Prognostication after cardiac arrest

Analysis of Cerebral CT Based on Supervised Machine Learning as a Predictor of Outcome After Out-of-Hospital Cardiac Arrest

BACKGROUND AND OBJECTIVES

In light of limited intensive care capacities and a lack of accurate prognostic tools to advise caregivers and family members responsibly, this study aims to determine whether automated cerebral CT (CCT) analysis allows prognostication after out-of-hospital cardiac arrest.

METHODS

In this monocentric, retrospective cohort study, a supervised machine learning classifier based on an elastic net regularized logistic regression model for gray matter alterations on nonenhanced CCT obtained after cardiac arrest was trained using 10-fold cross-validation and tested on a hold-out sample (random split 75%/25%) for outcome prediction. Following the literature, a favorable outcome was defined as a cerebral performance category of 1-2 and a poor outcome of 3-5. The diagnostic accuracy was compared with established and guideline-recommended prognostic measures within the sample, that is, gray matter-white matter ratio (GWR), neuron-specific enolase (NSE), and neurofilament light chain (NfL) in serum.

RESULTS

Of 279 adult patients, 132 who underwent CCT within 14 days of cardiac arrest with good imaging quality were identified. Our approach discriminated between favorable and poor outcomes with an area under the curve (AUC) of 0.73 (95% CI 0.59-0.82). Thus, the prognostic power outperformed the GWR (AUC 0.66, 95% CI 0.56-0.76). The biomarkers NfL, measured at days 1 and 2, and NSE, measured at day 2, exceeded the reliability of the imaging markers derived from CT (AUC NfL day 1: 0.87, 95% CI 0.75-0.99; AUC NfL day 2: 0.90, 95% CI 0.79-1.00; AUC NSE day: 2 0.78, 95% CI 0.62-0.94).

DISCUSSION

Our data show that machine learning-assisted gray matter analysis of CCT images offers prognostic information after out-of-hospital cardiac arrest. Thus, CCT gray matter analysis could become a reliable and time-independent addition to the standard workup with serum biomarkers sampled at predefined time points. Prospective studies are warranted to replicate these findings.

Early predictive value of lipocalin-type prostaglandin D synthase for 28-day mortality in cardiac arrest patients: study protocol for a prospective study

INTRODUCTION

Public training in cardiopulmonary resuscitation and treatment in emergency and intensive care unit have made tremendous progress. However, cardiac arrest remains a major health burden worldwide, with brain damage being a significant contributor to disability and mortality. Lipocalin-type prostaglandin D synthase (L-PGDS), which is mainly localised in the central nervous system, has been previously shown to inhibit postischemia neuronal apoptosis. Therefore, we aim to observe whether serum L-PGDS can serve as a potential biomarker and explore its role in determining the severity and prognosis of patients who have achieved restoration of spontaneous circulation (ROSC).

METHODS AND ANALYSIS

This is a prospective observational study. The participants (n = 60) who achieve ROSC will be distributed into two groups (non-survivor and survivor) based on 28-day survival. Healthy volunteers (n = 30) will be enrolled as controls. Each individual's relevant information will be extracted from Electronic Medical Record System in Xinhua Hospital, including demographic characteristics, clinical data, laboratory findings and so on. On days 1, 3 and 7 after ROSC, blood samples will be drawn and batch tested on the level of serum neuron-specific enolase, soluble protein 100β, L-PGDS, procalcitonin, tumour necrosis factor-alpha and interleukin-6. The cerebral performance category score was assessed on the 28th day after ROSC.

ETHICS AND DISSEMINATION

This study was performed with the approval of the Clinical Ethical Committee of Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine (Approval No. XHEC-C-2023-130-1). The results will be published in a peer-reviewed journal.

TRIAL REGISTRATION NUMBER

Chinese Clinical Trial Registry (ChiCTR2300078564).

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.

Effects of Dexmedetomidine Added to Ropivacaine in Ultrasound-Guided Continuous Pericapsular Nerve Group Block Among Elderly Patients Undergoing Total Hip Arthroplasty

Total hip arthroplasty (THA) is a highly effective intervention for addressing hip joint issues, yet managing perioperative pain remains a significant challenge. In this study, we aimed to investigate the impact of supplementing ropivacaine with dexmedetomidine in ultrasound-guided continuous pericapsular nerve group block (PENGB) among elderly patients undergoing THA. We conducted a retrospective analysis involving 112 elderly patients who underwent THA. These patients were divided into two groups: the Control group, receiving ropivacaine alone, and the DEX group, receiving ropivacaine combined with dexmedetomidine. We evaluated various parameters including hemodynamic data, postoperative pain levels assessed using the Visual Analog Scale, cognitive status measured with the Montreal Cognitive Assessment, and serum markers (S100β and GFAP). Our findings revealed that the DEX group exhibited improved stability in blood pressure and oxygen saturation following surgery. Moreover, patients in the DEX group reported significantly lower levels of pain at 6 and 12 hours postsurgery, with a prolonged duration of pain relief. Furthermore, dexmedetomidine administration was associated with preserved cognitive function during the early postoperative period. Analysis of serum markers suggested potential cognitive protection conferred by the addition of dexmedetomidine. Overall, our study underscores the multifaceted benefits of incorporating dexmedetomidine into ropivacaine-based PENGB for elderly THA patients.

The agreement between jugular bulb and cerebrospinal fluid lactate levels in patients with out-of-hospital cardiac arrest

We investigated the agreement between the jugular bulb (JB) and cerebrospinal fluid (CSF) lactate levels. The study was conducted from July 2021 to June 2023 as a prospective observational cohort study at a single center. The right jugular vein was accessed, and the placement of JB catheter tip was confirmed using lateral cervical spine X-ray. A lumbar catheter was inserted between the 3rd and 4th lumbar spine of the patient. Lactate levels were measured immediately, 24 h, 48 h, and 72 h after ROSC. In patients with a good neurological prognosis, kappa between JB and CSF lactate levels measured immediately, at 24 h, 48 h, and 72 h after ROSC were 0.08, 0.36, 0.14, - 0.05 (p = 0.65, 0.06, 0.48, and 0.75, respectively). However, in patients with a poor neurological prognosis, kappa between JB and CSF lactate levels measured immediately, at 24 h, 48 h, and 72 h after ROSC were 0.38, 0.21, 0.22, 0.12 (p = 0.001, 0.04, 0.04, and 0.27, respectively). This study demonstrated that JB lactate levels exhibited significant agreement with arterial lactate levels, compared to CSF lactate levels. Therefore, this should be considered when using JB lactate to monitor cerebral metabolism.

EEG Pattern With Spectral Analysis Can Prognosticate Good and Poor Neurologic Outcomes After Cardiac Arrest

PURPOSE

To investigate the prognostic value of a simple stratification system of electroencephalographical (EEG) patterns and spectral types for patients after cardiac arrest.

METHODS

In this prospectively enrolled cohort, using manually selected EEG segments, patients after cardiac arrest were stratified into five independent EEG patterns (based on background continuity and burden of highly epileptiform discharges) and four independent power spectral types (based on the presence of frequency components). The primary outcome is cerebral performance category (CPC) at discharge. Results from multimodal prognostication testing were included for comparison.

RESULTS

Of a total of 72 patients, 6 had CPC 1-2 by discharge, all of whom had mostly continuous EEG background without highly epileptiform activity at day 3. However, for the same EEG background pattern at day 3, 19 patients were discharged at CPC 3 and 15 patients at CPC 4-5. After adding spectral analysis, overall sensitivity for predicting good outcomes (CPC 1-2) was 83.3% (95% confidence interval 35.9% to 99.6%) and specificity was 97.0% (89.5% to 99.6%). In this cohort, standard prognostication testing all yielded 100% specificity but low sensitivity, with imaging being the most sensitive at 54.1% (36.9% to 70.5%).

CONCLUSIONS

Adding spectral analysis to qualitative EEG analysis may further improve the diagnostic accuracy of EEG and may aid developing novel measures linked to good outcomes in postcardiac arrest coma.

Prognostic Performance of Initial Clinical Examination in Predicting Good Neurological Outcome in Cardiac Arrest Patients Treated with Targeted Temperature Management

Prognostication studies of cardiac arrest patients have mainly focused on poor neurological outcomes. However, an optimistic prognosis for good outcome could provide both justification to maintain and escalate treatment and evidence-based support to persuade family members or legal surrogates after cardiac arrest. The aim of the study was to evaluate the utility of clinical examinations performed after return of spontaneous circulation (ROSC) in predicting good neurological outcomes in out-of-hospital cardiac arrest (OHCA) patients treated with targeted temperature management (TTM). This retrospective study included OHCA patients treated with TTM from 2009 to 2021. Initial clinical examination findings related to the Glasgow coma scale (GCS) motor score, pupillary light reflex, corneal reflex (CR) and breathing above the set ventilator rate were assessed immediately after ROSC and before the initiation of TTM. The primary outcome was good neurological outcome at 6 months after cardiac arrest. Of 350 patients included in the analysis, 119 (34%) experienced a good neurological outcome at 6 months after cardiac arrest. Among the parameters of the initial clinical examinations, specificity was the highest for the GCS motor score, and sensitivity was the highest for breathing above the set ventilator rate. A GCS motor score of >2 had a sensitivity of 42.0% (95% confidence interval [CI] = 33.0-51.4) and a specificity of 96.5% (95% CI = 93.3-98.5). Breathing above the set ventilator rate had a sensitivity of 84.0% (95% CI = 76.2-90.1) and a specificity of 69.7% (95% CI = 63.3-75.6). As the number of positive responses increased, the proportion of patients with good outcomes increased. Consequently, 87.0% of patients for whom all four examinations were positive experienced good outcomes. As a result, the initial clinical examinations predicted good neurological outcomes with a sensitivity of 42.0-84.0% and a specificity of 69.7-96.5%. When more examinations with positive results are achieved, a good neurological outcome can be expected.

A Comprehensive Review and Practical Guide of the Applications of Evoked Potentials in Neuroprognostication After Cardiac Arrest

Cardiorespiratory arrest is a very common cause of morbidity and mortality nowadays, and many therapeutic strategies, such as induced coma or targeted temperature management, are used to reduce patient sequelae. However, these procedures can alter a patient's neurological status, making it difficult to obtain useful clinical information for the reliable estimation of neurological prognosis. Therefore, complementary investigations are conducted in the early stages after a cardiac arrest to clarify functional prognosis in comatose cardiac arrest survivors in the first few hours or days. Current practice relies on a multimodal approach, which shows its greatest potential in predicting poor functional prognosis, whereas the data and tools to identify patients with good functional prognosis remain relatively limited in comparison. Therefore, there is considerable interest in investigating alternative biological parameters and advanced imaging technique studies. Among these, somatosensory evoked potentials (SSEPs) remain one of the simplest and most reliable tools. In this article, we discuss the technical principles, advantages, limitations, and prognostic implications of SSEPs in detail. We will also review other types of evoked potentials that can provide useful information but are less commonly used in clinical practice (e.g., visual evoked potentials; short-, medium-, and long-latency auditory evoked potentials; and event-related evoked potentials, such as mismatch negativity or P300).

Recovery and Survival of Patients After Out-of-Hospital Cardiac Arrest: A Literature Review Showcasing the Big Picture of Intensive Care Unit-Related Factors

As an important public health issue, out-of-hospital cardiac arrest (OHCA) requires several stages of high quality medical care, both on-field and after hospital admission. Post-cardiac arrest shock can lead to severe neurological injury, resulting in poor recovery outcome and increased risk of death. These characteristics make this condition one of the most important issues to deal with in post-OHCA patients hospitalized in intensive care units (ICUs). Also, the majority of initial post-resuscitation survivors have underlying coronary diseases making revascularization procedure another crucial step in early management of these patients. Besides keeping myocardial blood flow at a satisfactory level, other tissues must not be neglected as well, and maintaining mean arterial pressure within optimal range is also preferable. All these procedures can be simplified to a certain level along with using targeted temperature management methods in order to decrease metabolic demands in ICU-hospitalized post-OHCA patients. Additionally, withdrawal of life-sustaining therapy as a controversial ethical topic is under constant re-evaluation due to its possible influence on overall mortality rates in patients initially surviving OHCA. Focusing on all of these important points in process of managing ICU patients is an imperative towards better survival and complete recovery rates.

Neurological outcomes and quality of life in post-cardiac arrest patients with return of spontaneous circulation supported by ECMO: A retrospective case series

Post-cardiac arrest brain injury constitutes a significant contributor to morbidity and mortality, leading to cognitive impairment and subsequent disability. Individuals within this patient cohort grapple with uncertainty regarding the potential advantages of extracorporeal life support (ECMO) cannulation. This study elucidates the neurological outcomes and quality of life of post-cardiac arrest patients who attained spontaneous circulation and underwent ECMO cannulation. This is a retrospective case study within a local context, the research involved 32 patients who received ECMO support following an intrahospital cardiac arrest with return of spontaneous circulation (ROSC). An additional 32 patients experienced cardiac arrest with ROSC before undergoing cannulation. The average age was 41 years, with the primary causes of cardiac arrest identified as acute coronary syndrome (46.8%), pulmonary thromboembolism (21.88%), and hypoxemia (18.7%). The most prevalent arrest rhythm was asystole (37.5%), followed by ventricular fibrillation (34.4%). The mean SOFA score was 7 points (IQR 6.5-9), APACHE II score was 12 (IQR 9-16), RESP score was -1 (IQR -1 to -4) in cases of respiratory ECMO, and SAVE score was -3 (IQR -5 to 2) in cases of cardiac ECMO. Overall survival was 71%, and at 6 months, the Barthel score was 75 points, modified Rankin score was 2, cerebral performance categories score was 1, and the SF-12 had an average score of 30. Notably, there were no significant associations between the time, cause, or rhythm of cardiac arrest and neurological outcomes. Importantly, cardiac arrest is not a contraindication for ECMO cannulation. A meticulous assessment of candidates who have achieved spontaneous circulation after cardiac arrest, considering the absence of early signs of poor neurological prognosis, is crucial in patient selection. Larger prospective studies are warranted to validate and extend these findings.

Fingerprint of Circulating Immunocytes as Biomarkers for the Prognosis of Brain Inflammation and Neuronal Injury after Cardiac Arrest

Cardiac arrest is one of the most dangerous health problems in the world. Outcome prognosis is largely based on cerebral performance categories determined by neurological evaluations. Few systemic tests are currently available to predict survival to hospital discharge. Here, we present the results from the preclinical studies of cardiac arrest and resuscitation (CAR) in mice to identify signatures of circulating immune cells as blood-derived biomarkers to predict outcomes after CAR. Two flow cytometry panels for circulating blood lymphocytes and myeloid-derived cells, respectively, were designed to correlate with neuroinflammation and neuronal and dendritic losses in the selectively vulnerable regions of bilateral hippocampi. We found that CD4+CD25+ regulatory T cells, CD11b+CD11c- and CD11b+Ly6C+Ly6G+ myeloid-derived cells, and cells positive for the costimulatory molecules CD80 and CD86 in the blood were correlated with activation of microglia and astrocytosis, and CD4+CD25+ T cells are additionally correlated with neuronal and dendritic losses. A fingerprint pattern of blood T cells and monocytes is devised as a diagnostic tool to predict CAR outcomes. Blood tests aimed at identifying these immunocyte patterns in cardiac arrest patients will guide future clinical trials to establish better prognostication tools to avoid unnecessary early withdrawal from life-sustaining treatment.

Common Data Elements for Disorders of Consciousness: Recommendations from the Electrophysiology Working Group

BACKGROUND

Electroencephalography (EEG) has long been recognized as an important tool in the investigation of disorders of consciousness (DoC). From inspection of the raw EEG to the implementation of quantitative EEG, and more recently in the use of perturbed EEG, it is paramount to providing accurate diagnostic and prognostic information in the care of patients with DoC. However, a nomenclature for variables that establishes a convention for naming, defining, and structuring data for clinical research variables currently is lacking. As such, the Neurocritical Care Society's Curing Coma Campaign convened nine working groups composed of experts in the field to construct common data elements (CDEs) to provide recommendations for DoC, with the main goal of facilitating data collection and standardization of reporting. This article summarizes the recommendations of the electrophysiology DoC working group.

METHODS

After assessing previously published pertinent CDEs, we developed new CDEs and categorized them into "disease core," "basic," "supplemental," and "exploratory." Key EEG design elements, defined as concepts that pertained to a methodological parameter relevant to the acquisition, processing, or analysis of data, were also included but were not classified as CDEs.

RESULTS

After identifying existing pertinent CDEs and developing novel CDEs for electrophysiology in DoC, variables were organized into a framework based on the two primary categories of resting state EEG and perturbed EEG. Using this categorical framework, two case report forms were generated by the working group.

CONCLUSIONS

Adherence to the recommendations outlined by the electrophysiology working group in the resting state EEG and perturbed EEG case report forms will facilitate data collection and sharing in DoC research on an international level. In turn, this will allow for more informed and reliable comparison of results across studies, facilitating further advancement in the realm of DoC research.

Longitudinal serum neurofilament light kinetics in post-anoxic encephalopathy

Serum neurofilament light (sNfL) is a promising marker of outcome after cardiac arrest, but its kinetics are unclear. We prospectively measured sNfL concentrations in 62 patients at 0, 1, 3, 5, 7 and 10 days after cardiac arrest. Survivors and non-survivors had similar sNfL at admission (14.2 [8.6-21.9] vs. 22.5 [14.2-46.9] pg/mL) but largely different at 24 h (16.4 [10.2-293] vs. 464.3 [151.8-1658.2], respectively). The AUC for sNfL concentrations predicting death was above 0.95 from Day 1 to 10 (highest on Day 3). Late sNfL measurements may exert prognostic value, especially when early samples are unavailable or prognosis remains unclear.

Predicting neurologic recovery after severe acute brain injury using resting-state networks

OBJECTIVE

There is a lack of reliable tools used to predict functional recovery in unresponsive patients following a severe brain injury. The objective of the study is to evaluate the prognostic utility of resting-state functional magnetic resonance imaging for predicting good neurologic recovery in unresponsive patients with severe brain injury in the intensive-care unit.

METHODS

Each patient underwent a 5.5-min resting-state scan and ten resting-state networks were extracted via independent component analysis. The Glasgow Outcome Scale was used to classify patients into good and poor outcome groups. The Nearest Centroid classifier used each patient's ten resting-state network values to predict best neurologic outcome within 6 months post-injury.

RESULTS

Of the 25 patients enrolled (mean age = 43.68, range = [19-69]; GCS ≤ 9; 6 females), 10 had good and 15 had poor outcome. The classifier correctly and confidently predicted 8/10 patients with good and 12/15 patients with poor outcome (mean = 0.793, CI = [0.700, 0.886], Z = 2.843, p = 0.002). The prediction performance was largely determined by three visual (medial: Z = 3.11, p = 0.002; occipital pole: Z = 2.44, p = 0.015; lateral: Z = 2.85, p = 0.004) and the left frontoparietal network (Z = 2.179, p = 0.029).

DISCUSSION

Our approach correctly identified good functional outcome with higher sensitivity (80%) than traditional prognostic measures. By revealing preserved networks in the absence of discernible behavioral signs, functional connectivity may aid in the prognostic process and affect the outcome of discussions surrounding withdrawal of life-sustaining measures.

Electroencephalography Prediction of Neurological Outcomes After Hypoxic-Ischemic Brain Injury: A Systematic Review and Meta-Analysis

Background. Predicting neurological outcomes after hypoxic-ischemic brain injury (HIBI) is difficult. Objective. Electroencephalography (EEG) can identify acute and subacute brain abnormalities after hypoxic brain injury and predict HIBI recovery. We examined EEG's ability to predict neurologic outcomes following HIBI. Method. A PRISMA-compliant search was conducted in the Medline, Embase, Cochrane, and Central databases until January 2023. EEG-predicted neurological outcomes in HIBI patients were selected from relevant perspective and retrospective cohort studies. RevMan did meta-analysis, while QDAS2 assessed research quality. Results. Eleven studies with 3761 HIBI patients met the inclusion and exclusion criteria. We aggregated study-level estimates of sensitivity and specificity for EEG patterns determined a priori using random effect bivariate and univariate meta-analysis when appropriate. Positive indicators and anatomical area heterogeneity impacted prognosis accuracy. Funnel plots analyzed publication bias. Significant heterogeneity of greater than 80% was among the included studies with P < 0.001. The area under the curve was 0.94, the threshold effect was P < 0.001, and the sensitivity and specificity, with 95% confidence intervals, were 0.91 (0.84-0.99) and 0.86 (0.75-0.97). EEG detects status epilepticus and burst suppression with good sensitivity, specificity, and little probability of false-negative impairment result attribution. Study quality varied by domain, but patient flow and timing were well conducted in all. Conclusion. EEG can predict the outcome of HIBI with good prognostic accuracy, but more standardized cross-study protocols and descriptions of EEG patterns are needed to better evaluate its prognostic use for patients with HIBI.

Outcome of comatose patients following cardiac arrest: When mRS completes CPC

AIM

Good outcome in patients following cardiac arrest (CA) is usually defined as Cerebral Performance Category (CPC) 1-2, while CPC 3 is debated, and CPC 4-5 represent poor outcome. We aimed to assess when the modified Rankin Scale (mRS) can improve CPC outcome description, especially in CPC 3. We further aimed to correlate neuron specific enolase (NSE) with both functional measures to explore their relationship with neuronal damage.

METHODS

Peak NSE within the first 48 hours, and CPC and mRS at 3 months were prospectively collected for 665 consecutive comatose adults following CA treated between April 2016 and April 2023. For each CPC category, mRS was described. We considered good outcome as mRS 1-3, in line with existing recommendations. CPC and mRS were correlated to peak serum NSE using non-parametric assessments.

RESULTS

CPC 1, 2, 4 and 5 correlated almost perfectly with mRS in terms of good and poor outcomes. However, CPC 3 was heterogeneously associated to the dichotomized mRS (53.1% had good outcome (mRS 0-3), 46.9% poor outcome (mRS 4-6)). NSE was strongly correlated with CPC (Spearman's rho 0.616, P < 0.001) and mRS (Spearman's rho 0.613, P < 0.001).

CONCLUSION

CPC and mRS correlate similarly with neuronal damage. Whilst CPC 1-2 and CPC 4-5 are strongly associated with mRS 0-3 and, respectively, with mRS 5-6, CPC 3 is heterogenous: both good and poor mRS scores are found within this category. Therefore, we suggest that the mRS should be routinely assessed in patients with CPC 3 to refine outcome description.

Alterations of the gut microbial community structure modulates the Th17 cells response in a rat model of asphyxial cardiac arrest

Th17 cells triggered inflammation is a critical element in cerebral ischemic injury, and the gut microbiota intricately impacts T lymphocytes. Nevertheless, it remains unclear whether the gut microbiota involves in cardiac arrest/cardiopulmonary resuscitation (CA/CPR) induced-brain injury through Th17 cells. The present study investigated the interaction between gut microbiota and Th17 cells in a rat model. We observed that CA/CPR induced the alterations of the gut microbial community structure, and elevated the level of IL-17 in the serum, and a slight infiltration of Th17 cells into the brain. The Th17 cells were increased significantly in the peripheral blood, 28.33 ± 6.18% of these Th17 cells were derived from the Peyer's patches of small intestine. Furthermore, fecal microbiota transplantation (FMT) from rats with CA/CPR induced Th17 cell response, promoting hippocampal cell apoptosis and declining learning ability and memory in recipient rats. Taken together, CA/CPR-induced alterations of the gut microbial community structure stimulated Th17 cell response which aggravated brain injury.

Different neuroprognostication thresholds of neuron-specific enolase in shockable and non-shockable out-of-hospital cardiac arrest: a prospective multicenter observational study in Korea (the KORHN-PRO registry)

BACKGROUND

Serum neuron-specific enolase (NSE) is the only recommended biomarker for multimodal prognostication in postcardiac arrest patients, but low sensitivity of absolute NSE threshold limits its utility. This study aimed to evaluate the prognostic performance of serum NSE for poor neurologic outcome in out-of-hospital cardiac arrest (OHCA) survivors based on their initial rhythm and to determine the NSE cutoff values with false positive rate (FPR) < 1% for each group.

METHODS

This study included OHCA survivors who received targeted temperature management (TTM) and had serum NSE levels measured at 48 h after return of spontaneous circulation in the Korean Hypothermia Network, a prospective multicenter registry from 22 university-affiliated teaching hospitals in South Korea between October 2015 and December 2018. The primary outcome was poor outcome at 6 month, defined as a cerebral performance category of 3-5.

RESULTS

Of 623 patients who underwent TTM with NSE measured 48 h after the return of spontaneous circulation, 245 had an initial shockable rhythm. Median NSE level was significantly higher in the non-shockable group than in the shockable group (104.6 [40.6-228.4] vs. 25.9 [16.7-53.4] ng/mL, P < 0.001). Prognostic performance of NSE assessed by area under the receiver operating characteristic curve to predict poor outcome was significantly higher in the non-shockable group than in the shockable group (0.92 vs 0.86). NSE cutoff values with an FPR < 1% in the non-shockable and shockable groups were 69.3 (sensitivity of 42.1%) and 102.7 ng/mL (sensitivity of 76%), respectively.

CONCLUSION

NSE prognostic performance and its cutoff values with FPR < 1% for predicting poor outcome in OHCA survivors who underwent TTM differed between shockable and non-shockable rhythms, suggesting postcardiac arrest survivor heterogeneity. Trial registration KORHN-PRO, NCT02827422. Registered 11 September 2016-Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT02827422.

Prognosis of Cardiac Arrest-Peri-arrest and Post-arrest Considerations

There has been only a small improvement in survival and neurologic outcomes in patients with cardiac arrest in recent decades. Type of arrest, length of total arrest time, and location of arrest alter the trajectory of survival and neurologic outcome. In the post-arrest phase, clinical markers such as blood markers, pupillary light response, corneal reflex, myoclonic jerking, somatosensory evoked potential, and electroencephalography testing can be used to help guide neurological prognostication. Most of the testing should be performed 72 hours post-arrest with special considerations for longer observation periods in patients who underwent TTM or who had prolonged sedation and/or neuromuscular blockade.

Deep learning for EEG-based prognostication after cardiac arrest: from current research to future clinical applications

Outcome prognostication in comatose patients after cardiac arrest (CA) remains to date a challenge. The major determinant of clinical outcome is the post-hypoxic/ischemic encephalopathy. Electroencephalography (EEG) is routinely used to assess neural functions in comatose patients. Currently, EEG-based outcome prognosis relies on visual evaluation by medical experts, which is time consuming, prone to subjectivity, and oblivious to complex patterns. The field of deep learning has given rise to powerful algorithms for detecting patterns in large amounts of data. Analyzing EEG signals of coma patients with deep neural networks with the goal of assisting in outcome prognosis is therefore a natural application of these algorithms. Here, we provide the first narrative literature review on the use of deep learning for prognostication after CA. Existing studies show overall high performance in predicting outcome, relying either on spontaneous or on auditory evoked EEG signals. Moreover, the literature is concerned with algorithmic interpretability, and has shown that largely, deep neural networks base their decisions on clinically or neurophysiologically meaningful features. We conclude this review by discussing considerations that the fields of artificial intelligence and neurology will need to jointly address in the future, in order for deep learning algorithms to break the publication barrier, and to be integrated in clinical practice.

A Template for Translational Bioinformatics: Facilitating Multimodal Data Analyses in Preclinical Models of Neurological Injury

Background

Pediatric neurological injury and disease is a critical public health issue due to increasing rates of survival from primary injuries (e.g., cardiac arrest, traumatic brain injury) and a lack of monitoring technologies and therapeutics for the treatment of secondary neurological injury. Translational, preclinical research facilitates the development of solutions to address this growing issue but is hindered by a lack of available data frameworks and standards for the management, processing, and analysis of multimodal data sets.

Methods

Here, we present a generalizable data framework that was implemented for large animal research at the Children's Hospital of Philadelphia to address this technological gap. The presented framework culminates in an interactive dashboard for exploratory analysis and filtered data set download.

Results

Compared with existing clinical and preclinical data management solutions, the presented framework accommodates heterogeneous data types (single measure, repeated measures, time series, and imaging), integrates data sets across various experimental models, and facilitates dynamic visualization of integrated data sets. We present a use case of this framework for predictive model development for intra-arrest prediction of cardiopulmonary resuscitation outcome.

Conclusions

The described preclinical data framework may serve as a template to aid in data management efforts in other translational research labs that generate heterogeneous data sets and require a dynamic platform that can easily evolve alongside their research.

Relationship between serum neuron-specific enolase and EEG after cardiac arrest: A reappraisal

OBJECTIVE

Electroencephalogram (EEG) and serum neuron specific enolase (NSE) are frequently used prognosticators after cardiac arrest (CA). This study explored the association between NSE and EEG, considering the role of EEG timing, its background continuity, reactivity, occurrence of epileptiform discharges, and pre-defined malignancy degree.

METHODS

Retrospective analysis including 445 consecutive adults from a prospective registry, surviving the first 24 hours after CA and undergoing multimodal evaluation. EEG were interpreted blinded to NSE results.

RESULTS

Higher NSE was associated with poor EEG prognosticators, such as increasing malignancy, repetitive epileptiform discharges and lack of background reactivity, independently of EEG timing (including sedation and temperature). When stratified for background continuity, NSE was higher with repetitive epileptiform discharges, except in the case of suppressed EEGs. This relationship showed some variation according to the recording time.

CONCLUSIONS

Neuronal injury after CA, reflected by NSE, correlates with several EEG features: increasing EEG malignancy, lack of background reactivity, and presence of repetitive epileptiform discharges. The correlation between epileptiform discharges and NSE is influenced by underlying EEG background and timing.

SIGNIFICANCE

This study, describing the complex interplay between serum NSE and epileptiform features, suggests that epileptiform discharges reflect neuronal injury particularly in non-suppressed EEG.

Clinical presentation, diagnosis, treatment, and outcome in 8 dogs and 2 cats with global hypoxic-ischemic brain injury (2010-2022)

BACKGROUND

Global hypoxic-ischemic brain injury (GHIBI) results in variable degrees of neurological dysfunction. Limited data exists to guide prognostication on likelihood of functional recovery.

HYPOTHESIS

Prolonged duration of hypoxic-ischemic insult and absence of neurological improvement in the first 72 hours are negative prognostic indicators.

ANIMALS

Ten clinical cases with GHIBI.

METHODS

Retrospective case series describing 8 dogs and 2 cats with GHIBI, including clinical signs, treatment, and outcome.

RESULTS

Six dogs and 2 cats experienced cardiopulmonary arrest or anesthetic complication in a veterinary hospital and were promptly resuscitated. Seven showed progressive neurological improvement within 72 hours of the hypoxic-ischemic insult. Four fully recovered and 3 had residual neurological deficits. One dog presented comatose after resuscitation at the primary care practice. Magnetic resonance imaging confirmed diffuse cerebral cortical swelling and severe brainstem compression and the dog was euthanized. Two dogs suffered out-of-hospital cardiopulmonary arrest, secondary to a road traffic accident in 1 and laryngeal obstruction in the other. The first dog was euthanized after MRI that identified diffuse cerebral cortical swelling with severe brainstem compression. In the other dog, spontaneous circulation was recovered after 22 minutes of cardiopulmonary resuscitation. However, the dog remained blind, disorientated, and ambulatory tetraparetic with vestibular ataxia and was euthanized 58 days after presentation. Histopathological examination of the brain confirmed severe diffuse cerebral and cerebellar cortical necrosis.

CONCLUSIONS AND CLINICAL IMPORTANCE

Duration of hypoxic-ischemic insult, diffuse brainstem involvement, MRI features, and rate of neurological recovery could provide indications of the likelihood of functional recovery after GHIBI.

Cardiac arrest centres: what do they add?

There are wide regional variations in outcome following resuscitated out of hospital cardiac arrest. These geographical differences appear to be due to hospital infrastructure and provider experience rather than baseline characteristics. It is proposed that post-arrest care be delivered in a systematic fashion by concentrating services in Cardiac Arrest Centres, with greater provider experience, 24-hour access to diagnostics, and specialist treatment to minimise the impact of ischaemia-reperfusion injury and treat the causative pathology. These cardiac arrest centres would provide access to targeted critical care, acute cardiac care, radiology services and appropriate neuro-prognostication. However implementation of cardiac arrest networks with specialist receiving hospitals is complex and requires alignment of pre-hospital care services with those delivered in hospital. Furthermore there are no randomised trial data currently supporting pre-hospital delivery to a Cardiac Arrest Centre and definitions are heterogeneous. In this review article, we propose a universal definition of a Cardiac Arrest Centre and review the current observational data evidence and the potential impact of the ARREST trial.

Hypoxic-Ischemic Brain Injury in ECMO: Pathophysiology, Neuromonitoring, and Therapeutic Opportunities

Extracorporeal membrane oxygenation (ECMO), in conjunction with its life-saving benefits, carries a significant risk of acute brain injury (ABI). Hypoxic-ischemic brain injury (HIBI) is one of the most common types of ABI in ECMO patients. Various risk factors, such as history of hypertension, high day 1 lactate level, low pH, cannulation technique, large peri-cannulation PaCO2 drop (∆PaCO2), and early low pulse pressure, have been associated with the development of HIBI in ECMO patients. The pathogenic mechanisms of HIBI in ECMO are complex and multifactorial, attributing to the underlying pathology requiring initiation of ECMO and the risk of HIBI associated with ECMO itself. HIBI is likely to occur in the peri-cannulation or peri-decannulation time secondary to underlying refractory cardiopulmonary failure before or after ECMO. Current therapeutics target pathological mechanisms, cerebral hypoxia and ischemia, by employing targeted temperature management in the case of extracorporeal cardiopulmonary resuscitation (eCPR), and optimizing cerebral O2 saturations and cerebral perfusion. This review describes the pathophysiology, neuromonitoring, and therapeutic techniques to improve neurological outcomes in ECMO patients in order to prevent and minimize the morbidity of HIBI. Further studies aimed at standardizing the most relevant neuromonitoring techniques, optimizing cerebral perfusion, and minimizing the severity of HIBI once it occurs will improve long-term neurological outcomes in ECMO patients.

Temperature Control After Cardiac Arrest: A Narrative Review

Cardiac arrest (CA) is a critical public health issue affecting more than half a million Americans annually. The main determinant of outcome post-CA is hypoxic-ischemic brain injury (HIBI), and temperature control is currently the only evidence-based, guideline-recommended intervention targeting secondary brain injury. Temperature control is a key component of a post-CA care bundle; however, conflicting evidence challenges its wide implementation across the vastly heterogeneous population of CA survivors. Here, we critically appraise the available literature on temperature control in HIBI, detail how the evidence has been integrated into clinical practice, and highlight the complications associated with its use and the timing of neuroprognostication after CA. Future clinical trials evaluating different temperature targets, rates of rewarming, duration of cooling, and identifying which patient phenotype benefits from different temperature control methods are needed to address these prevailing knowledge gaps.

Diagnostic Value of Serum Lactate Dehydrogenase Level Measured in the Emergency Department in Predicting Clinical Outcome in Out-of-Hospital Cardiac Arrest: A Multicenter, Observational Study

INTRODUCTION

Out-of-hospital cardiac arrest (OHCA) is complex, and risk stratification tools have the potential to include components other than clinical risk indicators, thus requiring extensive studies. Simple and accurate biomarkers for OHCA patients with poor prognoses are still needed. Serum lactate dehydrogenase (LDH) has been identified as a risk factor in patients with various diseases, such as cancer, liver disease, severe infections, and sepsis. The primary aim of this study was to assess the accuracy of LDH values at initial presentation in the emergency department (ED) in predicting the clinical outcome in OHCA.

METHODS

This retrospective multicenter observational study was performed in the ED of two tertiary university hospitals and one general hospital between January 2015 and December 2021. All patients with OHCA who visited the ED were included. The primary outcome was the sustained return of spontaneous circulation (ROSC; >20 min) after advanced cardiac life support (ACLS). The secondary outcome was survival to discharge (including home care and nursing care discharge) among patients with ROSC. The neurological prognosis was considered a tertiary outcome in patients who survived to discharge.

RESULTS

In total, 759 patients were enrolled in the final analysis. The median LDH level in the ROSC group was 448 U/L (range: 112-4500), which was significantly lower than that in the no-ROSC group (p < 0.001). The median LDH level in the survival-to-discharge group was 376 U/L (range: 171-1620), which was significantly lower than that in the death group (p < 0.001). Using the adjusted model, the odds ratio of the LDH value (≤634 U/L) for primary outcomes was 2.418 (1.665-3.513) and the odds ratio of LDH value (≤553 U/L) for secondary outcomes was 4.961 (2.184-11.269).

CONCLUSIONS

In conclusion, the serum LDH levels of patients with OHCA measured in the ED can potentially serve as a predictive marker for clinical outcomes such as ROSC and survival to discharge, although it may be difficult to predict neurological outcomes.

Explainable artificial intelligence-based prediction of poor neurological outcome from head computed tomography in the immediate post-resuscitation phase

Predicting poor neurological outcomes after resuscitation is important for planning treatment strategies. We constructed an explainable artificial intelligence-based prognostic model using head computed tomography (CT) scans taken immediately within 3 h of resuscitation from cardiac arrest and compared its predictive accuracy with that of previous methods using gray-to-white matter ratio (GWR). We included 321 consecutive patients admitted to our institution after resuscitation for out-of-hospital cardiopulmonary arrest with circulation resumption over 6 years. A machine learning model using head CT images with transfer learning was used to predict the neurological outcomes at 1 month. These predictions were compared with the predictions of GWR for multiple regions of interest in head CT using receiver operating characteristic (ROC)-area under curve (AUC) and precision recall (PR)-AUC. The regions of focus were visualized using a heatmap. Both methods had similar ROC-AUCs, but the machine learning model had a higher PR-AUC (0.73 vs. 0.58). The machine learning-focused area of interest for classification was the boundary between gray and white matter, which overlapped with the area of focus when diagnosing hypoxic- ischemic brain injury. The machine learning model for predicting poor outcomes had superior accuracy to conventional methods and could help optimize treatment.

External validation of the PROLOGUE score to predict neurological outcome in adult patients after cardiac arrest: a prospective cohort study

BACKGROUND

The PROLOGUE score (PROgnostication using LOGistic regression model for Unselected adult cardiac arrest patients in the Early stages) is a novel prognostic model for the prediction of neurological outcome after cardiac arrest, which showed exceptional performance in the internal validation. The aim of this study is to validate the PROLOGUE score in an independent cohort of unselected adult cardiac arrest patients and to compare it to the thoroughly validated Out-of-Hospital Cardiac Arrest (OHCA) and Cardiac Arrest Hospital Prognosis (CAHP) scores.

METHODS

This study included consecutive adult cardiac arrest patients admitted to the intensive care unit (ICU) of a Swiss tertiary teaching hospital between October 2012 and July 2022. The primary endpoint was poor neurological outcome at hospital discharge, defined as a Cerebral Performance Category (CPC) score of 3 to 5 including death.

RESULTS

Of 687 patients included in the analysis, 321 (46.7%) survived to hospital discharge with good neurological outcome, 68 (9.9%) survived with poor neurological outcome and 298 (43.4%) died. The PROLOGUE score showed an area under the receiver operating characteristic curve (AUROC) of 0.83 (95% CI 0.80 to 0.86) and good calibration for the prediction of the primary outcome. The OHCA and CAHP score showed similar performance (AUROC 0.83 and 0.84 respectively), the differences between the three scores were not significant (p = 0.495). In a subgroup analysis, the PROLOGUE score performed equally in out-of-hospital and in-hospital cardiac arrest patients whereas the OHCA and CAHP score performed significantly better in OHCA patients.

CONCLUSION

The PROLOGUE score showed good prognostic accuracy for the early prediction of neurological outcome in adult cardiac arrest survivors in our cohort and might support early goals-of-care discussions in the ICU. Trial registration Not applicable.

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

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

Early Versus Delayed Coronary Angiography After Out-of-Hospital Cardiac Arrest Without ST-Segment Elevation-A Systematic Review and Meta-Analysis of Randomized Controlled Trials

The optimal timing of coronary angiography remains unclear following out-of-hospital cardiac arrest (OHCA) without ST elevation on electrocardiogram. The objective of this systematic review and meta-analysis was to evaluate the efficacy and safety of early angiography versus delayed angiography following OHCA without ST elevation.

DATA SOURCES

The databases MEDLINE, PubMed EMBASE, and CINHAL, as well as unpublished sources from inception to March 9, 2022.

STUDY SELECTION

A systematic search was performed for randomized controlled trials of adult patients after OHCA without ST elevation who were randomized to early as compared to delayed angiography.

DATA EXTRACTION

Reviewers screened and abstracted data independently and in duplicate. The certainty of evidence was assessed for each outcome using the Grading Recommendations Assessment, Development and Evaluation approach. The protocol was preregistered (CRD 42021292228).

DATA SYNTHESIS

Six trials were included (n = 1,590 patients). Early angiography probably has no effect on mortality (relative risk [RR] 1.04; 95% CI 0.94-1.15; moderate certainty) and may have no effect on survival with good neurologic outcome (RR 0.97; 95% CI 0.87-1.07; low certainty) or ICU length of stay (LOS) (mean difference 0.41 days fewer; 95% CI -1.3 to 0.5 d; low certainty). Early angiography has an uncertain effect on adverse events.

CONCLUSIONS

In OHCA patients without ST elevation, early angiography probably has no effect on mortality and may have no effect on survival with good neurologic outcome and ICU LOS. Early angiography has an uncertain effect on adverse events.

Comparison of in-hospital outcomes of acute myocardial infarction between patients with cardiogenic shock and with cardiac arrest

In-hospital mortality of acute myocardial infarction (AMI) complicated with cardiogenic shock (CS) remains high. Also, in-hospital mortality of AMI complicated with cardiac arrest (CA) has been reported to be highest among any AMI. However, there were few reports that compared in-hospital mortality directly between AMI complicated with CS and complicated with CA. The purpose of this study was to compare in-hospital outcomes between AMI complicated with CS and complicated with CA. We retrospectively included 195 AMI patients complicated by CS or CA, and divided those into the CA group (n = 109) and the CS group (n = 86). We also subdivided the CA group into CA with persistent CS (n = 83) and CA without persistent CS (n = 26). One-third of the study population died during the index admission. In-hospital death was more frequently observed in the CA group (45.0%) than in the CS group (20.9%) (p < 0.001). In-hospital mortality was highest in the CA with persistent CS group (68.7%), followed by the CS group (20.9%), and least in the CA without persistent CS group (11.5%) (p < 0.001). Favorable neurological function was more frequently observed in the CA without persistent CS group (76.9%) and the CS group (74.4%) than in the CA with persistent CS group (27.7%) (p < 0.001). In conclusion, in-hospital mortality was higher in AMI patients with CA than in those with CS. However, when we divided AMI patients with CA into those with and without persistent CS, in-hospital mortality was lowest in CA without persistent CS, followed by CS, and highest in CA with persistent CS.

Post-Cardiac Arrest: Mechanisms, Management, and Future Perspectives

Cardiac arrest is an important public health issue, with a survival rate of approximately 15 to 22%. A great proportion of these deaths occur after resuscitation due to post-cardiac arrest syndrome, which is characterized by the ischemia-reperfusion injury that affects the role body. Understanding physiopathology is mandatory to discover new treatment strategies and obtain better results. Besides improvements in cardiopulmonary resuscitation maneuvers, the great increase in survival rates observed in recent decades is due to new approaches to post-cardiac arrest care. In this review, we will discuss physiopathology, etiologies, and post-resuscitation care, emphasizing targeted temperature management, early coronary angiography, and rehabilitation.

Predicting neurological outcome in adult patients with cardiac arrest: systematic review and meta-analysis of prediction model performance

This work aims to assess the performance of two post-arrest (out-of-hospital cardiac arrest, OHCA, and cardiac arrest hospital prognosis, CAHP) and one pre-arrest (good outcome following attempted resuscitation, GO-FAR) prediction model for the prognostication of neurological outcome after cardiac arrest in a systematic review and meta-analysis. A systematic search was conducted in Embase, Medline, and Web of Science Core Collection from November 2006 to December 2021, and by forward citation tracking of key score publications. The search identified 1'021 records, of which 25 studies with a total of 124'168 patients were included in the review. A random-effects meta-analysis of C-statistics and overall calibration (total observed vs. expected [O:E] ratio) was conducted. Discriminatory performance was good for the OHCA (summary C-statistic: 0.83 [95% CI 0.81-0.85], 16 cohorts) and CAHP score (summary C-statistic: 0.84 [95% CI 0.82-0.87], 14 cohorts) and acceptable for the GO-FAR score (summary C-statistic: 0.78 [95% CI 0.72-0.84], five cohorts). Overall calibration was good for the OHCA (total O:E ratio: 0.78 [95% CI 0.67-0.92], nine cohorts) and the CAHP score (total O:E ratio: 0.78 [95% CI 0.72-0.84], nine cohorts) with an overestimation of poor outcome. Overall calibration of the GO-FAR score was poor with an underestimation of good outcome (total O:E ratio: 1.62 [95% CI 1.28-2.04], five cohorts). Two post-arrest scores showed good prognostic accuracy for predicting neurological outcome after cardiac arrest and may support early discussions about goals-of-care and therapeutic planning on the intensive care unit. A pre-arrest score showed acceptable prognostic accuracy and may support code status discussions.

Hypothermia and its role in patients with ST-segment-elevation myocardial infarction and cardiac arrest

Background

Patients suffering cardiac arrest resulting from ST-segment-elevation myocardial infarction (STEMI) are at very high risk of death. In addition to reperfusion strategies, therapeutic hypothermia is recommended for cardiac arrest patients who remain unconscious after resuscitation. However, data analysis of the impact of therapeutic hypothermia on survival showed inconsistent results. We aimed to investigate the benefits of therapeutic hypothermia in STEMI patients after cardiopulmonary resuscitation (CPR).

Methods

Patients with STEMI who received CPR were identified after nationwide German inpatient data (2005–2019) were screened. These patients were stratified for therapeutic hypothermia. The impact of hypothermia on mortality and adverse in-hospital outcomes was analyzed.

Results

Overall, 133,070 inpatients with STEMI and CPR (53.3% aged ≥70 years; 34% females) were recorded in Germany between 2005 and 2019, of which 12.3% (16,386 patients) underwent therapeutic hypothermia. Females (23.8 vs. 35.4%, p &lt; 0.001) and patients aged ≥70 years (34.9 vs. 55.9%, p &lt; 0.001) were less frequently treated with therapeutic hypothermia. The in-hospital case fatality rate was lower for STEMI with CPR and subsequent therapeutic hypothermia than for treatment without therapeutic hypothermia (53.5 vs. 66.7%, p &lt; 0.001). Therapeutic hypothermia was independently associated with a reduced in-hospital case fatality rate {OR 0.83 [95% confidence interval (CI) 0.80–0.86], p &lt; 0.001}. In addition, therapeutic hypothermia was associated with an increased risk for stroke (OR 1.37 [95% CI 1.25–1.49], p &lt; 0.001), pneumonia (OR 1.75 [95% CI 1.68–1.82], p &lt; 0.001), and acute kidney injury (OR 2.21 [95% CI 2.07–2.35], p &lt; 0.001).

Conclusion

Therapeutic hypothermia is associated with a survival benefit for STEMI patients after cardiac arrest.

Cerebral monitoring in a pig model of cardiac arrest with 48 h of intensive care

Background

Neurological injury is the primary cause of death after out-of-hospital cardiac arrest. There is a lack of studies investigating cerebral injury beyond the immediate post-resuscitation phase in a controlled cardiac arrest experimental setting.

Methods

The aim of this study was to investigate temporal changes in measures of cerebral injury and metabolism in a cardiac arrest pig model with clinically relevant post-cardiac arrest intensive care. A cardiac arrest group (n = 11) underwent 7 min of no-flow and was compared with a sham group (n = 6). Pigs underwent intensive care with 24 h of hypothermia at 33 °C. Blood markers of cerebral injury, cerebral microdialysis, and intracranial pressure (ICP) were measured. After 48 h, pigs underwent a cerebral MRI scan. Data are presented as median [25th; 75th percentiles].

Results

Return of spontaneous circulation was achieved in 7/11 pigs. Time to ROSC was 4.4 min [4.2; 10.9]. Both NSE and NfL increased over time (p < 0.001), and were higher in the cardiac arrest group at 48 h (NSE 4.2 µg/L [2.4; 6.1] vs 0.9 [0.7; 0.9], p < 0.001; NfL 63 ng/L [35; 232] vs 29 [21; 34], p = 0.02). There was no difference in ICP at 48 h (17 mmHg [14; 24] vs 18 [13; 20], p = 0.44). The cerebral lactate/pyruvate ratio had secondary surges in 3/7 cardiac arrest pigs after successful resuscitation. Apparent diffusion coefficient was lower in the cardiac arrest group in white matter cortex (689 × 10^–6 mm²/s [524; 765] vs 800 [799; 815], p = 0.04) and hippocampus (854 [834; 910] vs 1049 [964; 1180], p = 0.03). N-Acetylaspartate was lower on MR spectroscopy in the cardiac arrest group (− 17.2 log [− 17.4; − 17.0] vs − 16.9 [− 16.9; − 16.9], p = 0.03).

Conclusions

We have developed a clinically relevant cardiac arrest pig model that displays cerebral injury as marked by NSE and NfL elevations, signs of cerebral oedema, and reduced neuron viability. Overall, the burden of elevated ICP was low in the cardiac arrest group. A subset of pigs undergoing cardiac arrest had persisting metabolic disturbances after successful resuscitation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40635-022-00475-2.

Impact of admitting department on the management of acute coronary syndrome after an out of hospital cardiac arrest

AIM

This study aimed to analyze the influence of the hospital admitting department on adherence to the Guidelines of European Society of Cardiology for management of acute coronary syndromes in patients after out-of-hospital cardiac arrest (OHCA) of coronary etiology.

METHODS

We studied retrospective-prospective register of 102 consecutive patients with OHCA as a manifestation of acute coronary syndrome (ACS). Patients were admitted to the coronary care unit (CCU) 52, general intensive care unit (GICU) 21, or GICU after initial Cath lab treatment (CAG-GICU) 29. This study compared the differences in the management of ACS in patients with OHCA of coronary etiology based on the admitting department in a tertiary care institution.

RESULTS

Twelve of the 21 (57.1%) patients admitted to the GICU were evaluated as having ACS on-site where they experienced OHCA. In the CCU group, 50 out of 52 (96.2%) and 28 of 29 (100%) patients in the CAG-GICU group (P<0.001). Coronary angiography was performed in 10 of 21 patients (48%) admitted to the GICU. It was performed in 49 out of 52 (94%) CCU patients and, in the CAG-GICU group, 28 out of 29 patients. The mean time to CAG differed significantly across groups (that is, GICU 200.7 min., CCU 71.2 min., and CAG-GICU 7.5 min. (P<0.001)). Aspirin was used in 48% of GICU, 96% of CCU, and 79% of CAG-GICU patients (P<0.001), while in the pre-hospital phase, aspirin was used in 9.5% of GICU, 71.2% of CCU, and 50% of CAG-GICU patients (P<0.001). P2Y12 inhibitor prescriptions were lower in patients admitted to the GICU (33% vs. 89% CCU and 57% CAG-GICU, P<0.001). The department's choice significantly affected the time to initiation of antithrombotics, which was the longest in the GICU.

CONCLUSION

The choice of admission department for patients with OHCA caused by ACS was found to affect the extent to which the recommended treatments were used. An examination of OHCA patients by a cardiologist upon admission to the hospital increased the likelihood of an early diagnosis of ACS as the cause of OHCA.

Diagnostic and prognostic EEG analysis of critically ill patients: A deep learning study

Visual interpretation of electroencephalography (EEG) is time consuming, may lack objectivity, and is restricted to features detectable by a human. Computer-based approaches, especially deep learning, could potentially overcome these limitations. However, most deep learning studies focus on a specific question or a single pathology. Here we explore the potential of deep learning for EEG-based diagnostic and prognostic assessment of patients with acute consciousness impairment (ACI) of various etiologies. EEGs from 358 adults from a randomized controlled trial (CERTA, NCT03129438) were retrospectively analyzed. A convolutional neural network was used to predict the clinical outcome (based either on survival or on best cerebral performance category) and to determine the etiology (four diagnostic categories). The largest probability output served as marker for the confidence of the network in its prediction ("certainty factor"); we also systematically compared the predictions with raw EEG data, and used a visualization algorithm (Grad-CAM) to highlight discriminative patterns. When all patients were considered, the area under the receiver operating characteristic curve (AUC) was 0.721 for predicting survival and 0.703 for predicting the outcome based on best CPC; for patients with certainty factor ≥ 60 % the AUCs increased to 0.776 and 0.755 respectively; and for certainty factor ≥ 75 % to 0.852 and 0.879. The accuracy for predicting the etiology was 54.5 %; the accuracy increased to 67.7 %, 70.3 % and 84.1 % for patients with certainty factor of 50 %, 60 % and 75 % respectively. Visual analysis showed that the network learnt EEG patterns typically recognized by human experts, and suggested new criteria. This work demonstrates for the first time the potential of deep learning-based EEG analysis in critically ill patients with various etiologies of ACI. Certainty factor and post-hoc correlation of input data with prediction help to better characterize the method and pave the route for future implementations in clinical routine.

A technical solution to a professional problem: The risk management functions of prognosticators in the context of prognostication post-cardiac arrest

Cardiac arrest (CA) is a major cause of mortality and morbidity globally. Two-thirds of deaths among patients admitted to intensive care units following out-of-hospital CA are due to neurological injury, with most as a consequence of withdrawing life-sustaining treatment, following prognostication of unfavorable neurological outcome. Given the ramifications of prognosis for patient outcome, post-cardiac arrest (P-CA) guidelines stress the importance of minimizing the risk of falsely pessimistic predictions. Although prognosticator use is advocated to this end, 100% accurate prognosticators remain elusive, therefore prognostication P-CA remains pervaded by uncertainty and risk. Bioethical discourse notwithstanding, when located within a wider socio-cultural context, prognostication can be seen to present risk and uncertainty challenges of a professional nature. Such challenges do not, however, subvert the medical profession's moral and ethical prognostication obligation. We interpret prognosticator use as an attempt to manage professional risk presented by prognostication P-CA and demonstrate how through performing "risk work," prognosticators serve professional functions, mediating tension between the professional duty to prognosticate, and risk presented. We draw on sociological analyses of risk and uncertainty, and the professions to explicate these (hitherto less enunciated) professional risk management functions of prognosticators. Accordingly, the use of prognosticators is conceived of as a professional response - a technical/scientific solution to the problem of professional risk, inherent within the P-CA prognostication process.

Functional and Prognostic Assessment in Comatose Patients: A Study Using Somatosensory Evoked Potentials

Aim

The functional prognosis of patients after coma following either cardiac arrest (CA) or acute structural brain injury (ABI) is often uncertain. These patients are associated with high mortality and disability. N20 and N70 somatosensory evoked potentials (SSEP) are used to predict prognosis. We evaluated the utility of SSEP (N20–N70) as an early indicator of long-term prognosis in these patients.

Methods

This was a retrospective cohort study of patients (n = 120) admitted to the intensive care unit (ICU) with a diagnosis of coma after CA (n = 60) or ABI (n = 60). An SSEP study was performed, including N20 and N70 at 24–72 h, after coma onset. Functional recovery was assessed 6–12 months later using the modified Glasgow scale (mGS). The study was approved by our local research ethics committee.

Results

In the CA and ABI groups, the absence of N20 (36% of CA patients and 41% of ABI patients; specificity = 100%) or N70 (68% of CA patients and 78% of ABI patients) was a strong indicator of poor outcome. Conversely, the presence of N70 was an indicator of a good outcome (AC: specificity = 84.2%, sensitivity = 92.7%; ABI: specificity = 64.2% sensitivity = 91.3%).

Conclusion

Somatosensory evoked potentials are useful early prognostic markers with high specificity (N20) and sensitivity (N70). Moreover, N70 has additional potential value for improving the prediction of good long-term functional outcomes.

Clinical Trial Registration:

[https://clinicaltrials.gov/], identifier [2018/01/001].

Serum SCUBE-1 Levels and Return of Spontaneous Circulation Following Cardiopulmonary Resuscitation in Adult Patients

Background  SCUBE 1-has been used as a biomarker for the diagnoses of myocardial infarction, stroke, mesenteric ischemia, and gastric cancer in some recent studies. In this study, we investigated the relationship between serum SCUBE−1 levels and return of spontaneous circulation (ROSC) in patients who received cardiopulmonary resuscitation (CPR).

Methods  Patients over 18 years of age who were not pregnant and received CPR were divided into two groups: those who achieved ROSC and those who died. There were 25 patients in each group. SCUBE−1 and other routine biochemical parameters were studied in blood samples taken at the time of admission.

Results  There was no significant difference between the age and gender distribution of the patients between the two groups. The SCUBE−1 value of the ROSC group was significantly higher than that of the non-survivor group ( p ˂ 0.05). At a cut-off value of 9 ng/mL, SCUBE−1 had a sensitivity of 100%, a positive predictive value of 65.8%, specificity of 48%, and a negative predictive value of 100% in predicting ROSC.

Conclusions  The SCUBE−1 values were found to be significantly higher in the ROSC group compared with the non-survivor group.

The Added Value of Somatosensory Potential N70 in Neurological Prognosis After Coma by Acute Brain Structural Injury: A Retrospective Study

Background:

Coma after acute brain structural injury (ABI) are associated with high mortality and disability. Somatosensory evoked potentials (SSEP) N20 and N70 are used to predict prognosis.

Purpose:

We assessed the utility of SSEP (N20-N70) as an early indicator of long-term functional prognosis in these patients.

Methods:

We conducted a retrospective cohort study of patients admitted to the intensive care unit (ICU) with a diagnosis of coma after ABI (n=60). An SSEP study including N20 and N70 was performed 24–72 hours after coma onset. Functional recovery was evaluated 6 to 12 months later using the Modified Glasgow Scale (mGS). The study was approved by our local research ethics committee.

Results:

The absence of N20 (41% specificity=100%) or N70 (78%) was a strong indicator of a poor outcome. In contrast, the presence of N70 was an indicator of a good outcome (specificity=64.2% sensitivity=91.3%).

Conclusion:

SSEP N20 and N70 are useful early prognostic markers with high specificity (N20) and sensitivity (N70). N70 has potential additional value for improving the prediction of good functional outcomes in the long term.

Brain magnetic resonance imaging and histopathology findings in a dog with global brain ischaemia following cardiopulmonary arrest

Background

Global brain ischaemia following cardiopulmonary arrest is uncommonly reported in veterinary medicine yet neurologic injury after arrest is a known morbidity.

Case report

An 18‐week‐old male entire Cavalier King Charles Spaniel‐Poodle was referred following 3 days of neurologic abnormalities after cardiopulmonary arrest. After resuscitation, the animal had decerebrate rigidity, a stuporous mentation and intermittent episodes of vocalisation and apnoea. A brain magnetic resonance imaging (MRI) was undertaken 4 days after cardiopulmonary arrest, with standard sequences (T1‐weighted, T2‐weighted and fluid‐attenuated inversion recovery) as well as diffusion‐weighted imaging to better discern ischaemic injury and cytotoxic oedema for prognostic reasons. MRI findings were consistent with global brain ischaemia affecting the hippocampus, cerebellum and substantia nigra, the latter two not previously identified in canine cases of global brain ischaemia. The patient was euthanased on day eight post‐cardiopulmonary arrest due to a lack of neurological improvement and developing sepsis as a complication. Ante‐mortem identification of affected areas of the brain was confirmed on histological examination, with evidence of ischaemic injury seen in the cerebrum, hippocampus, cerebellum, basal nuclei and thalamus.

Conclusion

This report describes ante‐mortem MRI and postmortem findings in a dog with global brain ischaemia following cardiopulmonary arrest. A multimodal approach to neuroprognostication in patients recovering from cardiopulmonary arrest is recommended.

Necrosulfonamide improves post-resuscitation myocardial dysfunction via inhibiting pyroptosis and necroptosis in a rat model of cardiac arrest

The systemic inflammatory response following global myocardial ischemia/reperfusion (I/R) injury is a critical driver of poor outcomes. Both pyroptosis and necroptosis are involved in the systemic inflammatory response and contribute to regional myocardial I/R injury. This study aimed to explore the effect of necrosulfonamide (NSA) on post-resuscitation myocardial dysfunction in a rat model of cardiac arrest. Sprague-Dawley rats were randomly categorized to Sham, CPR and CPR-NSA groups. For rats in the latter two groups, ventricular fibrillation was induced without treatment for 6 min, with cardiopulmonary resuscitation (CPR) being sustained for 8 min. Rats were injected with NSA (10 mg/kg in DMSO) or vehicle at 5 min following return of spontaneous circulation. Myocardial function was measured by echocardiography, survival and neurological deficit score (NDS) were recorded at 24, 48, and 72 h after ROSC. Western blotting was used to assess pyroptosis- and necroptosis-related protein expression. ELISAs were used to measure levels of inflammatory cytokine. Rats in the CPR-NSA group were found to exhibit superior post-resuscitation myocardial function, and better NDS values in the group of CPR-NSA. Rats in the group of CPR-NSA exhibited median survival duration of 68 ± 8 h as compared to 34 ± 21 h in the CPR group. After treatment with NSA, NOD-like receptor 3 (NLRP3), GSDMD-N, phosphorylated-MLKL, and phosphorylated-RIP3 levels in cardiac tissue were reduced with corresponding reductions in inflammatory cytokine levels. Administration of NSA significantly improved myocardial dysfunction succeeding global myocardial I/R injury and enhanced survival outcomes through protective mechanisms potentially related to inhibition of pyroptosis and necroptosis pathways.

Gray-White Matter Ratio at the Level of the Basal Ganglia as a Predictor of Neurologic Outcomes in Cardiac Arrest Survivors: A Literature Review

Loss of gray-white matter discrimination is the primary early imaging finding within of cranial computed tomography in cardiac arrest survivors, and this has been also regarded as a novel predictor for evaluating neurologic outcome. As displayed clearly on computed tomography and based on sensitivity to hypoxia, the gray-white matter ratio at basal ganglia (GWR-BG) region was frequently detected to assess the neurologic outcome by several studies. The specificity of GWR-BG is 72.4 to 100%, while the sensitivity is significantly different. Herein we review the mechanisms mediating cerebral edema following cardiac arrest, demonstrate the determination procedures with respect to GWR-BG, summarize the related researches regarding GWR-BG in predicting neurologic outcomes within cardiac arrest survivors, and discuss factors associated with predicting the accuracy of this methodology. Finally, we describe the effective measurements to increase the sensitivity of GWR-BG in predicting neurologic outcome.