Performance of a guideline-recommended algorithm for prognostication of poor neurological outcome 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.

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.

Normal value of neuron-specific enolase for predicting good neurological outcomes in comatose out-of-hospital cardiac arrest survivors

Research on prognostic factors for good outcomes in out-of-hospital cardiac arrest (OHCA) survivors is lacking. We assessed whether normal levels of normal neuron-specific enolase (NSE) value would be useful for predicting good neurological outcomes in comatose OHCA survivors treated with targeted temperature management (TTM). This registry-based observational study with consecutive adult (≥18 years) OHCA survivors with TTM who underwent NSE measurement 48 hours after cardiac arrest was conducted from October 2015 to November 2022. Normal NSE values defined as the upper limit of the normal range by the manufacturer (NSE <16.3 μg/L) and guideline-suggested (NSE < 60 μg/L) were examined for good neurologic outcomes, defined as Cerebral Performance Categories ≤2, at 6 months post-survival. Among 226 OHCA survivors with TTM, 200 patients who underwent NSE measurement were enrolled. The manufacturer-suggested normal NSE values (<16.3 μg/L) had a specificity of 99.17% for good neurological outcomes with a very low sensitivity of 12.66%. NSE <60 μg/L predicted good outcomes with a sensitivity of 87.34% and specificity of 72.73%. However, excluding 14 poor-outcome patients who died from multi-organ dysfunction excluding hypoxic brain injury, the sensitivity and specificity of normal NSE values were 12.66% and 99.07% of NSE < 16.3 μg/L, and 87.34% and 82.24% of NSE < 60 μg/L. The manufacturer-suggested normal NSE had high specificity with low sensitivity, but the guideline-suggested normal NSE value had a comparatively low specificity for good outcome prediction in OHCA survivors. Our data demonstrate normal NSE levels can be useful as a tool for multimodal appropriation of good outcome prediction.

Good outcome prediction after out-of-hospital cardiac arrest: A prospective multicenter observational study in Korea (the KORHN-PRO registry)

AIM

To assess the ability of clinical examination, biomarkers, electrophysiology and brain imaging, individually or in combination to predict good neurological outcomes at 6 months after CA.

METHODS

This was a retrospective analysis of the Korean Hypothermia Network Prospective Registry 1.0, which included adult out-of-hospital cardiac arrest (OHCA) patients (≥18 years). Good outcome predictors were defined as both pupillary light reflex (PLR) and corneal reflex (CR) at admission, Glasgow Coma Scale Motor score (GCS-M) >3 at admission, neuron-specific enolase (NSE) <17 µg/L at 24-72 h, a median nerve somatosensory evoked potential (SSEP) N20/P25 amplitude >4 µV, continuous background without discharges on electroencephalogram (EEG), and absence of anoxic injury on brain CT and diffusion-weighted imaging (DWI).

RESULTS

A total of 1327 subjects were included in the final analysis, and their median age was 59 years; among them, 412 subjects had a good neurological outcome at 6 months. GCS-M >3 at admission had the highest specificity of 96.7% (95% CI 95.3-97.8), and normal brain DWI had the highest sensitivity of 96.3% (95% CI 92.9-98.4). When the two predictors were combined, the sensitivities tended to decrease (ranging from 2.7-81.1%), and the specificities tended to increase, ranging from81.3-100%. Through the explorative variation of the 2021 European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM) prognostication strategy algorithms, good outcomes were predicted, with a specificity of 83.2% and a sensitivity of 83.5% in patients by the algorithm.

CONCLUSIONS

Clinical examination, biomarker, electrophysiology, and brain imaging predicted good outcomes at 6 months after CA. When the two predictors were combined, the specificity further improved. With the 2021 ERC/ESICM guidelines, the number of indeterminate patients and the uncertainty of prognostication can be reduced by using a good outcome prediction algorithm.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Neuroimmune activation is associated with neurological outcome in anoxic and traumatic coma

The pathophysiological underpinnings of critically disrupted brain connectomes resulting in coma are poorly understood. Inflammation is potentially an important but still undervalued factor. Here, we present a first-in-human prospective study using the 18-kDa translocator protein (TSPO) radioligand 18F-DPA714 for PET imaging to allow in vivo neuroimmune activation quantification in patients with coma (n = 17) following either anoxia or traumatic brain injuries in comparison with age- and sex-matched controls. Our findings yielded novel evidence of an early inflammatory component predominantly located within key cortical and subcortical brain structures that are putatively implicated in consciousness emergence and maintenance after severe brain injury (i.e. mesocircuit and frontoparietal networks). We observed that traumatic and anoxic patients with coma have distinct neuroimmune activation profiles, both in terms of intensity and spatial distribution. Finally, we demonstrated that both the total amount and specific distribution of PET-measurable neuroinflammation within the brain mesocircuit were associated with the patient's recovery potential. We suggest that our results can be developed for use both as a new neuroprognostication tool and as a promising biometric to guide future clinical trials targeting glial activity very early after severe brain injury.

2021 European Resuscitation Council/European Society of Intensive Care Medicine Algorithm for Prognostication of Poor Neurological Outcome After Cardiac Arrest-Can Entry Criteria Be Broadened?

OBJECTIVES

To explore broadened entry criteria of the 2021 European Resuscitation Council/European Society of Intensive Care Medicine (ERC/ESICM) algorithm for neuroprognostication including patients with ongoing sedation and Glasgow Coma Scale-Motor score (GCS-M) scores 4-5.

DESIGN

Retrospective multicenter observational study.

SETTING

Four ICUs, Skane, Sweden.

PATIENTS

Postcardiac arrest patients managed at targeted temperature 36°C, 2014-2018. Neurologic outcome was assessed after 2-6 months according to the Cerebral Performance Category scale.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

In 794 included patients, median age was 69.5 years (interquartile range, 60.6-77.0 yr), 241 (30.4%) were female, 550 (69.3%) had an out-of-hospital cardiac arrest, and 314 (41.3%) had a shockable rhythm. Four hundred ninety-five patients were dead at follow-up, 330 of 495 died after a decision on withdrawal of life-sustaining therapies. At 72 hours after cardiac arrest 218 patients remained unconscious. The entry criteria of the original algorithm (GCS-M 1-3) was fulfilled by 163 patients and 115 patients with poor outcome were identified, with false positive rate (FPR) of 0% (95% CI, 0-79.4%) and sensitivity of 71.0% (95% CI, 63.6-77.4%). Inclusion of patients with ongoing sedation identified another 13 patients with poor outcome, generating FPR of 0% (95% CI, 0-65.8%) and sensitivity of 69.6% (95% CI, 62.6-75.8%). Inclusion of all unconscious patients (GCS-M 1-5), regardless of sedation, identified one additional patient, generating FPR of 0% (95% CI, 0-22.8) and sensitivity of 62.9% (95% CI, 56.1-69.2). The few patients with true negative prediction (patients with good outcome not fulfilling guideline criteria of a poor outcome) generated wide 95% CI for FPR.

CONCLUSION

The 2021 ERC/ESICM algorithm for neuroprognostication predicted poor neurologic outcome with a FPR of 0%. Broadening inclusion criteria to include all unconscious patients regardless of ongoing sedation identified an additional small number of patients with poor outcome but did not affect the FPR. Results are limited by high rate of withdrawal of life-sustaining therapies and few patients with true negative prediction.

The capacity of neurological pupil index to predict the absence of somatosensory evoked potentials after cardiac arrest - An observational study

Background

In neurologic prognostication of comatose survivors from cardiac arrest, two independent predictors of poor outcome are the loss of the Pupillary light reflex (PLR) and the loss of the N20 response from Somatosensory Evoked potentials (SSEP). The PLR can be quantitatively assessed by pupillometry. Both tests depend on the midbrain, in which a dysfunction reflects a severe hypoxic injury. We reasoned that a certain level of defective PLR would be predictive of a bilaterally absent SSEP N20 response.

Method

Neurological Pupil index (NPi) from the pupillometry and the SSEP N20 response were registered >48 h after cardiac arrest in comatose survivors. Clinical data were retrospectively analyzed. A receiver operating characteristic curve was used to evaluate the capacity of NPi to predict bilaterally absent SSEP N20 response. An NPi threshold value resulting in <5% false positive rate (FPR) for bilaterally absent N20 response was identified.

Results

From February 2020 to August 2022, we included 54 patients out of which 49 had conclusive pupillometry and SSEP examinations. The NPi threshold value with FPR < 5% was 3.4, yielding 36% sensitivity (95% CI 18-55) and significantly discriminated between respective groups with preserved and bilaterally absent N20 response to SSEP (p-value <0.01).

Conclusion

In this limited cohort, NPi < 3.4 in patients remaining comatose >48 hours after cardiac arrest predicted bilateral loss of the SSEP N20 response with a FPR < 5%. If validated in a larger cohort, an NPi threshold may be clinically applied in settings where SSEP is unavailable.

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.

2023 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations: Summary From the Basic Life Support; Advanced Life Support; Pediatric Life Support; Neonatal Life Support; Education, Implementation, and Teams; and First Aid Task Forces

The International Liaison Committee on Resuscitation engages in a continuous review of new, peer-reviewed, published cardiopulmonary resuscitation and first aid science. Draft Consensus on Science With Treatment Recommendations are posted online throughout the year, and this annual summary provides more concise versions of the final Consensus on Science With Treatment Recommendations from all task forces for the year. Topics addressed by systematic reviews this year include resuscitation of cardiac arrest from drowning, extracorporeal cardiopulmonary resuscitation for adults and children, calcium during cardiac arrest, double sequential defibrillation, neuroprognostication after cardiac arrest for adults and children, maintaining normal temperature after preterm birth, heart rate monitoring methods for diagnostics in neonates, detection of exhaled carbon dioxide in neonates, family presence during resuscitation of adults, and a stepwise approach to resuscitation skills training. Members from 6 International Liaison Committee on Resuscitation task forces have assessed, discussed, and debated the quality of the evidence, using Grading of Recommendations Assessment, Development, and Evaluation criteria, and their statements include consensus treatment recommendations. Insights into the deliberations of the task forces are provided in the Justification and Evidence-to-Decision Framework Highlights sections. In addition, the task forces list priority knowledge gaps for further research. Additional topics are addressed with scoping reviews and evidence updates.

Outcome prediction in comatose cardiac arrest patients with initial shockable and non-shockable rhythms

BACKGROUND

Prognosis after out-of-hospital cardiac arrest (OHCA) is presumed poorer in patients with non-shockable than shockable rhythms, frequently leading to treatment withdrawal. Multimodal outcome prediction is recommended 72 h post-arrest in still comatose patients, not considering initial rhythms. We investigated accuracy of outcome predictors in all comatose OHCA survivors, with a particular focus on shockable vs. non-shockable rhythms.

METHODS

In this observational NORCAST sub-study, patients still comatose 72 h post-arrest were stratified by shockable vs. non-shockable rhythms for outcome prediction analyzes. Good outcome was defined as cerebral performance category 1-2 within 6 months. False positive rate (FPR) was used for poor and sensitivity for good outcome prediction accuracy.

RESULTS

Overall, 72/128 (56%) patients with shockable and 12/50 (24%) with non-shockable rhythms had good outcome (p < .001). For poor outcome prediction, absent pupillary light reflexes (PLR) and corneal reflexes (clinical predictors) 72 h after sedation withdrawal, PLR 96 h post-arrest, and somatosensory evoked potentials (SSEP), all had FPR <0.1% in both groups. Unreactive EEG and neuron-specific enolase (NSE) >60 μg/L 24-72 h post-arrest had better precision in shockable patients. For good outcome, the clinical predictors, SSEP and CT, had 86%-100% sensitivity in both groups. For NSE, sensitivity varied from 22% to 69% 24-72 h post-arrest. The outcome predictors indicated severe brain injury proportionally more often in patients with non-shockable than with shockable rhythms. For all patients, clinical predictors, CT, and SSEP, predicted poor and good outcome with high accuracy.

CONCLUSION

Outcome prediction accuracy was comparable for shockable and non-shockable rhythms. PLR and corneal reflexes had best precision 72 h after sedation withdrawal and 96 h post-arrest.

2023 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations: Summary From the Basic Life Support; Advanced Life Support; Pediatric Life Support; Neonatal Life Support; Education, Implementation, and Teams; and First Aid Task Forces

The International Liaison Committee on Resuscitation engages in a continuous review of new, peer-reviewed, published cardiopulmonary resuscitation and first aid science. Draft Consensus on Science With Treatment Recommendations are posted online throughout the year, and this annual summary provides more concise versions of the final Consensus on Science With Treatment Recommendations from all task forces for the year. Topics addressed by systematic reviews this year include resuscitation of cardiac arrest from drowning, extracorporeal cardiopulmonary resuscitation for adults and children, calcium during cardiac arrest, double sequential defibrillation, neuroprognostication after cardiac arrest for adults and children, maintaining normal temperature after preterm birth, heart rate monitoring methods for diagnostics in neonates, detection of exhaled carbon dioxide in neonates, family presence during resuscitation of adults, and a stepwise approach to resuscitation skills training. Members from 6 International Liaison Committee on Resuscitation task forces have assessed, discussed, and debated the quality of the evidence, using Grading of Recommendations Assessment, Development, and Evaluation criteria, and their statements include consensus treatment recommendations. Insights into the deliberations of the task forces are provided in the Justification and Evidence-to-Decision Framework Highlights sections. In addition, the task forces list priority knowledge gaps for further research. Additional topics are addressed with scoping reviews and evidence updates.

Combination strategy for prognostication in patients undergoing post-resuscitation care after cardiac arrest

This study investigated the prognostic performance of combination strategies using a multimodal approach in patients treated after cardiac arrest. Prospectively collected registry data were used for this retrospective analysis. Poor outcome was defined as a cerebral performance category of 3-5 at 6 months. Predictors of poor outcome were absence of ocular reflexes (PR/CR) without confounding factors, a highly malignant pattern on the most recent electroencephalography, defined as suppressed background with or without periodic discharges and burst-suppression, high neuron-specific enolase (NSE) after 48 h, and diffuse injury on imaging studies (computed tomography or diffusion-weighted imaging [DWI]) at 72-96 h. The prognostic performances for poor outcomes were analyzed for sensitivity and specificity. A total of 130 patients were included in the analysis. Of these, 68 (52.3%) patients had poor outcomes. The best prognostic performance was observed with the combination of absent PR/CR, high NSE, and diffuse injury on DWI [91.2%, 95% confidence interval (CI) 80.7-97.1], whereas the combination strategy of all available predictors did not improve prognostic performance (87.8%, 95% CI 73.8-95.9). Combining three of the predictors may improve prognostic performance and be more efficient than adding all tests indiscriminately, given limited medical resources.

Early and late withdrawal of life-sustaining treatment after out-of-hospital cardiac arrest in the United Kingdom: Institutional variation and association with hospital mortality

AIM

Frequency and timing of Withdrawal of Life-Sustaining Treatment (WLST) after Out-of-Hospital Cardiac Arrest (OHCA) vary across Intensive Care Units (ICUs) in the United Kingdom (UK) and may be a marker of lower healthcare quality if instituted too frequently or too early. We aimed to describe WLST practice, quantify its variability across UK ICUs, and assess the effect of institutional deviation from average practice on patients' risk-adjusted hospital mortality.

METHODS

We conducted a retrospective multi-centre cohort study including all adult patients admitted after OHCA to UK ICUs between 2010 and 2017. We identified patient and ICU characteristics associated with early (within 72 h) and late (>72 h) WLST and quantified the between-ICU variation. We used the ICU-level observed-to-expected (O/E) ratios of early and late-WLST frequency as separate metrics of institutional deviation from average practice and calculated their association with patients' hospital mortality.

RESULTS

We included 28,438 patients across 204 ICUs. 10,775 (37.9%) had WLST and 6397 (59.4%) of them had early-WLST. Both WLST types were strongly associated with patient-level demographics and pre-existing conditions but weakly with ICU-level characteristics. After adjustment, we found unexplained between-ICU variation for both early-WLST (Median Odds Ratio 1.59, 95%CrI 1.49-1.71) and late-WLST (MOR 1.39, 95%CrI 1.31-1.50). Importantly, patients' hospital mortality was higher in ICUs with higher O/E ratio of early-WLST (OR 1.29, 95%CI 1.21-1.38, p < 0.001) or late-WLST (OR 1.39, 95%CI 1.31-1.48, p < 0.001).

CONCLUSIONS

Significant variability exists between UK ICUs in WLST frequency and timing. This matters because unexplained higher-than-expected WLST frequency is associated with higher hospital mortality independently of timing, potentially signalling prognostic pessimism and lower healthcare quality.

Post-cardiac arrest intensive care in Sweden: A survey of current clinical practice

BACKGROUND

European guidelines recommend targeted temperature management (TTM) in post-cardiac arrest care. A large multicentre clinical trial, however, showed no difference in mortality and neurological outcome when comparing hypothermia to normothermia with early treatment of fever. The study results were valid given a strict protocol for the assessment of prognosis using defined neurological examinations. With the current range of recommended TTM temperatures, and applicable neurological examinations, procedures may differ between hospitals and the variation of clinical practice in Sweden is not known.

AIM

The aim of this study was to investigate current practice in post-resuscitation care after cardiac arrest as to temperature targets and assessment of neurological prognosis in Swedish intensive care units (ICUs).

METHODS

A structured survey was conducted by telephone or e-mail in all Levels 2 and 3 (= 53) Swedish ICUs during the spring of 2022 with a secondary survey in April 2023.

RESULTS

Five units were not providing post-cardiac arrest care and were excluded. The response rate was 43/48 (90%) of the eligible units. Among the responding ICUs, normothermia (36-37.7°C) was applied in all centres (2023). There was a detailed routine for the assessment of neurological prognosis in 38/43 (88%) ICUs. Neurological assessment was applied 72-96 h after return of spontaneous circulation in 32/38 (84%) units. Electroencephalogram and computed tomography and/or magnetic resonance imaging were the most common technical methods available.

CONCLUSION

Swedish ICUs use normothermia including early treatment of fever in post-resuscitation care after cardiac arrest and almost all apply a detailed routine for the assessment of neurological prognosis. However, available methods for prognostic evaluation varies between hospitals.

Cognitive Biases and Shared Decision Making in Acute Brain Injury

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

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.

Guidelines for Neuroprognostication in Comatose Adult Survivors of Cardiac Arrest

BACKGROUND

Among cardiac arrest survivors, about half remain comatose 72 h following return of spontaneous circulation (ROSC). Prognostication of poor neurological outcome in this population may result in withdrawal of life-sustaining therapy and death. The objective of this article is to provide recommendations on the reliability of select clinical predictors that serve as the basis of neuroprognostication and provide guidance to clinicians counseling surrogates of comatose cardiac arrest survivors.

METHODS

A narrative systematic review was completed using Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology. Candidate predictors, which included clinical variables and prediction models, were selected based on clinical relevance and the presence of an appropriate body of evidence. The Population, Intervention, Comparator, Outcome, Timing, Setting (PICOTS) question was framed as follows: "When counseling surrogates of comatose adult survivors of cardiac arrest, should [predictor, with time of assessment if appropriate] be considered a reliable predictor of poor functional outcome assessed at 3 months or later?" Additional full-text screening criteria were used to exclude small and lower-quality studies. Following construction of the evidence profile and summary of findings, recommendations were based on four GRADE criteria: quality of evidence, balance of desirable and undesirable consequences, values and preferences, and resource use. In addition, good practice recommendations addressed essential principles of neuroprognostication that could not be framed in PICOTS format.

RESULTS

Eleven candidate clinical variables and three prediction models were selected based on clinical relevance and the presence of an appropriate body of literature. A total of 72 articles met our eligibility criteria to guide recommendations. Good practice recommendations include waiting 72 h following ROSC/rewarming prior to neuroprognostication, avoiding sedation or other confounders, the use of multimodal assessment, and an extended period of observation for awakening in patients with an indeterminate prognosis, if consistent with goals of care. The bilateral absence of pupillary light response > 72 h from ROSC and the bilateral absence of N20 response on somatosensory evoked potential testing were identified as reliable predictors. Computed tomography or magnetic resonance imaging of the brain > 48 h from ROSC and electroencephalography > 72 h from ROSC were identified as moderately reliable predictors.

CONCLUSIONS

These guidelines provide recommendations on the reliability of predictors of poor outcome in the context of counseling surrogates of comatose survivors of cardiac arrest and suggest broad principles of neuroprognostication. Few predictors were considered reliable or moderately reliable based on the available body of evidence.

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.

Novel serum biomarkers for predicting neurological outcomes in postcardiac arrest patients treated with targeted temperature management

OBJECTIVE

To determine the clinical feasibility of novel serum biomarkers in out-of-hospital cardiac arrest (OHCA) patients treated with target temperature management (TTM).

METHODS

This study was a prospective observational study conducted on OHCA patients who underwent TTM. We measured conventional biomarkers, neuron‑specific enolase and S100 calcium-binding protein (S-100B), as well as novel biomarkers, including tau protein, neurofilament light chain (NFL), glial fibrillary acidic protein (GFAP), and ubiquitin C-terminal hydrolase-L1 (UCH-L1), at 0, 24, 48, and 72 h after the return of spontaneous circulation identified by SIMOA immunoassay. The primary outcome was poor neurological outcome at 6 months after OHCA.

RESULTS

A total of 100 patients were included in this study from August 2018 to May 2020. Among the included patients, 46 patients had good neurologic outcomes at 6 months after OHCA. All conventional and novel serum biomarkers had the ability to discriminate between the good and poor neurological outcome groups (p < 0.001). The area under the curves of the novel serum biomarkers were highest at 72 h after cardiac arrest (CA) (0.906 for Tau, 0.946 for NFL, 0.875 for GFAP, and 0.935 for UCH-L1). The NFL at 72 h after CA had the highest sensitivity (77.1%, 95% CI 59.9-89.6) in predicting poor neurological outcomes while maintaining 100% specificity.

CONCLUSION

Novel serum biomarkers reliably predicted poor neurological outcomes for patients with OHCA treated with TTM when life-sustaining therapy was not withdrawn. Cutoffs from two large existing studies (TTM and COMACARE substudy) were externally validated in our study. The predictive power of the novel biomarkers was the highest at 72 h after CA.

Neurophysiological and Clinical Correlates of Acute Posthypoxic Myoclonus

SUMMARY

Prognostication following cardiorespiratory arrest relies on the neurological examination, which is supported by neuroimaging and neurophysiological testing. Acute posthypoxic myoclonus (PHM) is a clinical entity that has prognostic significance and historically has been considered an indicator of poor outcome, but this is not invariably the case. "Malignant" and more "benign" forms of acute PHM have been described and differentiating them is key in understanding their meaning in prognosis. Neurophysiological tests, electroencephalogram in particular, and clinical phenotyping are crucial in defining subtypes of acute PHM. This review describes the neurophysiological and phenotypic markers of malignant and benign forms of acute PHM, a clinical approach to evaluating acute PHM following cardiorespiratory arrest in determining prognosis, and gaps in our understanding of acute PHM that require further study.

Bayesian Outcome Prediction After Resuscitation From Cardiac Arrest

BACKGROUND AND OBJECTIVES

Postarrest prognostication research does not typically account for the sequential nature of real-life data acquisition and interpretation and reports nonintuitive estimates of uncertainty. Bayesian approaches offer advantages well suited to prognostication. We used Bayesian regression to explore the usefulness of sequential prognostic indicators in the context of prior knowledge and compared this with a guideline-concordant algorithm.

METHODS

We included patients hospitalized at a single center after cardiac arrest. We extracted prospective data and assumed these data accrued over time as in routine practice. We considered predictors demographic and arrest characteristics, initial and daily neurologic examination, laboratory results, therapeutic interventions, brain imaging, and EEG. We fit Bayesian hierarchical generalized linear multivariate models predicting discharge Cerebral Performance Category (CPC) 4 or 5 (poor outcomes) vs 1-3 including sequential clinical and prognostic data. We explored outcome posterior probability distributions (PPDs) for individual patients and overall. As a comparator, we applied the 2021 European Resuscitation Council and European Society of Intensive Care Medicine (ERC/ESICM) guidelines.

RESULTS

We included 2,692 patients of whom 864 (35%) were discharged with a CPC 1-3. Patients' outcome PPDs became narrow and shifted toward 0 or 1 as sequentially acquired information was added to models. These changes were largest after arrest characteristics and initial neurologic examination were included. Using information typically available at or before intensive care unit admission, sensitivity predicting poor outcome was 51% with a 0.6% false-positive rate. In our most comprehensive model, sensitivity for poor outcome prediction was 76% with 0.6% false-positive rate (FPR). The ERC/ESICM algorithm applied to 547 of 2,692 patients and yielded 36% sensitivity with 0% FPR.

DISCUSSION

Bayesian models offer advantages well suited to prognostication research. On balance, our findings support the view that in expert hands, accurate neurologic prognostication is possible in many cases before 72 hours postarrest. Although we caution against early withdrawal of life-sustaining therapies, rapid outcome prediction can inform clinical decision making and future clinical trials.

MRI markers of brain network integrity relate to neurological outcome in postanoxic coma

AIM

Current multimodal approaches leave approximately half of the comatose patients after cardiac arrest with an indeterminate prognosis. Here we investigated whether early MRI markers of brain network integrity can distinguish between comatose patients with a good versus poor neurological outcome six months later.

METHODS

We performed a prospective cohort study in 48 patients after cardiac arrest submitted in a comatose state to the Intensive Care Unit of two Dutch hospitals. MRI was performed at three days after cardiac arrest, including resting state functional MRI and diffusion-tensor imaging (DTI). Resting state fMRI was used to quantify functional connectivity within ten resting-state networks, and DTI to assess mean diffusivity (MD) in these same networks. We contrasted two groups of patients, those with good (n = 29, cerebral performance category 1-2) versus poor (n = 19, cerebral performance category 3-5) outcome at six months. Mutual associations between functional connectivity, MD, and clinical outcome were studied.

RESULTS

Patients with good outcome show higher within-network functional connectivity (fMRI) and higher MD (DTI) than patients with poor outcome across 8/10 networks, most prominent in the default mode network, salience network, and visual network. While the anatomical distribution of outcome-related changes was similar for functional connectivity and MD, the pattern of inter-individual differences was very different: functional connectivity showed larger inter-individual variability in good versus poor outcome, while the opposite was observed for MD. Exploratory analyses suggested that it is possible to define network-specific cut-off values that could help in outcome prediction: (1) high functional connectivity and high MD, associated with good outcome; (2) low functional connectivity and low MD, associated with poor outcome; (3) low functional connectivity and high MD, associated with uncertain outcome.

DISCUSSION

Resting-state functional connectivity and mean diffusivity-three days after cardiac arrest are strongly associated with neurological recovery-six months later in a complementary fashion. The combination of fMRI and MD holds potential to improve prediction of outcome.

External validation of the 2020 ERC/ESICM prognostication strategy algorithm after cardiac arrest

Purpose

To assess the performance of the post-cardiac arrest (CA) prognostication strategy algorithm recommended by the European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM) in 2020.

Methods

This was a retrospective analysis of the Korean Hypothermia Network Prospective Registry 1.0. Unconscious patients without confounders at day 4 (72–96 h) after return of spontaneous circulation (ROSC) were included. The association between the prognostic factors included in the prognostication strategy algorithm, except status myoclonus and the neurological outcome, was investigated, and finally, the prognostic performance of the prognostication strategy algorithm was evaluated. Poor outcome was defined as cerebral performance categories 3–5 at 6 months after ROSC.

Results

A total of 660 patients were included in the final analysis. Of those, 108 (16.4%) patients had a good neurological outcome at 6 months after CA. The 2020 ERC/ESICM prognostication strategy algorithm identified patients with poor neurological outcome with 60.2% sensitivity (95% CI 55.9–64.4) and 100% specificity (95% CI 93.9–100) among patients who were unconscious or had a GCS_M score ≤ 3 and with 58.2% sensitivity (95% CI 53.9–62.3) and 100% specificity (95% CI 96.6–100) among unconscious patients. When two prognostic factors were combined, any combination of prognostic factors had a false positive rate (FPR) of 0 (95% CI 0–5.6 for combination of no PR/CR and poor CT, 0–30.8 for combination of No SSEP N20 and NSE 60).

Conclusion

The 2020 ERC/ESICM prognostication strategy algorithm predicted poor outcome without an FPR and with sensitivities of 58.2–60.2%. Any combinations of two predictors recommended by ERC/ESICM showed 0% of FPR.

Advanced Life Support Update

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2022. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2022 . Further information about the Annual Update in Intensive Care and Emergency Medicine is available from https://link.springer.com/bookseries/8901 .

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).

Neurofilament light compared to neuron-specific enolase as a predictor of unfavourable outcome after out-of-hospital cardiac arrest

AIM

We compared the prognostic abilities of neurofilament light (NfL) and neuron-specific enolase (NSE) in patients resuscitated from out-of-hospital cardiac arrest (OHCA) of various aetiologies.

METHODS

We analysed frozen blood samples obtained at 24 and 48 hours from OHCA patients treated in 21 Finnish intensive care units in 2010 and 2011. We defined unfavourable outcome as Cerebral Performance Category (CPC) 3-5 at 12 months after OHCA. We evaluated the prognostic ability of the biomarkers by calculating the area under the receiver operating characteristic curves (AUROCs [95% confidence intervals]) and compared these with a bootstrap method.

RESULTS

Out of 248 adult patients, 12-month outcome was unfavourable in 120 (48.4%). The median (interquartile range) NfL concentrations for patients with unfavourable and those with favourable outcome, respectively, were 688 (146-1804) pg/mL vs. 31 (17-61) pg/mL at 24 h and 1162 (147-4361) pg/mL vs. 36 (21-87) pg/mL at 48 h, p < 0.001 for both. The corresponding NSE concentrations were 13.3 (7.2-27.3) µg/L vs. 8.5 (5.8-13.2) µg/L at 24 h and 20.4 (8.1-56.6) µg/L vs. 8.2 (5.9-12.1) µg/L at 48 h, p < 0.001 for both. The AUROCs to predict an unfavourable outcome were 0.90 (0.86-0.94) for NfL vs. 0.65 (0.58-0.72) for NSE at 24 h, p < 0.001 and 0.88 (0.83-0.93) for NfL and 0.73 (0.66-0.81) for NSE at 48 h, p < 0.001.

CONCLUSION

Compared to NSE, NfL demonstrated superior accuracy in predicting long-term unfavourable outcome after OHCA.

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.

Heart rate complexity: An early prognostic marker of patient outcome after cardiac arrest

OBJECTIVE

Early prognostication in comatose patients after cardiac arrest (CA) is difficult but essential to inform relatives and optimize treatment. Here we investigate the predictive value of heart-rate variability captured by multiscale entropy (MSE) for long-term outcomes in comatose patients during the first 24 hours after CA.

METHODS

In this retrospective analysis of prospective multi-centric cohort, we analyzed MSE of the heart rate in 79 comatose patients after CA while undergoing targeted temperature management and sedation during the first day of coma. From the MSE, two complexity indices were derived by summing values over short and long time scales (CI_s and CI_l). We splitted the data in training and test datasets for analysing the predictive value for patient outcomes (defined as best cerebral performance category within 3 months) of CI_s and CI_l.

RESULTS

Across the whole dataset, CI_l provided the best sensitivity, specificity, and accuracy (88%, 75%, and 82%, respectively). Positive and negative predictive power were 81% and 84%.

CONCLUSIONS

Characterizing the complexity of the ECG in patients after CA provides an accurate prediction of both favorable and unfavorable outcomes.

SIGNIFICANCE

The analysis of heartrate variability by means of MSE provides accurate outcome prediction on the first day of coma.

Postresuscitation care and prognostication

PURPOSE OF REVIEW

Most patients who are successfully resuscitated after cardiac arrest are initially comatose and require mechanical ventilation and other organ support in an ICU. Knowledge about the optimal strategy for treating these patients is evolving rapidly. This review will summarize the evidence on key aspects of postarrest care and prognostication, with a focus on actionable parameters that may impact patient survival and neurologic outcomes.

RECENT FINDINGS

Optimal targets for arterial blood oxygen and carbon dioxide in comatose postcardiac arrest patients remain uncertain. Observational data are conflicting and the few randomized controlled trials to date have failed to show that different ranges of blood oxygen and carbon dioxide values impact on biomarkers of neurological injury. The Targeted Temperature Management 2 (TTM-2) trial has documented no difference in 6-month mortality among comatose postcardiac arrest patients managed at 33 oC versus controlled normothermia. An extensive systematic review of the evidence on prognostication of outcome among comatose postcardiac arrest patients underpins new prognostication guidelines.

SUMMARY

Clinical guidelines for postresuscitation care have recently been updated and incorporate all the available science supporting the treatment of postcardiac arrests. At a minimum, fever should be strictly avoided in comatose postcardiac patients. Prognostication must involve multiple modalities and should not be attempted until assessment confounders have been sufficiently excluded.

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.

Brain injury after cardiac arrest

As more people are surviving cardiac arrest, focus needs to shift towards improving neurological outcomes and quality of life in survivors. Brain injury after resuscitation, a common sequela following cardiac arrest, ranges in severity from mild impairment to devastating brain injury and brainstem death. Effective strategies to minimise brain injury after resuscitation include early intervention with cardiopulmonary resuscitation and defibrillation, restoration of normal physiology, and targeted temperature management. It is important to identify people who might have a poor outcome, to enable informed choices about continuation or withdrawal of life-sustaining treatments. Multimodal prediction guidelines seek to avoid premature withdrawal in those who might survive with a good neurological outcome, or prolonging treatment that might result in survival with severe disability. Approximately one in three admitted to intensive care will survive, many of whom will need intensive, tailored rehabilitation after discharge to have the best outcomes.

Neurologic Outcome Prediction in the Intensive Care Unit

PURPOSE OF REVIEW

The burden of severe and disabling neurologic injury on survivors, families, and society can be profound. Neurologic outcome prediction, or neuroprognostication, is a complex undertaking with many important ramifications. It allows patients with good prognoses to be supported aggressively, survive, and recover; conversely, it avoids inappropriate prolonged and costly care in those with devastating injuries.

RECENT FINDINGS

Striving to maintain a high prediction performance during prognostic assessments encompasses acknowledging the shortcomings of this task and the challenges created by advances in medicine, which constantly shift the natural history of neurologic conditions. Embracing the unknowns of outcome prediction and the boundaries of knowledge surrounding neurologic recovery and plasticity is a necessary step toward refining neuroprognostication practices and improving the accuracy of prognostic impressions. The pillars of modern neuroprognostication include comprehensive characterization of neurologic injury burden (primary and secondary injuries), gauging cerebral resilience and estimated neurologic reserve, and tying it all together with individual values surrounding the acceptable extent of disability and the difficulties of an arduous convalescence journey.

SUMMARY

Comprehensive multimodal frameworks of neuroprognostication using different prognostic tools to portray the burden of neurologic injury coupled with the characterization of individual values and the degree of cerebral reserve and resilience are the cornerstone of modern outcome prediction.

Sublingual microcirculation predicts survival after out-of-hospital cardiac arrest

BACKGROUND

Despite successful resuscitation with return of spontaneous circulation (ROSC), the prediction of survival in patients suffering out-of-hospital cardiac arrest (OHCA) remains difficult. Several studies have shown alterations in sublingual microcirculation in the critical ill. We hypothesized that early alterations in sublingual microcirculation may predict short-term survival after OHCA.

METHODS

We prospectively included all adults admitted to our university hospital between April and September 2019 with ROSC following OHCA. Sidestream dark-field microscopy to obtain sublingual microcirculation was performed at admission and after 6, 12 and 24 hours. Primary outcome was survival until discharge.

RESULTS

Twenty-five patients were included. Six hours after ROSC, the proportion of perfused small vessels (PPV_small ) was lower in non-survivors than in survivors (85 ± 7.9 vs. 75 ± 6.6%; p = .01). PPV_small did not correlate with serum lactate. Stratification for survival with cutoff values >78.4% for PPV_small 6 h post-admission and <5.15 mmol/l for initial serum lactate as suggested by ROC-Analyses results in a positive predictive value of 100% and a negative one of 67% for our study population.

CONCLUSION

Estimating short-term prognosis of OHCA patients with ROSC may be supported by measuring the PPV_small at the sublingual microcirculation 6 hours after admission.

Serum markers of brain injury can predict good neurological outcome after out-of-hospital cardiac arrest

Purpose

The majority of unconscious patients after cardiac arrest (CA) do not fulfill guideline criteria for a likely poor outcome, their prognosis is considered “indeterminate”. We compared brain injury markers in blood for prediction of good outcome and for identifying false positive predictions of poor outcome as recommended by guidelines.

Methods

Retrospective analysis of prospectively collected serum samples at 24, 48 and 72 h post arrest within the Target Temperature Management after out-of-hospital cardiac arrest (TTM)-trial. Clinically available markers neuron-specific enolase (NSE) and S100B, and novel markers neurofilament light chain (NFL), total tau, ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) and glial fibrillary acidic protein (GFAP) were analysed. Normal levels with a priori cutoffs specified by reference laboratories or defined from literature were used to predict good outcome (no to moderate disability, Cerebral Performance Category scale 1–2) at 6 months.

Results

Seven hundred and seventeen patients were included. Normal NFL, tau and GFAP had the highest sensitivities (97.2–98% of poor outcome patients had abnormal serum levels) and NPV (normal levels predicted good outcome in 87–95% of patients). Normal S100B and NSE predicted good outcome with NPV 76–82.2%. Normal NSE correctly identified 67/190 (35.3%) patients with good outcome among those classified as “indeterminate outcome” by guidelines. Five patients with single pathological prognostic findings despite normal biomarkers had good outcome.

Conclusion

Low levels of brain injury markers in blood are associated with good neurological outcome after CA. Incorporating biomarkers into neuroprognostication may help prevent premature withdrawal of life-sustaining therapy.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00134-021-06481-4.

The capacity of neurological pupil index to predict absence of somatosensory evoked potentials after cardiac arrest-A study protocol

BACKGROUND

Anoxic-ischemic brain injury is the most common cause of death after cardiac arrest (CA). Robust methods to detect severe injury with a low false positive rate (FPR) for poor neurological outcome include the pupillary light reflex (PLR) and somatosensory evoked potentials (SSEP). The PLR can be assessed manually or with automated pupillometry which provides the neurological pupil index (NPi). We aim to describe the interrelation between NPi values and the absence of SSEP cortical response and to evaluate the capacity of NPi to predict the absence of cortical SSEP response in comatose patients after CA.

METHODS

A total of 50 patients will be included in an explorative, prospective, observational study of adult (>18 years) comatose survivors of CA admitted to intensive care in a university hospital. NPi assessed with a hand-held pupillometer will be compared to SSEP signals recorded >48 hours after CA. Primary outcomes are sensitivity, specificity, and odds ratio for NPi to predict bilateral absence of the SSEP N20 signal, with NPi values corresponding to <5% FPRs of SSEP absence. Secondary outcomes are the PLR and SSEP sensitivity, specificity, and odds ratio for poor neurological outcome at hospital discharge and death at 30 days.

DISCUSSION

The PLR and SSEP may have a systematic interrelation, and a certain NPi threshold could potentially predict the absence of cortical SSEP response. If this can be concluded from the present study, SSEP testing could be excluded in certain patients to save resources in the multimodal prognostication after CA. Editorial comment The interrelation between loss of the pupillary light reflex (PLR) and the loss of cortical response to a somatosensory evoked potential (SSEP) in comatose cardiac arrest patients is not known. This exploratory prospective study is designed to evaluate whether a specific degree of attenuated PLR, as measured by semiautomated pupillometry, can predict the bilateral loss of cortical SSEP response in severe anoxic/ischemic brain injury. Such an interrelation between the two methods would enable the use of pupillometry rather than the more resource demanding SSEP for neurologic prognostication in post cardiac arrest patients.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT04720482, Registered 21 January 2021, retrospectively registered.

Multimodal Approach to Predict Neurological Outcome after Cardiac Arrest: A Single-Center Experience

Introduction: The aims of this study were to assess the concordance of different tools and to describe the accuracy of a multimodal approach to predict unfavorable neurological outcome (UO) in cardiac arrest patients. Methods: Retrospective study of adult (>18 years) cardiac arrest patients who underwent multimodal monitoring; UO was defined as cerebral performance category 3–5 at 3 months. Predictors of UO were neurological pupillary index (NPi) ≤ 2 at 24 h; highly malignant patterns on EEG (HMp) within 48 h; bilateral absence of N20 waves on somato-sensory evoked potentials; and neuron-specific enolase (NSE) > 75 μg/L. Time-dependent decisional tree (i.e., NPi on day 1; HMp on day 1–2; absent N20 on day 2–3; highest NSE) and classification and regression tree (CART) analysis were used to assess the prediction of UO. Results: Of 137 patients, 104 (73%) had UO. Abnormal NPi, HMp on day 1 or 2, the bilateral absence of N20 or NSE >75 mcg/L had a specificity of 100% to predict UO. The presence of abnormal NPi was highly concordant with HMp and high NSE, and absence of N20 or high NSE with HMp. However, HMp had weak to moderate concordance with other predictors. The time-dependent decisional tree approach identified 73/103 patients (70%) with UO, showing a sensitivity of 71% and a specificity of 100%. Using the CART approach, HMp on EEG was the only variable significantly associated with UO. Conclusions: This study suggests that patients with UO had often at least two predictors of UO, except for HMp. A multimodal time-dependent approach may be helpful in the prediction of UO after CA. EEG should be included in all multimodal prognostic models.

Enabling a learning healthcare system with automated computer protocols that produce replicable and personalized clinician actions

Clinical decision-making is based on knowledge, expertise, and authority, with clinicians approving almost every intervention-the starting point for delivery of "All the right care, but only the right care," an unachieved healthcare quality improvement goal. Unaided clinicians suffer from human cognitive limitations and biases when decisions are based only on their training, expertise, and experience. Electronic health records (EHRs) could improve healthcare with robust decision-support tools that reduce unwarranted variation of clinician decisions and actions. Current EHRs, focused on results review, documentation, and accounting, are awkward, time-consuming, and contribute to clinician stress and burnout. Decision-support tools could reduce clinician burden and enable replicable clinician decisions and actions that personalize patient care. Most current clinical decision-support tools or aids lack detail and neither reduce burden nor enable replicable actions. Clinicians must provide subjective interpretation and missing logic, thus introducing personal biases and mindless, unwarranted, variation from evidence-based practice. Replicability occurs when different clinicians, with the same patient information and context, come to the same decision and action. We propose a feasible subset of therapeutic decision-support tools based on credible clinical outcome evidence: computer protocols leading to replicable clinician actions (eActions). eActions enable different clinicians to make consistent decisions and actions when faced with the same patient input data. eActions embrace good everyday decision-making informed by evidence, experience, EHR data, and individual patient status. eActions can reduce unwarranted variation, increase quality of clinical care and research, reduce EHR noise, and could enable a learning healthcare system.

Application of a standardized EEG pattern classification in the assessment of neurological prognosis after cardiac arrest: A retrospective analysis

INTRODUCTION

Electroencephalogram (EEG) is used in the neurological prognostication after cardiac arrest. "Highly malignant" EEG patterns classified according to Westhall have a high specificity for poor neurological outcome when applied within protocols of recent studies. However, their predictive performance when applied in everyday clinical practice has not been investigated. We studied the prognostic accuracy and the interrater agreement when standardized EEG patterns were analysed and compared to neurological outcome in a patient cohort at a tertiary centre not involved in the original study of the standardized EEG pattern classification.

METHODS

Comatose patients treated for out-of-hospital cardiac arrest were included. Poor outcome was defined as Cerebral Performance Category 3-5. Two senior consultants and one resident in clinical neurophysiology, blinded to clinical data and outcome, independently reviewed their EEG registrations and categorised the pattern as "highly malignant", "malignant" or "benign". These categories were compared to neurological outcome at hospital discharge. Interrater agreement was assessed using Cohen's Kappa.

RESULTS

In total, 62 patients were included. The median (IQR) time to EEG was 59 (42-91) h after return of spontaneous circulation. Poor outcome was found in 52 (84%) patients. In 21 patients at least one of the raters considered the EEG to contain a "highly malignant" pattern, all with poor outcome (42% sensitivity, 100% specificity). The interrater agreement varied from kappa 0.62 to 0.29.

CONCLUSION

"Highly malignant" patterns predict poor neurological outcome with a high specificity in everyday practice. However, interrater agreement may vary substantially even between experienced EEG interpreters.

Plasma proenkephalin A 119-159 and dipeptidyl peptidase 3 on admission after cardiac arrest help predict long-term neurological outcome

BACKGROUND

A large proportion of adult survivors of cardiac arrest have a poor neurological outcome. Guidelines recommend multimodal neuro-prognostication no earlier than 72-96 h after cardiac arrest. There is great interest in earlier prognostic markers, including very early markers at admission. The novel blood biomarkers proenkephalin A 119-159 (penKid), bioactive adrenomedullin (bio-ADM) and circulating dipeptidyl peptidase 3 (cDPP3) have not been previously investigated for the early prognosis of cardiac arrest survivors.

METHODS

This multicentre observational study included adult survivors of cardiac arrest admitted to intensive care at four Swedish intensive care units (ICUs) during 2016. Blood samples were collected at ICU admission and batch analysed. The association between admission plasma penKid, bio-ADM and cDPP3 and poor long-term neurological outcome, according to the Cerebral Performance Category (CPC) scale, was assessed by binary logistic regression. Their prognostic performance was assessed using the area under the receiver operating characteristic curve (AUC).

RESULTS

A total of 190 patients were included, of which 136 patients had suffered out-of-hospital and 54 patients in-hospital cardiac arrest. Poor long-term neurological outcome was associated with elevated admission plasma concentrations of penKid and cDPP3, but not with bio-ADM. The association for penKid, but not for cDPP3, remained after adjusting for clinical cardiac arrest variables with prognostic value (time to return of spontaneous circulation (ROSC), initial rhythm, admission Glasgow coma scale (GCS) motor score and absence of pupillary reflexes). The prognostic performance of above mentioned clinical cardiac arrest variables alone was very good with an AUC of 0.90 (95% confidence interval, CI, 0.86-0.95), but improved further with the addition of penKid resulting in an AUC of 0.93 (95% CI 0.89-0.97, p < 0.026). Plasma penKid and cDPP3 alone provided moderate long-term prognostic information with AUCs of 0.70 and 0.71, respectively.

CONCLUSION

After cardiac arrest, admission plasma levels of penKid and cDPP3, but not bio-ADM, predicted long-term neurological outcome. When added to clinical cardiac arrest variables, penKid further improved prognostic performance.

SSEP amplitude accurately predicts both good and poor neurological outcome early after cardiac arrest; a post-hoc analysis of the ProNeCA multicentre study

AIM

To assess if, in comatose resuscitated patients, the amplitude of the N20 wave (N20amp) of somatosensory evoked potentials (SSEP) can predict 6-months neurological outcome.

SETTING

Multicentre study in 13 Italian intensive care units.

METHODS

The N20amp in microvolts (μV) was measured at 12 h, 24 h, and 72 h from cardiac arrest, along with pupillary reflex (PLR) and a 30-min EEG classified according to the ACNS terminology. Sensitivity and false positive rate (FPR) of N20amp alone or in combination were calculated.

RESULTS

403 patients (age 69[58-68] years) were included. At 12 h, an N20amp >3 μV predicted good neurological outcome (Cerebral Performance Categories [CPC] 1-2) with 61[50-72]% sensitivity and 11[6-18]% FPR. Combining it with a benign (continuous or nearly continuous) EEG increased sensitivity to 91[82-96]%. For poor outcome (CPC 3-5), an N20Amp ≤0.38 μV, ≤0.73 μV and ≤1.01 μV at 12 h, 24 h, and 72 h, respectively, had 0% FPR with sensitivity ranging from 61[51-69]% and 82[76-88]%. Sensitivity was higher than that of a bilaterally absent N20 at all time points. At 12 h and 24 h, a highly malignant (suppression or burst-suppression) EEG and bilaterally absent PLR achieved 0% FPR only when combined with SSEP. A combination of all three predictors yielded a 0[0-4]% FPR, with maximum sensitivity of 44[36-53]%.

CONCLUSION

At 12 h from arrest, a high N20Amp predicts good outcome with high sensitivity, especially when combined with benign EEG. At 12 h and 24 h from arrest a low-voltage N20amp has a high sensitivity and is more specific than EEG or PLR for predicting poor outcome.

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.

Expanding controlled donation after the circulatory determination of death: statement from an international collaborative

A decision to withdraw life-sustaining treatment (WLST) is derived by a conclusion that further treatment will not enable a patient to survive or will not produce a functional outcome with acceptable quality of life that the patient and the treating team regard as beneficial. Although many hospitalized patients die under such circumstances, controlled donation after the circulatory determination of death (cDCDD) programs have been developed only in a reduced number of countries. This International Collaborative Statement aims at expanding cDCDD in the world to help countries progress towards self-sufficiency in transplantation and offer more patients the opportunity of organ donation. The Statement addresses three fundamental aspects of the cDCDD pathway. First, it describes the process of determining a prognosis that justifies the WLST, a decision that should be prior to and independent of any consideration of organ donation and in which transplant professionals must not participate. Second, the Statement establishes the permanent cessation of circulation to the brain as the standard to determine death by circulatory criteria. Death may be declared after an elapsed observation period of 5 min without circulation to the brain, which confirms that the absence of circulation to the brain is permanent. Finally, the Statement highlights the value of perfusion repair for increasing the success of cDCDD organ transplantation. cDCDD protocols may utilize either in situ or ex situ perfusion consistent with the practice of each country. Methods to accomplish the in situ normothermic reperfusion of organs must preclude the restoration of brain perfusion to not invalidate the determination of death.