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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.

The aim of these guidelines is to provide evidence‑based guidance for temperature control in adults who are comatose after resuscitation from either in-hospital or out-of-hospital cardiac arrest, regardless of the underlying cardiac rhythm. These guidelines replace the recommendations on temperature management after cardiac arrest included in the 2021 post-resuscitation care guidelines co-issued by the European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM). The guideline panel included thirteen international clinical experts who authored the 2021 ERC-ESICM guidelines and two methodologists who participated in the evidence review completed on behalf of the International Liaison Committee on Resuscitation (ILCOR) of whom ERC is a member society. We followed the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach to assess the certainty of evidence and grade recommendations. The panel provided suggestions on guideline implementation and identified priorities for future research. The certainty of evidence ranged from moderate to low. In patients who remain comatose after cardiac arrest, we recommend continuous monitoring of core temperature and actively preventing fever (defined as a temperature > 37.7 °C) for at least 72 h. There was insufficient evidence to recommend for or against temperature control at 32–36 °C or early cooling after cardiac arrest. We recommend not actively rewarming comatose patients with mild hypothermia after return of spontaneous circulation (ROSC) to achieve normothermia. We recommend not using prehospital cooling with rapid infusion of large volumes of cold intravenous fluids immediately after ROSC.

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.

Less than 500 participants have been included in randomized trials comparing hypothermia with regular care for out-of-hospital cardiac arrest patients, and many of these trials were small and at a high risk of bias. Consequently, the accrued data on this potentially beneficial intervention resembles that of a drug following small phase II trials. A large confirmatory trial is therefore warranted. The TTM2-trial is an international, multicenter, parallel group, investigator-initiated, randomized, superiority trial in which a target temperature of 33°C after cardiac arrest will be compared with a strategy to maintain normothermia and early treatment of fever (≥37.8°C). Participants will be randomized within 3 hours of return of spontaneous circulation with the intervention period lasting 40 hours in both groups. Sedation will be mandatory for all patients throughout the intervention period. The clinical team involved with direct patient care will not be blinded to allocation group due to the inherent difficulty in blinding the intervention. Prognosticators, outcome-assessors, the steering group, the trial coordinating team, and trial statistician will be blinded. The primary outcome will be all-cause mortality at 180 days after randomization. We estimate a 55% mortality in the control group. To detect an absolute risk reduction of 7.5% with an alpha of 0.05 and 90% power, 1900 participants will be enrolled. The main secondary neurological outcome will be poor functional outcome (modified Rankin Scale 4–6) at 180 days after arrest. The TTM2-trial will compare hypothermia to 33°C with normothermia and early treatment of fever (≥37.8°C) after out-of-hospital cardiac arrest.

Background Pre-hospital circumstances, cardiac arrest characteristics, comorbidities and clinical status on admission are strongly associated with outcome after out-of-hospital cardiac arrest (OHCA). Early prediction of outcome may inform prognosis, tailor therapy and help in interpreting the intervention effect in heterogenous clinical trials. This study aimed to create a model for early prediction of outcome by artificial neural networks (ANN) and use this model to investigate intervention effects on classes of illness severity in cardiac arrest patients treated with targeted temperature management (TTM). Methods Using the cohort of the TTM trial, we performed a post hoc analysis of 932 unconscious patients from 36 centres with OHCA of a presumed cardiac cause. The patient outcome was the functional outcome, including survival at 180 days follow-up using a dichotomised Cerebral Performance Category (CPC) scale with good functional outcome defined as CPC 1–2 and poor functional outcome defined as CPC 3–5. Outcome prediction and severity class assignment were performed using a supervised machine learning model based on ANN. Results The outcome was predicted with an area under the receiver operating characteristic curve (AUC) of 0.891 using 54 clinical variables available on admission to hospital, categorised as background, pre-hospital and admission data. Corresponding models using background, pre-hospital or admission variables separately had inferior prediction performance. When comparing the ANN model with a logistic regression-based model on the same cohort, the ANN model performed significantly better ( p  = 0.029). A simplified ANN model showed promising performance with an AUC above 0.852 when using three variables only: age, time to ROSC and first monitored rhythm. The ANN-stratified analyses showed similar intervention effect of TTM to 33 °C or 36 °C in predefined classes with different risk of a poor outcome. Conclusion A supervised machine learning model using ANN predicted neurological recovery, including survival excellently, and outperformed a conventional model based on logistic regression. Among the data available at the time of hospitalisation, factors related to the pre-hospital setting carried most information. ANN may be used to stratify a heterogenous trial population in risk classes and help determine intervention effects across subgroups.

The understanding of recovery after critical COVID-19 beyond the first year is limited. To describe changes in functional, physical, and mental health outcomes between 1 and 3 years among survivors of critical COVID-19 and to identify factors associated with incomplete recovery at 3 years. A prospective multicentre cohort study of survivors of critical COVID-19 with follow-up at 1 and 3 years. The primary outcome was functional outcome, assessed using the Glasgow Outcome Scale-Extended (GOSE), which ranges from 1 to 8, with scores of 6 or less indicating incomplete recovery. Secondary outcomes included return-to-work, physical and mental Health-Related Quality of Life (HRQoL), life satisfaction, fatigue, psychological symptoms (anxiety, depression, post-traumatic stress disorder), and respiratory symptoms. Multivariable logistic regression was used to identify factors associated with incomplete recovery (GOSE ≤ 6) at 3 years. Among 191 of 210 eligible participants, functional outcome declined from 1 to 3 years, and participants with incomplete recovery increased from 32% to 45%. Worse outcomes were observed in mental HRQoL, fatigue, depression, and post-traumatic stress, while return-to-work rates, physical HRQoL, life satisfaction, anxiety, and respiratory symptoms remained stable. Younger age [OR 0.70 (95% CI 0.54-0.91), p = 0.008] and higher Clinical Frailty Scale score [OR 1.54 (95% CI 1.04-2.28), p = 0.029] were independently associated with incomplete recovery at 3 years. Survivors of critical COVID-19 experienced a decline in functional outcome and worsening mental health between 1 and 3 years after ICU admission. Younger and frail survivors may require increased attention and support. ClinicalTrials.gov Identifier: NCT04974775, registered April 28, 2020.

Background Prognostication of neurological outcome in patients who remain comatose after cardiac arrest resuscitation is complex. Clinical variables, as well as biomarkers of brain injury, cardiac injury, and systemic inflammation, all yield some prognostic value. We hypothesised that cumulative information obtained during the first three days of intensive care could produce a reliable model for predicting neurological outcome following out-of-hospital cardiac arrest (OHCA) using artificial neural network (ANN) with and without biomarkers. Methods We performed a post hoc analysis of 932 patients from the Target Temperature Management trial. We focused on comatose patients at 24, 48, and 72 h post-cardiac arrest and excluded patients who were awake or deceased at these time points. 80% of the patients were allocated for model development (training set) and 20% for internal validation (test set). To investigate the prognostic potential of different levels of biomarkers (clinically available and research-grade), patients’ background information, and intensive care observation and treatment, we created three models for each time point: (1) clinical variables, (2) adding clinically accessible biomarkers, e.g., neuron-specific enolase (NSE) and (3) adding research-grade biomarkers, e.g., neurofilament light (NFL). Patient outcome was the dichotomised Cerebral Performance Category (CPC) at six months; a good outcome was defined as CPC 1–2 whilst a poor outcome was defined as CPC 3–5. The area under the receiver operating characteristic curve (AUROC) was calculated for all test sets. Results AUROC remained below 90% when using only clinical variables throughout the first three days in the ICU. Adding clinically accessible biomarkers such as NSE, AUROC increased from 82 to 94% ( p  < 0.01). The prognostic accuracy remained excellent from day 1 to day 3 with an AUROC at approximately 95% when adding research-grade biomarkers. The models which included NSE after 72 h and NFL on any of the three days had a low risk of false-positive predictions while retaining a low number of false-negative predictions. Conclusions In this exploratory study, ANNs provided good to excellent prognostic accuracy in predicting neurological outcome in comatose patients post OHCA. The models which included NSE after 72 h and NFL on all days showed promising prognostic performance.

Background Cognitive impairment is common following out-of-hospital cardiac arrest (OHCA), but the nature of the impairment is poorly understood. Our objective was to describe cognitive impairment in OHCA survivors, with the hypothesis that OHCA survivors would perform significantly worse on neuropsychological tests of cognition than controls with acute myocardial infarction (MI). Another aim was to investigate the relationship between cognitive performance and the associated factors of emotional problems, fatigue, insomnia, and cardiovascular risk factors following OHCA. Methods This was a prospective case–control sub-study of The Targeted Hypothermia versus Targeted Normothermia after Out-of-Hospital Cardiac Arrest (TTM2) trial. Eight of 61 TTM2-sites in Sweden, Denmark, and the United Kingdom included adults with OHCA of presumed cardiac or unknown cause. A matched non-arrest control group with acute MI was recruited. At approximately 7 months post-event, we administered an extensive neuropsychological test battery and questionnaires on anxiety, depression, fatigue, and insomnia, and collected information on the cardiovascular risk factors hypertension and diabetes. Results Of 184 eligible OHCA survivors, 108 were included, with 92 MI controls enrolled. Amongst OHCA survivors, 29% performed z -score ≤ − 1 (at least borderline–mild impairment) in ≥ 2 cognitive domains, 14% performed z -score ≤ − 2 (major impairment) in ≥ 1 cognitive domain while 54% performed without impairment in any domain. Impairment was most pronounced in episodic memory, executive functions, and processing speed. OHCA survivors performed significantly worse than MI controls in episodic memory (mean difference, MD = − 0.37, 95% confidence intervals [− 0.61, − 0.12]), verbal (MD = − 0.34 [− 0.62, − 0.07]), and visual/constructive functions (MD = − 0.26 [− 0.47, − 0.04]) on linear regressions adjusted for educational attainment and sex. When additionally adjusting for anxiety, depression, fatigue, insomnia, hypertension, and diabetes, executive functions (MD = − 0.44 [− 0.82, − 0.06]) were also worse following OHCA. Diabetes, symptoms of anxiety, depression, and fatigue were significantly associated with worse cognitive performance. Conclusions In our study population, cognitive impairment was generally mild following OHCA. OHCA survivors performed worse than MI controls in 3 of 6 domains. These results support current guidelines that a post-OHCA follow-up service should screen for cognitive impairment, emotional problems, and fatigue. Trial registration ClinicalTrials.gov, NCT03543371. Registered 1 June 2018.

ObjectiveThe aim was to compare self-reported health between cardiac arrest survivors with good cerebral performance (CPC 1) and survivors with moderate cerebral disability (CPC 2).MethodsThis comparative register study was based on nationwide data from the Swedish Register of Cardiopulmonary Resuscitation. The study included 2058 in-hospital and out-of-hospital cardiac arrest survivors with good cerebral performance or survivors with moderate cerebral disability, 3–6 months postcardiac arrest. Survivors completed a questionnaire including the Hospital Anxiety and Depression Scale (HADS) and EQ-5D five-levels (EQ-5D-5L). Data were analysed using ordinal and linear regression models.ResultsFor all survivors, the prevalence of anxiety and depression symptoms measured by the HADS was 14% and 13%, respectively. Using the EQ-5D-5L, the cardiac arrest survivors reported most health problems relating to pain/discomfort (57%), followed by anxiety/depression (47%), usual activities (46%), mobility (40%) and self-care (18%). Compared with the survivors with good cerebral performance, survivors with moderate cerebral disability reported significantly higher symptom levels of anxiety and depression measured with HADS, and poorer health in all dimensions of the EQ-5D-5L after adjusting for age, sex, place of cardiac arrest, aetiology and initial rhythm (p<0.001).ConclusionsThese findings stress the importance of screening for health problems in all cardiac arrest survivors to identify those in need of professional support and rehabilitation, independent on neurological outcome.

Background Calprotectin (S100A8/A9) is a pro-inflammatory mediator primarily released from neutrophils. Previous studies have revealed associations between plasma calprotectin, disease severity and in-hospital mortality in unselected COVID-19 patients. Objective We aimed to assess whether plasma calprotectin dynamics during the first week of intensive care are associated with mortality and functional outcome in critically ill COVID-19 patients. Methods This prospective study included 498 COVID-19 patients admitted to six intensive care units (ICUs) in Sweden between May 2020 and May 2021. Blood samples were collected on ICU admission and on day 7. The primary outcome was 12-month mortality. Secondary outcomes were functional outcome of survivors at 3 and 12 months, and the need for invasive mechanical ventilation (IMV) or continuous renal replacement therapy (CRRT) during the ICU stay. Functional outcome was assessed by the Glasgow Outcome Scale Extended (GOSE, range 1–8, with < 5 representing an unfavourable outcome). Associations between plasma calprotectin and outcomes were examined in binary logistic regression analyses adjusted for age, sex, BMI, hypertension, smoking, and creatinine. Results High plasma calprotectin on admission and day 7 was independently associated with increased 12-month mortality. Increasing calprotectin from admission to day 7 was independently associated with higher mortality at 12 months [OR 2.10 (95% CI 1.18–3.74), p  = 0.012], unfavourable functional outcome at 3 months [OR 2.53 (95% CI 1.07–6.10), p  = 0.036], and the use of IMV [OR 2.23 (95% CI 1.10–4.53), p  = 0.027)] and CRRT [OR 2.07 (95% CI 1.07–4.00), p  = 0.031)]. A receiver operator characteristic (ROC) model including day 7 calprotectin and age was a good predictor of 12-month mortality [AUC 0.79 (95% CI 0.74–0.84), p  < 0.001]. Day 7 calprotectin alone predicted an unfavourable functional outcome at 3 months [AUC 0.67 (95% CI 0.58–0.76), p  < 0.001]. Conclusion In critically ill COVID-19 patients, increasing calprotectin levels after admission to the ICU are associated with 12-month mortality and unfavourable functional outcome in survivors. Monitoring plasma calprotectin dynamics in the ICU may be considered to evaluate prognosis in critical COVID-19. Study registration: ClinicalTrials.gov Identifier : NCT04974775, registered April 28, 2020.