Death after awakening from post-anoxic coma: the "Best CPC" project

Duration of resuscitation, regain of consciousness and histopathological severity of hypoxic-ischemic encephalopathy after cardiac arrest

Purpose

To study the histopathologically quantified severity of hypoxic-ischemic encephalopathy (HIE) in deceased cardiac arrest unbiased by death causes and correlated with demographic parameters.

Methods

We conducted a retrospective, single-centre study including cardiac arrest patients with postmortem brain autopsies. Using the selective eosinophilic neuronal death (SEND), the histopathological severity of HIE was quantified in the cerebral neocortex, hippocampus, basal ganglia, cerebellum, and brainstem, and correlated with demographic parameters.

Results

We included 319 patients with a median time of return from cardiac arrest to spontaneous circulation (tROSC) of 10 min, of whom 62(19.4%) had a regain of consciousness (RoC) before death. The tROSC was significantly correlated with the SEND in all brain regions (p < 0.05, Spearman's rho = 0.14 to 0.29). The SEND in the neocortex, hippocampus, and basal ganglia was significantly correlated with RoC (p < 0.05, Spearman's rho = -0.25 to -0.11). In 9 patients with tROSCs less than 1 min, all had a brainstem SEND less than 30%, and 8(88.9%) had neocortical SEND less than 30%. Among 69 patients with tROSCs greater than 20 min, 47.8-82.6% showed a SEND less than 30% across brain regions.

Conclusions

We found less SEND and RoC was more likely in patients with shorter tROSCs. A tROSC less than 1 min was mostly associated with SEND less than 30% in all brain regions. Prolonged resuscitations with tROSCs greater than 20 min did not exclude a SEND less than 30% in a relevant proportion of patients. Future histopathological studies are warranted to investigate the impact of modifiable clinical parameters on the severity of HIE.

Neuroprotection with hypothermic reperfusion and extracorporeal cardiopulmonary resuscitation - A randomized controlled animal trial of prolonged ventricular fibrillation cardiac arrest in rats

Extracorporeal cardiopulmonary resuscitation (ECPR) facilitates resuscitation with immediate and precise temperature control. This study aimed to determine the optimal reperfusion temperature to minimize neurological damage after ventricular fibrillation cardiac arrest (VFCA). Twenty-four rats were randomized (n = 8 per group) to normothermia (NT = 37°C), mild hypothermia (MH = 33°C) or moderate hypothermia (MOD = 27°C). The rats were subjected to 10 minutes of VFCA, before 15 minutes of ECPR at their respective target temperature. After ECPR weaning, rats in the MOD group were rapidly rewarmed to 33°C, and temperature maintained at 33°C (MH/MOD) or 37°C (NT) for 12 hours before slow rewarming to normothermia (MH/MOD). The primary outcome was 30-day survival with overall performance category (OPC) 1 or 2 (1 = normal, 2 = slight disability, 3 = severe disability, 4 = comatose, 5 = dead). Secondary outcomes included awakening rate (OPC ≤ 3) and neurological deficit score (NDS, from 0 = normal to 100 = brain dead). The survival rate did not differ between reperfusion temperatures (NT = 25%, MH = 63%, MOD = 38%, p = 0.301). MH had the lowest NDS (NT = 4[IQR 3-4], MH = 2[1-2], MOD = 5[3-5], p = 0.044) and highest awakening rate (NT = 25%, MH = 88%, MOD = 75%, p = 0.024). In conclusion, ECPR with 33°C reperfusion did not statistically significantly improve survival after VFCA when compared with 37°C or 27°C reperfusion but was neuroprotective as measured by awakening rate and neurological function.

Heart rate variability for neuro-prognostication after CA: Insight from the Parisian registry

BACKGROUND

Hypoxic ischemic brain injury (HIBI) induced by cardiac arrest (CA) seems to predominate in cortical areas and to a lesser extent in the brainstem. These regions play key roles in modulating the activity of the autonomic nervous system (ANS), that can be assessed through analyses of heart rate variability (HRV). The objective was to evaluate the prognostic value of various HRV parameters to predict neurological outcome after CA.

METHODS

Retrospective monocentric study assessing the prognostic value of HRV markers and their association with HIBI severity. Patients admitted for CA who underwent EEG for persistent coma after CA were included. HRV markers were computed from 5 min signal of the ECG lead of the EEG recording. HRV indices were calculated in the time-, frequency-, and non-linear domains. Frequency-domain analyses differentiated very low frequency (VLF 0.003-0.04 Hz), low frequency (LF 0.04-0.15 Hz), high frequency (HF 0.15-0.4 Hz), and LF/HF ratio. HRV indices were compared to other prognostic markers: pupillary light reflex, EEG, N20 on somatosensory evoked potentials (SSEP) and biomarkers (neuron specific enolase-NSE). Neurological outcome at 3 months was defined as unfavorable in case of best CPC 3-4-5.

RESULTS

Between 2007 and 2021, 199 patients were included. Patients were predominantly male (64%), with a median age of 60 [48.9-71.7] years. 76% were out-of-hospital CA, and 30% had an initial shockable rhythm. Neurological outcome was unfavorable in 73%. Compared to poor outcome, patients with a good outcome had higher VLF (0.21 vs 0.09 ms2/Hz, p < 0.01), LF (0.07 vs 0.04 ms2/Hz, p = 0.003), and higher LF/HF ratio (2.01 vs 1.01, p = 0.008). Several non-linear domain indices were also higher in the good outcome group, such as SD2 (15.1 vs 10.2, p = 0.016) and DFA α1 (1.03 vs 0.78, p = 0.002). These indices also differed depending on the severity of EEG pattern and abolition of pupillary light reflex. These time-frequency and non-linear domains HRV parameters were predictive of poor neurological outcome, with high specificity despite a low sensitivity.

CONCLUSION

In comatose patients after CA, some HRV markers appear to be associated with unfavorable outcome, EEG severity and PLR abolition, although the sensitivity of these HRV markers remains limited.

Performance of the MRI lesion pattern score in predicting neurological outcome after out of hospital cardiac arrest: a retrospective cohort analysis

BACKGROUND

Despite advances in resuscitation practice, patient survival following cardiac arrest remains poor. The utilization of MRI in neurological outcome prognostication post-cardiac arrest is growing and various classifications has been proposed; however a consensus has yet to be established. MRI, though valuable, is resource-intensive, time-consuming, costly, and not universally available. This study aims to validate a MRI lesion pattern score in a cohort of out of hospital cardiac arrest patients at a tertiary referral hospital in Switzerland.

METHODS

This cohort study spanned twelve months from February 2021 to January 2022, encompassing all unconscious patients aged ≥ 18 years who experienced out-of-hospital cardiac arrest of any cause and were admitted to the intensive care unit (ICU) at Inselspital, University Hospital Bern, Switzerland. We included patients who underwent the neuroprognostication process, assessing the performance and validation of a MRI scoring system.

RESULTS

Over the twelve-month period, 137 patients were admitted to the ICU, with 52 entering the neuroprognostication process and 47 undergoing MRI analysis. Among the 35 MRIs indicating severe hypoxic brain injury, 33 patients (94%) experienced an unfavourable outcome (UO), while ten (83%) of the twelve patients with no or minimal MRI lesions had a favourable outcome. This yielded a sensitivity of 0.94 and specificity of 0.83 for predicting UO with the proposed MRI scoring system. The positive and negative likelihood ratios were 5.53 and 0.07, respectively, resulting in an accuracy of 91.49%.

CONCLUSION

We demonstrated the effectiveness of the MLP scoring scheme in predicting neurological outcome in patients following cardiac arrest. However, to ensure a comprehensive neuroprognostication, MRI results need to be combined with other assessments. While neuroimaging is a promising objective tool for neuroprognostication, given the absence of sedation-related confounders-compared to electroencephalogram (EEG) and clinical examination-the current lack of a validated scoring system necessitates further studies. Incorporating standardized MRI techniques and grading systems is crucial for advancing the reliability of neuroimaging for neuroprognostication.

TRIAL REGISTRATION

Registry of all Projects in Switzerland (RAPS) 2020-01761.

The International Cardiac Arrest Research Consortium Electroencephalography Database

OBJECTIVES

To develop the International Cardiac Arrest Research (I-CARE), a harmonized multicenter clinical and electroencephalography database for acute hypoxic-ischemic brain injury research involving patients with cardiac arrest.

DESIGN

Multicenter cohort, partly prospective and partly retrospective.

SETTING

Seven academic or teaching hospitals from the United States and Europe.

PATIENTS

Individuals 16 years old or older who were comatose after return of spontaneous circulation following a cardiac arrest who had continuous electroencephalography monitoring were included.

INTERVENTIONS

Not applicable.

MEASUREMENTS AND MAIN RESULTS

Clinical and electroencephalography data were harmonized and stored in a common Waveform Database-compatible format. Automated spike frequency, background continuity, and artifact detection on electroencephalography were calculated with 10-second resolution and summarized hourly. Neurologic outcome was determined at 3-6 months using the best Cerebral Performance Category (CPC) scale. This database includes clinical data and 56,676 hours (3.9 terabytes) of continuous electroencephalography data for 1,020 patients. Most patients died ( n = 603, 59%), 48 (5%) had severe neurologic disability (CPC 3 or 4), and 369 (36%) had good functional recovery (CPC 1-2). There is significant variability in mean electroencephalography recording duration depending on the neurologic outcome (range, 53-102 hr for CPC 1 and CPC 4, respectively). Epileptiform activity averaging 1 Hz or more in frequency for at least 1 hour was seen in 258 patients (25%) (19% for CPC 1-2 and 29% for CPC 3-5). Burst suppression was observed for at least 1 hour in 207 (56%) and 635 (97%) patients with CPC 1-2 and CPC 3-5, respectively.

CONCLUSIONS

The I-CARE consortium electroencephalography database provides a comprehensive real-world clinical and electroencephalography dataset for neurophysiology research of comatose patients after cardiac arrest. This dataset covers the spectrum of abnormal electroencephalography patterns after cardiac arrest, including epileptiform patterns and those in the ictal-interictal continuum.

Neurophysiology State Dynamics Underlying Acute Neurologic Recovery After Cardiac Arrest

BACKGROUND AND OBJECTIVES

Epileptiform activity and burst suppression are neurophysiology signatures reflective of severe brain injury after cardiac arrest. We aimed to delineate the evolution of coma neurophysiology feature ensembles associated with recovery from coma after cardiac arrest.

METHODS

Adults in acute coma after cardiac arrest were included in a retrospective database involving 7 hospitals. The combination of 3 quantitative EEG features (burst suppression ratio [BSup], spike frequency [SpF], and Shannon entropy [En]) was used to define 5 distinct neurophysiology states: epileptiform high entropy (EHE: SpF ≥4 per minute and En ≥5); epileptiform low entropy (ELE: SpF ≥4 per minute and <5 En); nonepileptiform high entropy (NEHE: SpF <4 per minute and ≥5 En); nonepileptiform low entropy (NELE: SpF <4 per minute and <5 En), and burst suppression (BSup ≥50% and SpF <4 per minute). State transitions were measured at consecutive 6-hour blocks between 6 and 84 hours after return of spontaneous circulation. Good neurologic outcome was defined as best cerebral performance category 1-2 at 3-6 months.

RESULTS

One thousand thirty-eight individuals were included (50,224 hours of EEG), and 373 (36%) had good outcome. Individuals with EHE state had a 29% rate of good outcome, while those with ELE had 11%. Transitions out of an EHE or BSup state to an NEHE state were associated with good outcome (45% and 20%, respectively). No individuals with ELE state lasting >15 hours had good recovery.

DISCUSSION

Transition to high entropy states is associated with an increased likelihood of good outcome despite preceding epileptiform or burst suppression states. High entropy may reflect mechanisms of resilience to hypoxic-ischemic brain injury.

The International Cardiac Arrest Research (I-CARE) Consortium Electroencephalography Database

Objective

To develop a harmonized multicenter clinical and electroencephalography (EEG) database for acute hypoxic-ischemic brain injury research involving patients with cardiac arrest.

Design

Multicenter cohort, partly prospective and partly retrospective.

Setting

Seven academic or teaching hospitals from the U.S. and Europe.

Patients

Individuals aged 16 or older who were comatose after return of spontaneous circulation following a cardiac arrest who had continuous EEG monitoring were included.

Interventions

not applicable.

Measurements and Main Results

Clinical and EEG data were harmonized and stored in a common Waveform Database (WFDB)-compatible format. Automated spike frequency, background continuity, and artifact detection on EEG were calculated with 10 second resolution and summarized hourly. Neurological outcome was determined at 3-6 months using the best Cerebral Performance Category (CPC) scale. This database includes clinical and 56,676 hours (3.9 TB) of continuous EEG data for 1,020 patients. Most patients died (N=603, 59%), 48 (5%) had severe neurological disability (CPC 3 or 4), and 369 (36%) had good functional recovery (CPC 1-2). There is significant variability in mean EEG recording duration depending on the neurological outcome (range 53-102h for CPC 1 and CPC 4, respectively). Epileptiform activity averaging 1 Hz or more in frequency for at least one hour was seen in 258 (25%) patients (19% for CPC 1-2 and 29% for CPC 3-5). Burst suppression was observed for at least one hour in 207 (56%) and 635 (97%) patients with CPC 1-2 and CPC 3-5, respectively.

Conclusions

The International Cardiac Arrest Research (I-CARE) consortium database provides a comprehensive real-world clinical and EEG dataset for neurophysiology research of comatose patients after cardiac arrest. This dataset covers the spectrum of abnormal EEG patterns after cardiac arrest, including epileptiform patterns and those in the ictal-interictal continuum.

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.

Serum proteome profiles in patients treated with targeted temperature management after out-of-hospital cardiac arrest

BACKGROUND

Definition of temporal serum proteome profiles after out-of-hospital cardiac arrest may identify biological processes associated with severe hypoxia-ischaemia and reperfusion. It may further explore intervention effects for new mechanistic insights, identify candidate prognostic protein biomarkers and potential therapeutic targets. This pilot study aimed to investigate serum proteome profiles from unconscious patients admitted to hospital after out-of-hospital cardiac arrest according to temperature treatment and neurological outcome.

METHODS

Serum samples at 24, 48, and 72 h after cardiac arrest at three centres included in the Target Temperature Management after out-of-hospital cardiac arrest trial underwent data-independent acquisition mass spectrometry analysis (DIA-MS) to find changes in serum protein concentrations associated with neurological outcome at 6-month follow-up and targeted temperature management (TTM) at 33 °C as compared to 36 °C. Neurological outcome was defined according to Cerebral Performance Category (CPC) scale as "good" (CPC 1-2, good cerebral performance or moderate disability) or "poor" (CPC 3-5, severe disability, unresponsive wakefulness syndrome, or death).

RESULTS

Of 78 included patients [mean age 66 ± 12 years, 62 (80.0%) male], 37 (47.4%) were randomised to TTM at 36 °C. Six-month outcome was poor in 47 (60.3%) patients. The DIA-MS analysis identified and quantified 403 unique human proteins. Differential protein abundance testing comparing poor to good outcome showed 19 elevated proteins in patients with poor outcome (log₂-fold change (FC) range 0.28-1.17) and 16 reduced proteins (log₂(FC) between - 0.22 and - 0.68), involved in inflammatory/immune responses and apoptotic signalling pathways for poor outcome and proteolysis for good outcome. Analysis according to level of TTM showed a significant protein abundance difference for six proteins [five elevated proteins in TTM 36 °C (log₂(FC) between 0.33 and 0.88), one reduced protein (log₂(FC) - 0.6)] mainly involved in inflammatory/immune responses only at 48 h after cardiac arrest.

CONCLUSIONS

Serum proteome profiling revealed an increase in inflammatory/immune responses and apoptosis in patients with poor outcome. In patients with good outcome, an increase in proteolysis was observed, whereas TTM-level only had a modest effect on the proteome profiles. Further validation of the differentially abundant proteins in response to neurological outcome is necessary to validate novel biomarker candidates that may predict prognosis after cardiac arrest.

EEG in a four-electrode frontotemporal montage reliably predicts outcome after cardiac arrest

AIM

To increase efficiency of continuous EEG monitoring for prognostication of neurological outcome in patients after cardiac arrest, we investigated the reliability of EEG in a four-electrode frontotemporal (4-FT) montage, compared to our standard nine-electrode (9-EL) montage.

METHODS

EEG recorded with Ag/AgCl cup-electrodes at 12 and/or 24h after cardiac arrest of 153 patients was available from a previous study. 220 EEG epochs of 5 minutes were reexamined in a 4-FT montage according to the ACNS criteria. Background classification was compared to the available 9-EL classification using Cohens kappa. Reliability for prognostication was assessed in 151 EEG epochs at 24h after CA using sensitivity and specificity for prediction of poor (cerebral performance categories (CPC) 3-5) and good (CPC 1-2) neurological outcome.

RESULTS

Agreement for EEG background classification between the two montages was substantial with a kappa of 0.85 (95%-CI 0.81-0.90). Specificity for prediction of poor outcome was 100% (95%-CI 95-100) for both montages, sensitivity was 31% (95%-CI 21-43) for the 4-FT montage and 35% (95%-CI 24-47) for the 9-EL montage. Good outcome was predicted with 65% specificity (95%-CI 53-76) and 81% sensitivity (95%-CI 71-89) for the 4-FT montage, similar to the 9-EL montage.

CONCLUSION

In this cohort, EEG background patterns determined in a four-electrode frontotemporal montage predict both poor and good outcome after CA with similar reliability. Our results may contribute to decreasing the workload of EEG monitoring in patients after CA without compromising reliability of outcome prediction. However, validation in a larger cohort is necessary, as is a multimodal approach.

Time to Awakening and Self-Fulfilling Prophecies After Cardiac Arrest

OBJECTIVES

Withdrawal of life-sustaining therapies for perceived poor neurologic prognosis (WLST-N) is common after resuscitation from cardiac arrest and may bias outcome estimates from models trained using observational data. We compared several approaches to outcome prediction with the goal of identifying strategies to quantify and reduce this bias.

DESIGN

Retrospective observational cohort study.

SETTING

Two academic medical centers ("UPMC" and "University of Alabama Birmingham" [UAB]).

PATIENTS

Comatose adults resuscitated from cardiac arrest.

INTERVENTION

None.

MEASUREMENTS AND MAIN RESULTS

As potential predictors, we considered clinical, laboratory, imaging, and quantitative electroencephalography data available early after hospital arrival. We followed patients until death, discharge, or awakening from coma. We used penalized Cox regression with a least absolute shrinkage and selection operator penalty and five-fold cross-validation to predict time to awakening in UPMC patients and then externally validated the model in UAB patients. This model censored patients after WLST-N, considering subsequent potential for awakening to be unknown. Next, we developed a penalized logistic model predicting awakening, which treated failure to awaken after WLST-N as a true observed outcome, and a separate logistic model predicting WLST-N. We scaled and centered individual patients' Cox and logistic predictions for awakening to allow direct comparison and then explored the difference in predictions across probabilities of WLST-N. Overall, 1,254 patients were included, and 29% awakened. Cox models performed well (mean area under the curve was 0.93 in the UPMC test sets and 0.83 in external validation). Logistic predictions of awakening were systematically more pessimistic than Cox-based predictions for patients at higher risk of WLST-N, suggesting potential for self-fulfilling prophecies to arise when failure to awaken after WLST-N is considered as the ground truth outcome.

CONCLUSIONS

Compared with traditional binary outcome prediction, censoring outcomes after WLST-N may reduce potential for bias and self-fulfilling prophecies.

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

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

Cerebrospinal fluid features in comatose survivors of cardiac arrest: A pilot study

INTRODUCTION

Lumbar puncture is among the investigations used to identify various neurological conditions, including some that can cause cardiac arrest (CA). However, CA per se may alter cerebrospinal fluid (CSF) characteristics. Few studies have investigated CSF findings after CA. In this descriptive work, we assessed the frequency and risk factors of abnormal CSF findings after CA and the contribution of CSF analysis to the etiological diagnosis.

MATERIALS AND METHODS

We retrospectively studied data from prospectively established databases of consecutive patients who were admitted to two French ICUs in 2007-2016 with sustained return of spontaneous circulation (ROSC) after CA and who underwent lumbar puncture as an etiological investigation.

RESULTS

Of 1984 patients with sustained ROSC, 55 (2.7%) underwent lumbar puncture and were included. Lumbar puncture identified a neurological cause of CA in 2/55 (3.6%) patients. Nonspecific CSF abnormalities were noted in 37/53 (69.8%) patients. By multivariate analysis, postresuscitation shock was positively associated with CSF abnormalities (OR, 6.92; 95% confidence interval [95%CI], 1.62-37.26; P = 0.013). A no-flow time above 6 minutes (OR, 0.19; 95%CI, 0.03-1.11; P = 0.076) and a respiratory cause of CA (OR, 2.91; 95%CI, 0.53-23.15; P = 0.24) were not statistically associated with CSF abnormalities. Nonspecific CSF abnormalities were not significantly associated with poor outcomes (Cerebral Performance Category ≥3; P = 0.06).

CONCLUSIONS

Lumbar puncture, although infrequently performed, may contribute to the etiological diagnosis of CA, albeit rarely. Nonspecific CSF abnormalities seem common after CA, notably with postresuscitation shock, and may be related to blood-brain barrier disruption. These findings may help to interpret CSF findings after CA. Further studies are warranted to assess our results.

Predicting Neurological Outcome From Electroencephalogram Dynamics in Comatose Patients After Cardiac Arrest With Deep Learning

OBJECTIVE

Most cardiac arrest patients who are successfully resuscitated are initially comatose due to hypoxic-ischemic brain injury. Quantitative electroencephalography (EEG) provides valuable prognostic information. However, prior approaches largely rely on snapshots of the EEG, without taking advantage of temporal information.

METHODS

We present a recurrent deep neural network with the goal of capturing temporal dynamics from longitudinal EEG data to predict long-term neurological outcomes. We utilized a large international dataset of continuous EEG recordings from 1,038 cardiac arrest patients from seven hospitals in Europe and the US. Poor outcome was defined as a Cerebral Performance Category (CPC) score of 3-5, and good outcome as CPC score 0-2 at 3 to 6-months after cardiac arrest. Model performance is evaluated using 5-fold cross validation.

RESULTS

The proposed approach provides predictions which improve over time, beginning from an area under the receiver operating characteristic curve (AUC-ROC) of 0.78 (95% CI: 0.72-0.81) at 12 hours, and reaching 0.88 (95% CI: 0.85-0.91) by 66 h after cardiac arrest. At 66 h, (sensitivity, specificity) points of interest on the ROC curve for predicting poor outcomes were (32,99)%, (55,95)%, and (62,90)%, (99,23)%, (95,47)%, and (90,62)%; whereas for predicting good outcome, the corresponding operating points were (17,99)%, (47,95)%, (62,90)%, (99,19)%, (95,48)%, (70,90)%. Moreover, the model provides predicted probabilities that closely match the observed frequencies of good and poor outcomes (calibration error 0.04).

CONCLUSIONS AND SIGNIFICANCE

These findings suggest that accounting for EEG trend information can substantially improve prediction of neurologic outcomes for patients with coma following cardiac arrest.

SSEP N20 and P25 amplitudes predict poor and good neurologic outcomes after cardiac arrest

Background

To assess in comatose patients after cardiac arrest (CA) if amplitudes of two somatosensory evoked potentials (SSEP) responses, namely, N20-baseline (N20-b) and N20–P25, are predictive of neurological outcome.

Methods

Monocentric prospective study in a tertiary cardiac center between Nov 2019 and July-2021. All patients comatose at 72 h after CA with at least one SSEP recorded were included. The N20-b and N20–P25 amplitudes were automatically measured in microvolts (µV), along with other recommended prognostic markers (status myoclonus, neuron-specific enolase levels at 2 and 3 days, and EEG pattern). We assessed the predictive value of SSEP for neurologic outcome using the best Cerebral Performance Categories (CPC1 or 2 as good outcome) at 3 months (main endpoint) and 6 months (secondary endpoint). Specificity and sensitivity of different thresholds of SSEP amplitudes, alone or in combination with other prognostic markers, were calculated.

Results

Among 82 patients, a poor outcome (CPC 3–5) was observed in 78% of patients at 3 months. The median time to SSEP recording was 3(2–4) days after CA, with a pattern “bilaterally absent” in 19 patients, “unilaterally present” in 4, and “bilaterally present” in 59 patients. The median N20-b amplitudes were different between patients with poor and good outcomes, i.e., 0.93 [0–2.05]µV vs. 1.56 [1.24–2.75]µV, respectively (p < 0.0001), as the median N20–P25 amplitudes (0.57 [0–1.43]µV in poor outcome vs. 2.64 [1.39–3.80]µV in good outcome patients p < 0.0001). An N20-b > 2 µV predicted good outcome with a specificity of 73% and a moderate sensitivity of 39%, although an N20–P25 > 3.2 µV was 93% specific and only 30% sensitive. A low voltage N20-b < 0.88 µV and N20–P25 < 1 µV predicted poor outcome with a high specificity (sp = 94% and 93%, respectively) and a moderate sensitivity (se = 50% and 66%). Association of “bilaterally absent or low voltage SSEP” patterns increased the sensitivity significantly as compared to “bilaterally absent” SSEP alone (se = 58 vs. 30%, p = 0.002) for prediction of poor outcome.

Conclusion

In comatose patient after CA, both N20-b and N20–P25 amplitudes could predict both good and poor outcomes with high specificity but low to moderate sensitivity. Our results suggest that caution is needed regarding SSEP amplitudes in clinical routine, and that these indicators should be used in a multimodal approach for prognostication after cardiac arrest.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13613-022-00999-6.

Prediction of good neurological outcome in comatose survivors of cardiac arrest: a systematic review

PURPOSE

To assess the ability of clinical examination, blood biomarkers, electrophysiology or neuroimaging assessed within 7 days from return of spontaneous circulation (ROSC) to predict good neurological outcome, defined as no, mild, or moderate disability (CPC 1-2 or mRS 0-3) at discharge from intensive care unit or later, in comatose adult survivors from cardiac arrest (CA).

METHODS

PubMed, EMBASE, Web of Science and the Cochrane Database of Systematic Reviews were searched. Sensitivity and specificity for good outcome were calculated for each predictor. The risk of bias was assessed using the QUIPS tool.

RESULTS

A total of 37 studies were included. Due to heterogeneities in recording times, predictor thresholds, and definition of some predictors, meta-analysis was not performed. A withdrawal or localisation motor response to pain immediately or at 72-96 h after ROSC, normal blood values of neuron-specific enolase (NSE) at 24 h-72 h after ROSC, a short-latency somatosensory evoked potentials (SSEPs) N20 wave amplitude > 4 µV or a continuous background without discharges on electroencephalogram (EEG) within 72 h from ROSC, and absent diffusion restriction in the cortex or deep grey matter on MRI on days 2-7 after ROSC predicted good neurological outcome with more than 80% specificity and a sensitivity above 40% in most studies. Most studies had moderate or high risk of bias.

CONCLUSIONS

In comatose cardiac arrest survivors, clinical, biomarker, electrophysiology, and imaging studies identified patients destined to a good neurological outcome with high specificity within the first week after cardiac arrest (CA).

L-arginine, asymmetric and symmetric dimethylarginine for early outcome prediction in unselected cardiac arrest victims: a prospective cohort study

Early prediction of the mortality, neurological outcome is clinically essential after successful cardiopulmonary resuscitation. To find a prognostic marker among unselected cardiac arrest survivors, we aimed to evaluate the alterations of the L-arginine pathway molecules in the early post-resuscitation care. We prospectively enrolled adult patients after successfully resuscitated in- or out-of-hospital cardiac arrest. Blood samples were drawn within 6, 24, and 72 post-cardiac arrest hours to measure asymmetric and symmetric dimethylarginine (ADMA and SDMA) and L-arginine plasma concentrations. We recorded Sequential Organ Failure Assessment, Simplified Acute Physiology Score, and Cerebral Performance Category scores. Endpoints were 72 h, intensive care unit, and 30-day mortality. Among 54 enrolled patients [median age: 67 (61-78) years, 48% male], the initial ADMA levels were significantly elevated in those who died within 72 h [0.88 (0.64-0.97) µmol/L vs. 0.55 (0.45-0.69) µmol/L, p = 0.001]. Based on receiver operator characteristic analysis (AUC = 0.723; p = 0.005) of initial ADMA for poor neurological outcome, the best cutoff was determined as > 0.65 µmol/L (sensitivity = 66.7%; specificity = 81.5%), while for 72 h mortality (AUC = 0.789; p = 0.001) as > 0.81 µmol/L (sensitivity = 71.0%; specificity = 87.5%). Based on multivariate analysis, initial ADMA (OR = 1.8 per 0.1 µmol/L increment; p = 0.002) was an independent predictor for 72 h mortality. Increased initial ADMA predicts 72 h mortality and poor neurological outcome among unselected cardiac arrest victims.

The accuracy of various neuro-prognostication algorithms and the added value of neurofilament light chain dosage for patients resuscitated from shockable cardiac arrest: An ancillary analysis of the ISOCRATE study

PURPOSE

In current guidelines, neurological prognostication after cardiopulmonary resuscitation is based on a multimodal approach bundled in algorithms. Biomarkers are of particular interest because they are unaffected by interpretation bias. We assessed the predictive value of serum neurofilament light chains (NF-L) in patients with a shockable rhythm who received cardiopulmonary resuscitation, and evaluated the predictive value of a modified algorithm where NF-L dosage is included.

METHODS

All patients who were included participated in the randomized ISOCRATE trial. NF-L values 48 h after ROSC were compared for patients with a good (Cerebral Performance Category (CPC) 1 or 2) and a poor prognosis (CPC 3 to 5 or death). The benefit of adding NF-L dosage to the current guideline algorithm was then assessed for NF-L thresholds of 500 and 1,200 pg/ml as previously described.

RESULTS

NF-L was assayed for 49 patients. In patients with good versus those with poor outcomes, median NF-L values at 48 h were 72 ± 78 and 7,755 ± 9,501 pg/ml respectively (P < 0.0001; AUC [95 %CI] = 0.87 [0.74;0.99]). The sensitivity of the modified ESICM/ERC 2021 algorithm after adding NF-L with thresholds of 500 and 1,200 pg/ml was 0.74 (CI 95% 0.51-0.88) and 0.68 (CI 95% 0.46-0.86), respectively, versus 0.53 (CI 95% 0.32-0.73) for the unmodified algorithm. In three instances the specificity was 1.

CONCLUSION

High NF-L plasma levels 48 h after cardiac arrest was significantly associated with a poor outcome. Adjunction to the current guideline algorithm of an NF-L assay with a 500 pg/ml threshold 48 h after cardiac arrest provided the best sensitivity compared to the algorithm alone, while specificity remained excellent.

Brain injury after cardiac arrest: pathophysiology, treatment, and prognosis

Post-cardiac arrest brain injury (PCABI) is caused by initial ischaemia and subsequent reperfusion of the brain following resuscitation. In those who are admitted to intensive care unit after cardiac arrest, PCABI manifests as coma, and is the main cause of mortality and long-term disability. This review describes the mechanisms of PCABI, its treatment options, its outcomes, and the suggested strategies for outcome prediction.

Predicting early recovery of consciousness after cardiac arrest supported by quantitative electroencephalography

OBJECTIVE

To determine the ability of quantitative electroencephalography (QEEG) to improve the accuracy of predicting recovery of consciousness by post-cardiac arrest day 10.

METHODS

Unconscious survivors of cardiac arrest undergoing daily clinical and EEG assessments through post-cardiac arrest day 10 were studied in a prospective observational cohort study. Power spectral density, local coherence, and permutation entropy were calculated from daily EEG clips following a painful stimulus. Recovery of consciousness was defined as following at least simple commands by day 10. We determined the impact of EEG metrics to predict recovery when analyzed with established predictors of recovery using partial least squares regression models. Explained variance analysis identified which features contributed most to the predictive model.

RESULTS

367 EEG epochs from 98 subjects were analyzed in conjunction with clinical measures. Highest prediction accuracy was achieved when adding QEEG features from post-arrest days 4-6 to established predictors (area under the receiver operating curve improved from 0.81 ± 0.04 to 0.86 ± 0.05). Prediction accuracy decreased from 0.84 ± 0.04 to 0.79 ± 0.04 when adding QEEG features from post-arrest days 1-3. Patients with recovery of command-following by day 10 showed higher coherence across the frequency spectrum and higher centro-occipital delta-frequency spectral power by days 4-6, and globally-higher theta range permutation entropy by days 7-10.

CONCLUSIONS

Adding quantitative EEG metrics to established predictors of recovery allows modest improvement of prediction accuracy for recovery of consciousness, when obtained within a week of cardiac arrest. Further research is needed to determine the best strategy for integration of QEEG data into prognostic models in this patient population.

Clinical Characteristics and In-Hospital Mortality of Cardiac Arrest Survivors in Brazil: A Large Retrospective Multicenter Cohort Study

Supplemental Digital Content is available in the text.

Data on cardiac arrest survivors from developing countries are scarce. This study investigated clinical characteristics associated with in-hospital mortality in resuscitated patients following cardiac arrest in Brazil.

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

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

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

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

Standardized visual EEG features predict outcome in patients with acute consciousness impairment of various etiologies

BACKGROUND

Early prognostication in patients with acute consciousness impairment is a challenging but essential task. Current prognostic guidelines vary with the underlying etiology. In particular, electroencephalography (EEG) is the most important paraclinical examination tool in patients with hypoxic ischemic encephalopathy (HIE), whereas it is not routinely used for outcome prediction in patients with traumatic brain injury (TBI).

METHOD

Data from 364 critically ill patients with acute consciousness impairment (GCS ≤ 11 or FOUR ≤ 12) of various etiologies and without recent signs of seizures from a prospective randomized trial were retrospectively analyzed. Random forest classifiers were trained using 8 visual EEG features-first alone, then in combination with clinical features-to predict survival at 6 months or favorable functional outcome (defined as cerebral performance category 1-2).

RESULTS

The area under the ROC curve was 0.812 for predicting survival and 0.790 for predicting favorable outcome using EEG features. Adding clinical features did not improve the overall performance of the classifier (for survival: AUC = 0.806, p = 0.926; for favorable outcome: AUC = 0.777, p = 0.844). Survival could be predicted in all etiology groups: the AUC was 0.958 for patients with HIE, 0.955 for patients with TBI and other neurosurgical diagnoses, 0.697 for patients with metabolic, inflammatory or infectious causes for consciousness impairment and 0.695 for patients with stroke. Training the classifier separately on subgroups of patients with a given etiology (and thus using less training data) leads to poorer classification performance.

CONCLUSIONS

While prognostication was best for patients with HIE and TBI, our study demonstrates that similar EEG criteria can be used in patients with various causes of consciousness impairment, and that the size of the training set is more important than homogeneity of ACI etiology.

Frequency, risk factors, and outcomes of non-occlusive mesenteric ischaemia after cardiac arrest

PURPOSE

Mesenteric ischaemia after successfully resuscitated cardiac arrest (CA) has been insufficiently studied. We aimed to assess the frequency, risk factors, and outcomes of non-occlusive mesenteric ischaemia (NOMI) after CA.

METHODS

We retrospectively included patients admitted to a CA centre with sustained return of spontaneous circulation between 2007 and 2017. NOMI was suspected based on clinical symptoms and classified as possible if no tests were feasible or the only test was a negative abdominal computed tomography (CT) scan and as confirmed if diagnosed by endoscopy, CT, or surgery.

RESULTS

Of 1343 patients, 82 (6%) had suspected NOMI, including 33 (2.5%) with confirmed NOMI. Investigations for suspected NOMI were done in 47/82 (57%) patients (CT, n = 30; lower digestive endoscopy, n = 14; and upper digestive endoscopy, n = 12); 11 patients underwent surgery. By multivariate analysis, factors associated with suspected NOMI were female sex (OR, 1.8; 95%CI, 1.1-2.9, p = 0.02), cardiovascular comorbidities (OR, 1.6; 95%CI, 1.0-2.7; p = 0.047), admission lactate >5 mmol/L (OR, 2.0; 95%CI, 1.2-3.4; p = 0.01), low flow >17 min (OR, 2.2; 95%CI, 1.3-3.8; p = 0.003), and inotropic score >7 μg/kg/min (OR, 1.8; 95%CI, 1.1-3.2; p = 0.03). ICU mortality was 96% (79/82), with 61% of patients dying from multi-organ failure (MOF) and 35% from post-anoxic brain injury. Of the eight patients who regained consciousness, 5 finally died from MOF, leaving 3 patients discharged alive from the ICU with a good neurologic outcome.

CONCLUSIONS

NOMI may affect 2.5-6% of patients after CA. Mortality was extremely high in patients, and very few survived with a good neurological outcome.

EEG reactivity testing for prediction of good outcome in patients after cardiac arrest

Objective

To determine the additional value of EEG reactivity (EEG-R) testing to EEG background pattern for prediction of good outcome in adult patients after cardiac arrest (CA).

Methods

In this post hoc analysis of a prospective cohort study, EEG-R was tested twice a day, using a strict protocol. Good outcome was defined as a Cerebral Performance Category score of 1–2 within 6 months. The additional value of EEG-R per EEG background pattern was evaluated using the diagnostic odds ratio (DOR). Prognostic value (sensitivity and specificity) of EEG-R was investigated in relation to time after CA, sedative medication, different stimuli, and repeated testing.

Results

Between 12 and 24 hours after CA, data of 108 patients were available. Patients with a continuous (n = 64) or discontinuous (n = 19) normal voltage background pattern with reactivity were 3 and 8 times more likely to have a good outcome than without reactivity (continuous: DOR, 3.4; 95% confidence interval [CI], 0.97–12.0; p = 0.06; discontinuous: DOR, 8.0; 95% CI, 1.0–63.97; p = 0.0499). EEG-R was not observed in other background patterns within 24 hours after CA. In 119 patients with a normal voltage EEG background pattern, continuous or discontinuous, any time after CA, prognostic value was highest in sedated patients (sensitivity 81.3%, specificity 59.5%), irrespective of time after CA. EEG-R induced by handclapping and sternal rubbing, especially when combined, had highest prognostic value. Repeated EEG-R testing increased prognostic value.

Conclusion

EEG-R has additional value for prediction of good outcome in patients with discontinuous normal voltage EEG background pattern and possibly with continuous normal voltage. The best stimuli were clapping and sternal rubbing.

Temporal trends in the use of targeted temperature management after cardiac arrest and association with outcome: insights from the Paris Sudden Death Expertise Centre

Purpose

Recent doubts regarding the efficacy may have resulted in a loss of interest for targeted temperature management (TTM) in comatose cardiac arrest (CA) patients, with uncertain consequences on outcome. We aimed to identify a change in TTM use and to assess the relationship between this change and neurological outcome.

Methods

We used Utstein data prospectively collected in the Sudden Death Expertise Center (SDEC) registry (capturing CA data from all secondary and tertiary hospitals located in the Great Paris area, France) between May 2011 and December 2017. All cases of non-traumatic OHCA patients with stable return of spontaneous circulation (ROSC) were included. After adjustment for potential confounders, we assessed the relationship between changes over time in the use of TTM and neurological recovery at discharge using the Cerebral Performance Categories (CPC) scale.

Results

Between May 2011 and December 2017, 3925 patients were retained in the analysis, of whom 1847 (47%) received TTM. The rate of good neurological outcome at discharge (CPC 1 or 2) was higher in TTM patients as compared with no TTM (33% vs 15%, P < 0.001). Gender, age, and location of CA did not change over the years. Bystander CPR increased from 55% in 2011 to 73% in 2017 (P < 0.001) and patients with a no-flow time longer than 3 min decreased from 53 to 38% (P < 0.001). The use of TTM decreased from 55% in 2011 to 37% in 2017 (P < 0.001). Meanwhile, the rate of patients with good neurological recovery remained stable (19 to 23%, P = 0.76). After adjustment, year of CA occurrence was not associated with outcome.

Conclusions

We report a progressive decrease in the use of TTM in post-cardiac arrest patients over the recent years. During this period, neurological outcome remained stable, despite an increase in bystander-initiated resuscitation and a decrease in “no flow” duration.