Dalbavancin in catheter-related bloodstream infections: a pilot study.

Background: Catheter-related bloodstream infections (CRBSI) represent a frequent complication of vascular catheterization, with high morbidity, mortality, and associated costs. Most infections are caused by Gram-positive bacteria; thus dalbavancin, a new long-acting lipoglicopeptide, may have a role in early patient discharge strategies optimizing treatment and reducing overall costs. Methods: In this small pilot feasibility study, we assessed the efficacy and safety of a "single step" treatment strategy combining dalbavancin administration (1500 mg IV single dose), catheter removal, and early discharge in adult patients admitted to medical wards in a three-year period. Results: We enrolled sixteen patients with confirmed Gram-positive CRBSI, with a mean age of 68 years and relevant comorbidities (median Charlson Comorbidity index=7). The most frequent causative agents were staphylococci, with 25% of methicillin-resistant strains, and the majority of infected devices were short term central venous catheter (CVC) and peripherally inserted central catheter (PICC). Ten out of sixteen patients had been treated empirically before dalbavancin administration. The mean time from dalbavancin administration to discharge was 2 days; none of the patients had adverse drug-related reactions; at 30- and 90-day follow-up, no patients have been readmitted to the hospital due to bacteraemia recurrence. Conclusions: Our results indicate that single-dose dalbavancin is highly effective, well-tolerated, and cost-saving for Gram-positive CRBSI.

Brain injury markers in blood predict signs of hypoxic ischaemic encephalopathy on head computed tomography after cardiac arrest.

BACKGROUND/AIM: Signs of hypoxic ischaemic encephalopathy (HIE) on head computed tomography (CT) predicts poor neurological outcome after cardiac arrest. We explore whether levels of brain injury markers in blood could predict the likelihood of HIE on CT. METHODS: Retrospective analysis of CT performed at 24-168 h post cardiac arrest on clinical indication within the Target Temperature Management after out-of-hospital cardiac arrest-trial. Biomarkers prospectively collected at 24- and 48 h post-arrest were analysed for neuron specific enolase (NSE), neurofilament light (NFL), total-tau and glial fibrillary acidic protein (GFAP). HIE was assessed through visual evaluation and quantitative grey-white-matter ratio (GWR) was retrospectively calculated on Swedish subjects with original images available. RESULTS: In total, 95 patients were included. The performance to predict HIE on CT (performed at IQR 73-116 h) at 48 h was similar for all biomarkers, assessed as area under the receiving operating characteristic curve (AUC) NSE 0.82 (0.71-0.94), NFL 0.79 (0.67-0.91), total-tau 0.84 (0.74-0.95), GFAP 0.79 (0.67-0.90). The predictive performance of biomarker levels at 24 h was AUC 0.72-0.81. At 48 h biomarker levels below Youden Index accurately excluded HIE in 77.3-91.7% (negative predictive value) and levels above Youden Index correctly predicted HIE in 73.3-83.7% (positive predictive value). NSE cut-off at 48 h was 48 ng/ml. Elevated biomarker levels irrespective of timepoint significantly correlated with lower GWR. CONCLUSION: Biomarker levels can assess the likelihood of a patient presenting with HIE on CT and could be used to select suitable patients for CT-examination during neurological prognostication in unconscious cardiac arrest patients.

Neuronal desertification after a direct lightning strike: a case report.

BACKGROUND: Lightning strike is a rare but dramatic cause of injury. Patients admitted to intensive care units (ICUs) with lightning strike frequently have a high mortality and significant long-term morbidity related to a direct brain injury or induced cardiac arrest (CA). CASE PRESENTATION: A 50-year-old Caucasian man was admitted to our hospital after being struck by lightning resulting in immediate CA. Spontaneous circulation was initially restored, and the man was admitted to the ICU, but ultimately died while in hospital due to neurological injury. The computer tomography scan revealed a massive loss of grey-white matter differentiation at the fronto-temporal lobes bilaterally. Somatosensory-evoked potentials demonstrated bilateral absence of the cortical somatosensory N20-potential, and the electroencephalogram recorded minimal cerebral electrical activity. The patient died on day 10 and a post-mortem study revealed a widespread loss of neurons. CONCLUSION: This case study illustrates severe brain injury caused by a direct lighting strike, with the patient presenting an extraordinary microscopic pattern of neuronal desertification.

Hypothermic versus Normothermic Temperature Control after Cardiac Arrest.

Hypothermia versus Normothermia after Cardiac ArrestHolgersson et al. perform an individual patient data meta-analysis of the TTM and TTM2 trials of hypothermia after cardiac arrest and find no difference in 6-month mortality with hypothermia to 33°C versus normothermia.

Do ventilatory parameters influence outcome in patients with severe acute respiratory infection? Secondary analysis of an international, multicentre14-day inception cohort study.

PURPOSE: To investigate the possible association between ventilatory settings on the first day of invasive mechanical ventilation (IMV) and mortality in patients admitted to the intensive care unit (ICU) with severe acute respiratory infection (SARI). MATERIALS AND METHODS: In this pre-planned sub-study of a prospective, multicentre observational study, 441 patients with SARI who received controlled IMV during the ICU stay were included in the analysis. RESULTS: ICU and hospital mortality rates were 23.1 and 28.1%, respectively. In multivariable analysis, tidal volume and respiratory rate on the first day of IMV were not associated with an increased risk of death; however, higher driving pressure (DP: odds ratio (OR) 1.05; 95% confidence interval (CI): 1.01-1.1, p = 0.011), plateau pressure (Pplat) (OR 1.08; 95% CI: 1.04-1.13, p < 0.001) and positive end-expiratory pressure (PEEP) (OR 1.13; 95% CI: 1.03-1.24, p = 0.006) were independently associated with in-hospital mortality. In subgroup analysis, in hypoxemic patients and in patients with acute respiratory distress syndrome (ARDS), higher DP, Pplat, and PEEP were associated with increased risk of in-hospital death. CONCLUSIONS: In patients with SARI receiving IMV, higher DP, Pplat and PEEP, and not tidal volume, were associated with a higher risk of in-hospital death, especially in those with hypoxemia or ARDS.

[Adult advanced life support]. / Erweiterte lebensrettende Maßnahmen für Erwachsene: Leitlinien des European Resuscitation Council 2021.

These European Resuscitation Council Advanced Life Support guidelines are based on the 2020 International Consensus on Cardiopulmonary Resuscitation Science with Treatment Recommendations. This section provides guidelines on the prevention of and ALS treatments for both in-hospital cardiac arrest and out-of-hospital cardiac arrest.

Artificial neural network model from a case series of COVID-19 patients: a prognostic analysis.

BACKGROUND AND AIM: There is a need to determine which clinical variables predict the severity of COVID-19. We analyzed a series of critically ill COVID-19 patients to see if any of our dataset's clinical variables were associated with patient outcomes. METHODS: We retrospectively analyzed the data of COVID-19 patients admitted to the ICU of the Hospital in Pordenone from March 11, 2020, to April 17, 2020. Patients' characteristics of survivors and deceased groups were compared. The variables with a different distribution between the two groups were implemented in a generalized linear regression model (LM) and in an Artificial Neural Network (NN) model to verify the "robustness" of the association with mortality. RESULTS: In the considered period, we reviewed the data of 22 consecutive patients: 8 died. The causes of death were a severe respiratory failure (3), multi-organ failure (1), septic shock (1), pulmonary thromboembolism (2), severe hemorrhage (1). Lymphocyte and the platelet count were significantly lower in the group of deceased patients (p-value 0.043 and 0.020, respectively; cut-off values: 660/mm3; 280,000/mm3, respectively). Prothrombin time showed a statistically significant trend (p-value= 0.065; cut-off point: 16.8/sec). The LM model (AIC= 19.032), compared to the NN model (Mean Absolute Error, MAE = 0.02), was substantially alike (MSE 0.159 vs. 0.136). CONCLUSIONS: In the context of critically ill COVID-19 patients admitted to ICU, lymphocytopenia, thrombocytopenia, and lengthening of prothrombin time were strictly correlated with higher mortality. Additional clinical data are needed to be able to validate this prognostic score.

Diagnostic performance of an automated chemiluminescence immunoassay for SARS-CoV-2 IgG and IgM antibodies detection: A real life experience.

BACKGROUND: Recently many serological assays for detection of antibodies to SARS-COV-2 virus were introduced on the market. Aim of this study was to assess the diagnostic performance of an automated CLIA for quantitative detection of anti-SARS-CoV-2 IgM and IgG antibodies. METHODS: A total of 354 sera, 89 from consecutive patients diagnosed with COVID-19 (43 mild, 32 severe and 13 critical) and 265 from asymptomatic and negative on rRT-PCR testing healthcare workers, were evaluated for IgM and IgG anti-SARS-CoV-2 antibodies with MAGLUMI immunoassay. RESULTS: The overall sensitivity and specificity were 86.5% (95%CI: 77.6-92.8) and 98.5% (95%CI:96.2-99.6), respectively. PPV, PPN, LR+, LR- and OR were 95.1 (95%CI: 87.8-98.6), 95.6 (95%CI: 92.4-97.7), 57.3 (95%CI: 21.6-152.1), 7.3 (95%CI: 4.31-12.4) and 418.6 (95%CI: 131.2-1335.2), respectively. The levels of SARS-CoV-2 IgM and IgG antibodies were 1.22 â€‹± â€‹1.2 AU/mL and 15.86 â€‹± â€‹24.83 AU/mL, 2.86 â€‹± â€‹2.4 AU/mL and 69.3 â€‹± â€‹55.5 AU/mL, 2.47 â€‹± â€‹1.33 AU/mL and 83.9 â€‹± â€‹83.9 AU/mL in mild, severe and critical COVID-19 groups, respectively. A significant difference in antibody levels between mild and severe/critical subjects has been shown. CONCLUSIONS: The CLIA assay showed good diagnostic performance and a significant association between antibody levels and severity of the disease was found.

Classification and analysis of outcome predictors in non-critically ill COVID-19 patients.

BACKGROUND: Early detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected patients who could develop a severe form of COVID-19 must be considered of great importance to carry out adequate care and optimise the use of limited resources. AIMS: To use several machine learning classification models to analyse a series of non-critically ill COVID-19 patients admitted to a general medicine ward to verify if any clinical variables recorded could predict the clinical outcome. METHODS: We retrospectively analysed non-critically ill patients with COVID-19 admitted to the general ward of the hospital in Pordenone from 1 March 2020 to 30 April 2020. Patients' characteristics were compared based on clinical outcomes. Through several machine learning classification models, some predictors for clinical outcome were detected. RESULTS: In the considered period, we analysed 176 consecutive patients admitted: 119 (67.6%) were discharged, 35 (19.9%) dead and 22 (12.5%) were transferred to intensive care unit. The most accurate models were a random forest model (M2) and a conditional inference tree model (M5) (accuracy = 0.79; 95% confidence interval 0.64-0.90, for both). For M2, glomerular filtration rate and creatinine were the most accurate predictors for the outcome, followed by age and fraction-inspired oxygen. For M5, serum sodium, body temperature and arterial pressure of oxygen and inspiratory fraction of oxygen ratio were the most reliable predictors. CONCLUSIONS: In non-critically ill COVID-19 patients admitted to a medical ward, glomerular filtration rate, creatinine and serum sodium were promising predictors for the clinical outcome. Some factors not determined by COVID-19, such as age or dementia, influence clinical outcomes.

Multimodal Long-Term Predictors of Outcome in Out of Hospital Cardiac Arrest Patients Treated with Targeted Temperature Management at 36 °C.

Introduction: Early prediction of long-term outcomes in patients resuscitated after cardiac arrest (CA) is still challenging. Guidelines suggested a multimodal approach combining multiple predictors. We evaluated whether the combination of the electroencephalography (EEG) reactivity, somatosensory evoked potentials (SSEPs) cortical complex and Gray to White matter ratio (GWR) on brain computed tomography (CT) at different temperatures could predict survival and good outcome at hospital discharge and six months after the event. Methods: We performed a retrospective cohort study including consecutive adult, non-traumatic patients resuscitated from out-of-hospital CA who remained comatose on admission to our intensive care unit from 2013 to 2017. We acquired SSEPs and EEGs during the treatment at 36 °C and after rewarming at 37 °C, Gray to white matter ratio (GWR) was calculated on the brain computed tomography scan performed within six hours of the hospital admission. We primarily hypothesized that SSEP was associated with favor-able functional outcome at distance and secondarily that SSEP provides independent information from EEG and CT. Outcomes were evaluated using the Cerebral Performance Category (CPC) scale at six months from discharge. Results: Of 171 resuscitated patients, 75 were excluded due to missing data or uninterpretable neurophysiological findings. EEG reactivity at 37 °C has been shown the best single predictor of good out-come (AUC 0.803) while N20P25 was the best single predictor for survival at each time point. (AUC 0.775 at discharge and AUC 0.747 at six months follow up). The predictive value of a model including EEG reactivity, average GWR, and SSEP N20P25 amplitude was superior (AUC 0.841 for survival and 0.920 for good out-come) to any combination of two tests or any single test. Conclusions: Our study, in which life-sustaining treatments were never suspended, suggests SSEP cortical complex N20P25, after normothermia and off sedation, is a reliable predictor for survival at any time. When SSEP cortical complex N20P25 is added into a model with GWR average and EEG reactivity, the predictivity for good outcome and survival at distance is superior than each single test alone.

European Resuscitation Council Guidelines 2021: Adult advanced life support.

These European Resuscitation Council Advanced Life Support guidelines, are based on the 2020 International Consensus on Cardiopulmonary Resuscitation Science with Treatment Recommendations. This section provides guidelines on the prevention of and ALS treatments for both in-hospital cardiac arrest and out-of-hospital cardiac arrest.

Education, Implementation, and Teams: 2020 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations.

For this 2020 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations, the Education, Implementation, and Teams Task Force applied the population, intervention, comparator, outcome, study design, time frame format and performed 15 systematic reviews, applying the Grading of Recommendations, Assessment, Development, and Evaluation guidance. Furthermore, 4 scoping reviews and 7 evidence updates assessed any new evidence to determine if a change in any existing treatment recommendation was required. The topics covered included training for the treatment of opioid overdose; basic life support, including automated external defibrillator training; measuring implementation and performance in communities, and cardiac arrest centers; advanced life support training, including team and leadership training and rapid response teams; measuring cardiopulmonary resuscitation performance, feedback devices, and debriefing; and the use of social media to improve cardiopulmonary resuscitation application.

Willingness to perform bystander cardiopulmonary resuscitation: A scoping review.

BACKGROUND: Despite the proven effectiveness of rapid initiation of cardiopulmonary resuscitation (CPR) for patients with out-of-hospital cardiac arrest (OHCA) by bystanders, fewer than half of the victims actually receive bystander CPR. We aimed to review the evidence of the barriers and facilitators for bystanders to perform CPR. METHODS: This scoping review was conducted as part of the continuous evidence evaluation process of the International Liaison Committee on Resuscitation (ILCOR), and followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews. This review included studies assessing barriers or facilitators for the lay rescuers to perform CPR in actual emergency settings and excluded studies that overlapped with other ILCOR systematic reviews/scoping reviews (e.g. dispatcher instructed CPR etc). The key findings were classified into three kinds of factors: personal factors; CPR knowledge; and procedural issues. RESULTS: We identified 18 eligible studies. Of these studies addressing the reduced willingness to respond to cardiac arrest, 14 related to "personal factors", 3 to "CPR knowledge", and 2 to "procedural issues". On the other hand, we identified 5 articles assessing factors increasing bystanders' willingness to perform CPR. However, we observed significant heterogeneity among study populations, methodologies, factors definitions, outcome measures utilized and outcomes reported. CONCLUSIONS: We found that a number of factors were present in actual settings which either inhibit or facilitate lay rescuers' performance of CPR. Interventional strategies to improve CPR performance of lay rescuers in the actual settings should be established, taking these factors into consideration.

Serum Neurofilament Light Chain for Prognosis of Outcome After Cardiac Arrest.

Importance: Prognostication of neurologic outcome after cardiac arrest is an important but challenging aspect of patient therapy management in critical care units. Objective: To determine whether serum neurofilament light chain (NFL) levels can be used for prognostication of neurologic outcome after cardiac arrest. Design, Setting and Participants: Prospective clinical biobank study of data from the randomized Target Temperature Management After Cardiac Arrest trial, an international, multicenter study with 29 participating sites. Patients were included between November 11, 2010, and January 10, 2013. Serum NFL levels were analyzed between August 1 and August 23, 2017, after trial completion. A total of 782 unconscious patients with out-of-hospital cardiac arrest of presumed cardiac origin were eligible. Exposures: Serum NFL concentrations analyzed at 24, 48, and 72 hours after cardiac arrest with an ultrasensitive immunoassay. Main Outcomes and Measures: Poor neurologic outcome at 6-month follow-up, defined according to the Cerebral Performance Category Scale as cerebral performance category 3 (severe cerebral disability), 4 (coma), or 5 (brain death). Results: Of 782 eligible patients, 65 patients (8.3%) were excluded because of issues with aliquoting, missing sampling, missing outcome, or transport problems of samples. Of the 717 patients included (91.7%), 580 were men (80.9%) and median (interquartile range [IQR]) age was 65 (56-73) years. A total of 360 patients (50.2%) had poor neurologic outcome at 6 months. Median (IQR) serum NFL level was significantly increased in the patients with poor outcome vs good outcome at 24 hours (1426 [299-3577] vs 37 [20-70] pg/mL), 48 hours (3240 [623-8271] vs 46 [26-101] pg/mL), and 72 hours (3344 [845-7838] vs 54 [30-122] pg/mL) (P < .001 at all time points), with high overall performance (area under the curve, 0.94-0.95) and high sensitivities at high specificities (eg, 69% sensitivity with 98% specificity at 24 hours). Serum NFL levels had significantly greater performance than the other biochemical serum markers (ie, tau, neuron-specific enolase, and S100). At comparable specificities, serum NFL levels had greater sensitivity for poor outcome compared with routine electroencephalogram, somatosensory-evoked potentials, head computed tomography, and both pupillary and corneal reflexes (ranging from 29.2% to 49.0% greater for serum NFL level). Conclusions and Relevance: Findings from this study suggest that the serum NFL level is a highly predictive marker of long-term poor neurologic outcome at 24 hours after cardiac arrest and may be a useful complement to currently available neurologic prognostication methods.

Worldwide audit of blood transfusion practice in critically ill patients.

BACKGROUND: The aim was to describe transfusion practice in critically ill patients at an international level and evaluate the effects of red blood cell (RBC) transfusion on outcomes in these patients. METHODS: This was a pre-planned sub-study of the Intensive Care Over Nations audit, which involved 730 ICUs in 84 countries and included all adult patients admitted between 8 May and 18 May 2012, except admissions for routine postoperative surveillance. RESULTS: ICU and hospital outcomes were recorded. Among the 10,069 patients included in the audit, data related to transfusion had been completed for 9553 (mean age 60 ± 18 years, 60% male); 2511 (26.3%) of these had received a transfusion, with considerable variation among geographic regions. The mean lowest hemoglobin on the day of transfusion was 8.3 ± 1.7 g/dL, but varied from 7.8 ± 1.4 g/dL in the Middle East to 8.9 ± 1.9 g/dL in Eastern Europe. Hospital mortality rates were higher in transfused than in non-transfused patients (30.0% vs. 19.6%, p < 0.001) and increased with increasing numbers of transfused units. In an extended Cox proportional hazard analysis, the relative risk of in-hospital death was slightly lower after transfusion in the whole cohort (hazard ratio 0.98, confidence interval 0.96-1.00, p = 0.048). There was a stepwise decrease in the hazard ratio for mortality after transfusion with increasing admission severity scores. CONCLUSIONS: More than one fourth of critically ill patients are transfused during their ICU stay, with considerable variations in transfusion practice among geographic regions. After adjustment for confounders, RBC transfusions were associated with a slightly lower relative risk of in-hospital death, especially in the most severely ill patients, highlighting the importance of taking the severity of illness into account when making transfusion decisions.

Serum tau and neurological outcome in cardiac arrest.

OBJECTIVE: To test serum tau as a predictor of neurological outcome after cardiac arrest. METHODS: We measured the neuronal protein tau in serum at 24, 48, and 72 hours after cardiac arrest in 689 patients in the prospective international Target Temperature Management trial. The main outcome was poor neurological outcome, defined as Cerebral Performance Categories 3-5 at 6 months. RESULTS: Increased tau was associated with poor outcome at 6 months after cardiac arrest (median = 38.5, interquartile range [IQR] = 5.7-245ng/l in poor vs median = 1.5, IQR = 0.7-2.4ng/l in good outcome, for tau at 72 hours, p < 0.0001). Tau improved prediction of poor outcome compared to using clinical information (p < 0.0001). Tau cutoffs had low false-positive rates (FPRs) for good outcome while retaining high sensitivity for poor outcome. For example, tau at 72 hours had FPR = 2% (95% CI = 1-4%) with sensitivity = 66% (95% CI = 61-70%). Tau had higher accuracy than serum neuron-specific enolase (NSE; the area under the receiver operating characteristic curve was 0.91 for tau vs 0.86 for NSE at 72 hours, p = 0.00024). During follow-up (up to 956 days), tau was significantly associated with overall survival. The accuracy in predicting outcome by serum tau was equally high for patients randomized to 33 °C and 36 °C targeted temperature after cardiac arrest. INTERPRETATION: Serum tau is a promising novel biomarker for prediction of neurological outcome in patients with cardiac arrest. It may be significantly better than serum NSE, which is recommended in guidelines and currently used in clinical practice in several countries to predict outcome after cardiac arrest. Ann Neurol 2017;82:665-675.

Head computed tomography for prognostication of poor outcome in comatose patients after cardiac arrest and targeted temperature management.

INTRODUCTION: A multimodal approach to prognostication of outcome after cardiac arrest (CA) is recommended. Evidence for combinations of methods is low. In this post-hoc analysis we described findings on head computed tomography (CT) after CA. We also examined whether generalised oedema on CT alone or together with the biomarker Neuron-specific enolase (NSE) could predict poor outcome. METHODS: Patients participating in the Target Temperature Management after out-of-hospital-cardiac-arrest-trial underwent CT based on clinical indications. Findings were divided into pre-specified categories according to local radiologists descriptions. Generalised oedema alone and in combination with peak NSE at either 48h or 72h was correlated with poor outcome at 6 months follow-up using the Cerebral Performance Category (CPC 3-5). RESULTS: 356/939 (37.9%) of patients underwent head CT. Initial CT≤24h after CA was normal in 174/218 (79.8%), whilst generalised oedema was diagnosed in 21/218 (9.6%). Between days 1-7, generalised oedema was seen in 65/143 (45.5%), acute/subacute infarction in 27/143 (18.9%) and bleeding in 9/143 (6.3%). Overall, generalised oedema predicted poor outcome with 33.6% sensitivity (95%CI:28.1-39.5) and 98.4% specificity (95%CI:94.3-99.6), whilst peak NSE demonstrated sensitivities of 61.5-64.8% and specificity 95.7% (95%CI:89.5-98.4). The combination of peak NSE>38ng/l and generalised oedema on CT predicted poor outcome with 46.0% sensitivity (95%CI:36.5-55.8) with no false positives. NSE was significantly higher in patients with generalised oedema. CONCLUSION: In this study, generalised oedema was more common >24h≤7d after CA. The combination of CT and NSE improved sensitivity and specificity compared to CT alone, with no false positives in this limited population.

Protein S100 as outcome predictor after out-of-hospital cardiac arrest and targeted temperature management at 33 °C and 36 °C.

BACKGROUND: We aimed to investigate the diagnostic performance of S100 as an outcome predictor after out-of-hospital cardiac arrest (OHCA) and the potential influence of two target temperatures (33 °C and 36 °C) on serum levels of S100. METHODS: This is a substudy of the Target Temperature Management after Out-of-Hospital Cardiac Arrest (TTM) trial. Serum levels of S100 were measured a posteriori in a core laboratory in samples collected at 24, 48, and 72 h after OHCA. Outcome at 6 months was assessed using the Cerebral Performance Categories Scale (CPC 1-2 = good outcome, CPC 3-5 = poor outcome). RESULTS: We included 687 patients from 29 sites in Europe. Median S100 values were higher in patients with a poor outcome at 24, 48, and 72 h: 0.19 (IQR 0.10-0.49) versus 0.08 (IQR 0.06-0.11) µg/ml, 0.16 (IQR 0.10-0.44) versus 0.07 (IQR 0.06-0.11) µg/L, and 0.13 (IQR 0.08-0.26) versus 0.06 (IQR 0.05-0.09) µg/L (p < 0.001), respectively. The ability to predict outcome was best at 24 h with an AUC of 0.80 (95% CI 0.77-0.83). S100 values were higher at 24 and 72 h in the 33 °C group than in the 36 °C group (0.12 [0.07-0.22] versus 0.10 [0.07-0.21] µg/L and 0.09 [0.06-0.17] versus 0.08 [0.05-0.10], respectively) (p < 0.02). In multivariable analyses including baseline variables and the allocated target temperature, the addition of S100 improved the AUC from 0.80 to 0.84 (95% CI 0.81-0.87) (p < 0.001), but S100 was not an independent outcome predictor. Adding S100 to the same model including neuron-specific enolase (NSE) did not further improve the AUC. CONCLUSIONS: The allocated target temperature did not affect S100 to a clinically relevant degree. High S100 values are predictive of poor outcome but do not add value to present prognostication models with or without NSE. S100 measured at 24 h and afterward is of limited value in clinical outcome prediction after OHCA. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT01020916 . Registered on 25 November 2009.