen saturation (SjvO2) and rs-fMRI activity in resuscitated comatose patients. We also examined the relationship between the amplitude of the N20-baseline and the rs-fMRI activity within the intracranial conduction pathway of somatosensory evoked potentials (SSEPs).

METHODS

Between January 2021 and January 2024, eligible post-resuscitated patients were screened to undergo fMRI examination. The amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo) of rs-fMRI blood oxygenation level-dependent (BOLD) signals were used to characterize regional neural activity. Neurological outcomes were evaluated using the Glasgow-Pittsburgh cerebral performance category (CPC) scale at 3 months after CA.

RESULTS

In total, 20 healthy controls and 31 post-resuscitated patients were enrolled in this study. The rs-fMRI activity of resuscitated patients revealed complex changes, characterized by increased activity in some local brain regions and reduced activity in others compared to healthy controls (P < 0.05). However, the mean ALFF values of the whole brain were significantly greater in CA patients (P = 0.011). Among the clusters of abnormal rs-fMRI activity, the cluster values of ALFF in the left middle temporal gyrus and inferior temporal gyrus and the cluster values of ReHo in the right precentral gyrus, superior frontal gyrus and middle frontal gyrus were strongly correlated with the CPC score (P < 0.001). There was a strong correlation between the mean ALFF and SjvO2 in CA patients (r = 0.910, P < 0.001). The SSEP N20-baseline amplitudes in CA patients were negatively correlated with thalamic rs-fMRI activity (all P < 0.001).

CONCLUSIONS

This study revealed that abnormal rs-fMRI BOLD signals in resuscitated patients showed complex changes, characterized by increased activity in some local brain regions and reduced activity in others. Abnormal BOLD signals were associated with neurological outcomes in resuscitated patients. The mean ALFF values of the whole brain were closely related to SjvO2 levels, and changes in the thalamic BOLD signals correlated with the N20-baseline amplitudes of SSEP responses.

TRIAL REGISTRATION

NCT05966389 (Registered July 27, 2023).

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

Clinical conversations surrounding the continuation or limitation of life-sustaining therapies (LLST) are both challenging and tragically necessary for patients with disorders of consciousness (DoC) following severe brain injury. Divergent cultural, philosophical and religious perspectives contribute to vast heterogeneity in clinical approaches to LLST-as reflected in regional differences and inter-clinician variability. Here we provide an ethical analysis of factors that inform LLST decisions among patients with DoC. We begin by introducing the clinical and ethical challenge and clarifying the distinction between withdrawing and withholding life-sustaining therapy. We then describe relevant factors that influence LLST decision-making including diagnostic and prognostic uncertainty, perception of pain, defining a 'good' outcome, and the role of clinicians. In concluding sections, we explore global variation in LLST practices as they pertain to patients with DoC and examine the impact of cultural and religious perspectives on approaches to LLST. Understanding and respecting the cultural and religious perspectives of patients and surrogates is essential to protecting patient autonomy and advancing goal-concordant care during critical moments of medical decision-making involving patients with DoC.

Regional Brain Net Water Uptake in Computed Tomography after Cardiac Arrest - A Novel Biomarker for Neuroprognostication

BACKGROUND

Selective water uptake by neurons and glial cells and subsequent brain tissue oedema are key pathophysiological processes of hypoxic-ischemic encephalopathy (HIE) after cardiac arrest (CA). Although brain computed tomography (CT) is widely used to assess the severity of HIE, changes of brain radiodensity over time have not been investigated. These could be used to quantify regional brain net water uptake (NWU), a potential prognostic biomarker.

METHODS

We conducted an observational prognostic accuracy study including a derivation (single center cardiac arrest registry) and a validation (international multicenter TTM2 trial) cohort. Early (<6 h) and follow-up (>24 h) head CTs of CA patients were used to determine regional NWU for grey and white matter regions after co-registration with a brain atlas. Neurological outcome was dichotomized as good versus poor using the Cerebral Performance Category Scale (CPC) in the derivation cohort and Modified Rankin Scale (mRS) in the validation cohort.

RESULTS

We included 115 patients (81 derivation, 34 validation) with out-of-hospital (OHCA) and in-hospital cardiac arrest (IHCA). Regional brain water content remained unchanged in patients with good outcome. In patients with poor neurological outcome, we found considerable regional water uptake with the strongest effect in the basal ganglia. NWU >8% in the putamen and caudate nucleus predicted poor outcome with 100% specificity (95%-CI: 86-100%) and 43% (moderate) sensitivity (95%-CI: 31-56%).

CONCLUSION

This pilot study indicates that NWU derived from serial head CTs is a promising novel biomarker for outcome prediction after CA. NWU >8% in basal ganglia grey matter regions predicted poor outcome while absence of NWU indicated good outcome. NWU and follow-up CTs should be investigated in larger, prospective trials with standardized CT acquisition protocols.

Impact of Lactate Clearance on Clinical and Neurological Outcomes of Patients With Out-of-Hospital Cardiac Arrest Treated With Extracorporeal Cardiopulmonary Resuscitation: A Secondary Data Analysis

OBJECTIVES

Serial evaluations of lactate concentration may be more useful in predicting outcomes in patients with out-of-hospital cardiac arrest (OHCA) than a single measurement. This study aimed to evaluate the impact of lactate clearance (LC) on clinical and neurologic outcomes in patients with OHCA who underwent extracorporeal cardiopulmonary resuscitation (ECPR).

DESIGN

Retrospective multicenter observational study.

SETTING

Patients with OHCA receiving ECPR at 36 hospitals in Japan between January 1, 2013, and December 31, 2018.

PATIENTS

This study evaluated 1227 patients, with lactate initial assessed upon emergency department admission and lactate second measured subsequently. To adjust for the disparity in the time between lactate measurements, the modified 6-hour LC was defined as follows: ([lactate initial -lactate second ]/lactate initial ) × 100 × (6/the duration between the initial and second measurements [hr]). The patients were divided into four groups according to the modified 6-hour LC with an equivalent number of patients among LC quartiles: Q1 (LC < 18.8), Q2 (18.8 < LC < 59.9), Q3 (60.0 < LC < 101.2), and Q4 (101.2 < LC).

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

The 30-day survival rates increased as the 6-hour LC increased (Q1, 21.2%; Q2, 36.8%; Q3, 41.4%; Q4, 53.6%; p for trend < 0.001). In the multivariate analysis, the modified 6-hour LC was significantly associated with a 30-day survival rate (adjusted odds ratio [AOR], 1.003; 95% CI, 1.001-1.005; p < 0.001) and favorable neurologic outcome (AOR, 1.002; 95% CI, 1.000-1.004; p = 0.027).

CONCLUSIONS

In patients with OHCA who underwent ECPR, an increase in the modified 6-hour LC was associated with favorable clinical and neurologic outcome. Thus, LC can be a criterion to assess whether ECPR should be continued.

Standardised and automated assessment of head computed tomography reliably predicts poor functional outcome after cardiac arrest: a prospective multicentre study

PURPOSE

Application of standardised and automated assessments of head computed tomography (CT) for neuroprognostication after out-of-hospital cardiac arrest.

METHODS

Prospective, international, multicentre, observational study within the Targeted Hypothermia versus Targeted Normothermia after out-of-hospital cardiac arrest (TTM2) trial. Routine CTs from adult unconscious patients obtained > 48 h ≤ 7 days post-arrest were assessed qualitatively and quantitatively by seven international raters blinded to clinical information using a pre-published protocol. Grey-white-matter ratio (GWR) was calculated from four (GWR-4) and eight (GWR-8) regions of interest manually placed at the basal ganglia level. Additionally, GWR was obtained using an automated atlas-based approach. Prognostic accuracies for prediction of poor functional outcome (modified Rankin Scale 4-6) for the qualitative assessment and for the pre-defined GWR cutoff < 1.10 were calculated.

RESULTS

140 unconscious patients were included; median age was 68 years (interquartile range [IQR] 59-76), 76% were male, and 75% had poor outcome. Standardised qualitative assessment and all GWR models predicted poor outcome with 100% specificity (95% confidence interval [CI] 90-100). Sensitivity in median was 37% for the standardised qualitative assessment, 39% for GWR-8, 30% for GWR-4 and 41% for automated GWR. GWR-8 was superior to GWR-4 regarding prognostic accuracies, intra- and interrater agreement. Overall prognostic accuracy for automated GWR (area under the curve [AUC] 0.84, 95% CI 0.77-0.91) did not significantly differ from manually obtained GWR.

CONCLUSION

Standardised qualitative and quantitative assessments of CT are reliable and feasible methods to predict poor functional outcome after cardiac arrest. Automated GWR has the potential to make CT quantification for neuroprognostication accessible to all centres treating cardiac arrest patients.

Individualized music induces theta-gamma phase-amplitude coupling in patients with disorders of consciousness

Objective

This study aimed to determine whether patients with disorders of consciousness (DoC) could experience neural entrainment to individualized music, which explored the cross-modal influences of music on patients with DoC through phase-amplitude coupling (PAC). Furthermore, the study assessed the efficacy of individualized music or preferred music (PM) versus relaxing music (RM) in impacting patient outcomes, and examined the role of cross-modal influences in determining these outcomes.

Methods

Thirty-two patients with DoC [17 with vegetative state/unresponsive wakefulness syndrome (VS/UWS) and 15 with minimally conscious state (MCS)], alongside 16 healthy controls (HCs), were recruited for this study. Neural activities in the frontal-parietal network were recorded using scalp electroencephalography (EEG) during baseline (BL), RM and PM. Cerebral-acoustic coherence (CACoh) was explored to investigate participants' abilitiy to track music, meanwhile, the phase-amplitude coupling (PAC) was utilized to evaluate the cross-modal influences of music. Three months post-intervention, the outcomes of patients with DoC were followed up using the Coma Recovery Scale-Revised (CRS-R).

Results

HCs and patients with MCS showed higher CACoh compared to VS/UWS patients within musical pulse frequency (p = 0.016, p = 0.045; p < 0.001, p = 0.048, for RM and PM, respectively, following Bonferroni correction). Only theta-gamma PAC demonstrated a significant interaction effect between groups and music conditions (F (2,44) = 2.685, p = 0.036). For HCs, the theta-gamma PAC in the frontal-parietal network was stronger in the PM condition compared to the RM (p = 0.016) and BL condition (p < 0.001). For patients with MCS, the theta-gamma PAC was stronger in the PM than in the BL (p = 0.040), while no difference was observed among the three music conditions in patients with VS/UWS. Additionally, we found that MCS patients who showed improved outcomes after 3 months exhibited evident neural responses to preferred music (p = 0.019). Furthermore, the ratio of theta-gamma coupling changes in PM relative to BL could predict clinical outcomes in MCS patients (r = 0.992, p < 0.001).

Conclusion

Individualized music may serve as a potential therapeutic method for patients with DoC through cross-modal influences, which rely on enhanced theta-gamma PAC within the consciousness-related network.

Ferroptosis-related gene MAPK3 is associated with the neurological outcome after cardiac arrest

BACKGROUND

Neuronal ferroptosis is closely related to the disease of the nervous system, and the objective of the present study was to recognize and verify the potential ferroptosis-related genes to forecast the neurological outcome after cardiac arrest.

METHODS

Cardiac Arrest-related microarray datasets GSE29540 and GSE92696 were downloaded from GEO and batch normalization of the expression data was performed using "sva" of the R package. GSE29540 was analyzed to identify DEGs. Venn diagram was applied to recognize ferroptosis-related DEGs from the DEGs. Subsequently, The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed, and PPI network was applied to screen hub genes. Receiver operating characteristic (ROC) curves were adopted to determine the predictive value of the biomarkers, and the GSE92696 dataset was applied to further evaluate the diagnostic efficacy of the biomarkers. We explore transcription factors and miRNAs associated with hub genes. The "CIBERSORT" package of R was utilized to analyse the proportion infiltrating immune cells. Finally, validated by a series of experiments at the cellular level.

RESULTS

112 overlapping ferroptosis-related DEGs were further obtained via intersecting these DEGs and ferroptosis-related genes. The GO and KEGG analysis demonstrate that ferroptosis-related DEGs are mainly involved in response to oxidative stress, ferroptosis, apoptosis, IL-17 signalling pathway, autophagy, toll-like receptor signalling pathway. The top 10 hub genes were selected, including HIF1A, MAPK3, PPARA, IL1B, PTGS2, RELA, TLR4, KEAP1, SREBF1, SIRT6. Only MAPK3 was upregulated in both GSE29540 and GAE92696. The AUC values of the MAPK3 are 0.654 and 0.850 in GSE29540 and GSE92696 respectively. The result of miRNAs associated with hub genes indicates that hsa-miR-214-3p and hsa-miR-483-5p can regulate the expression of MAPK3. MAPK3 was positively correlated with naive B cells, macrophages M0, activated dendritic cells and negatively correlated with activated CD4 memory T cells, CD8 T cells, and memory B cells. Compared to the OGD4/R24 group, the OGD4/R12 group had higher MAPK3 expression at both mRNA and protein levels and more severe ferroptosis.

CONCLUSION

In summary, the MAPK3 ferroptosis-related gene could be used as a biomarker to predict the neurological outcome after cardiac arrest. Potential biological pathways provide novel insights into the pathogenesis of cardiac arrest.

Association Between QRS Characteristics in Pulseless Electrical Activity and Survival Outcome in Cardiac Arrest Patients: A Systematic Review and Meta-Analysis

OBJECTIVE

Recent studies have shown inconsistent results regarding the association between QRS characteristics and survival outcomes in patients with cardiac arrest and pulseless electrical activity (PEA) rhythms. This meta-analysis aimed to identify the usefulness of QRS width and frequency as prognostic tools for outcomes in patients with cardiac arrest and PEA rhythm.

METHODS

Extensive searches were conducted using Medline, Embase, and the Cochrane Library to find articles published from database inception to 4 June 2023. Studies that assessed the association between the QRS characteristics of cardiac arrest patients with PEA rhythm and survival outcomes were included. The Newcastle-Ottawa Scale was used to assess the methodological quality of the included studies.

RESULTS

A total of 9727 patients from seven observational studies were included in this systematic review and meta-analysis. The wide QRS group (QRS ≥ 120 ms) was associated with significantly higher odds of mortality than the narrow QRS group (QRS < 120 ms) (odds ratio (OR) = 1.86, 95% confidence interval (CI) = 1.11-3.11, I2 = 58%). The pooled OR for mortality was significantly higher in patients with a QRS frequency of < 60/min than in those with a QRS frequency of ≥ 60/min (OR = 1.90, 95% CI = 1.19-3.02, I2 = 65%).

CONCLUSIONS

Wide QRS width or low QRS frequency is associated with increased odds of mortality in patients with PEA cardiac arrest. These findings may be beneficial to guide the disposition of cardiac arrest patients with PEA during resuscitation.

Prediction of outcomes after cardiac arrest by a generative artificial intelligence model

Aims

To investigate the prognostic accuracy of a non-medical generative artificial intelligence model (Chat Generative Pre-Trained Transformer 4 - ChatGPT-4) as a novel aspect in predicting death and poor neurological outcome at hospital discharge based on real-life data from cardiac arrest patients.

Methods

This prospective cohort study investigates the prognostic performance of ChatGPT-4 to predict outcomes at hospital discharge of adult cardiac arrest patients admitted to intensive care at a large Swiss tertiary academic medical center (COMMUNICATE/PROPHETIC cohort study). We prompted ChatGPT-4 with sixteen prognostic parameters derived from established post-cardiac arrest scores for each patient. We compared the prognostic performance of ChatGPT-4 regarding the area under the curve (AUC), sensitivity, specificity, positive and negative predictive values, and likelihood ratios of three cardiac arrest scores (Out-of-Hospital Cardiac Arrest [OHCA], Cardiac Arrest Hospital Prognosis [CAHP], and PROgnostication using LOGistic regression model for Unselected adult cardiac arrest patients in the Early stages [PROLOGUE score]) for in-hospital mortality and poor neurological outcome.

Results

Mortality at hospital discharge was 43% (n = 309/713), 54% of patients (n = 387/713) had a poor neurological outcome. ChatGPT-4 showed good discrimination regarding in-hospital mortality with an AUC of 0.85, similar to the OHCA, CAHP, and PROLOGUE (AUCs of 0.82, 0.83, and 0.84, respectively) scores. For poor neurological outcome, ChatGPT-4 showed a similar prediction to the post-cardiac arrest scores (AUC 0.83).

Conclusions

ChatGPT-4 showed a similar performance in predicting mortality and poor neurological outcome compared to validated post-cardiac arrest scores. However, more research is needed regarding illogical answers for potential incorporation of an LLM in the multimodal outcome prognostication after cardiac arrest.

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.