Deep learning-enabled detection of hypoxic-ischemic encephalopathy after cardiac arrest in CT scans: a comparative study of 2D and 3D approaches.

Objective: To establish a deep learning model for the detection of hypoxic-ischemic encephalopathy (HIE) features on CT scans and to compare various networks to determine the best input data format. Methods: 168 head CT scans of patients after cardiac arrest were retrospectively identified and classified into two categories: 88 (52.4%) with radiological evidence of severe HIE and 80 (47.6%) without signs of HIE. These images were randomly divided into a training and a test set, and five deep learning models based on based on Densely Connected Convolutional Networks (DenseNet121) were trained and validated using different image input formats (2D and 3D images). Results: All optimized stacked 2D and 3D networks could detect signs of HIE. The networks based on the data as 2D image data stacks provided the best results (S100: AUC: 94%, ACC: 79%, S50: AUC: 93%, ACC: 79%). We provide visual explainability data for the decision making of our AI model using Gradient-weighted Class Activation Mapping. Conclusion: Our proof-of-concept deep learning model can accurately identify signs of HIE on CT images. Comparing different 2D- and 3D-based approaches, most promising results were achieved by 2D image stack models. After further clinical validation, a deep learning model of HIE detection based on CT images could be implemented in clinical routine and thus aid clinicians in characterizing imaging data and predicting outcome.

On the Electride Nature of Na-hP4.

Early quantum mechanical models suggested that pressure drives solids towards free-electron metal behavior where the ions are locked into simple close-packed structures. The prediction and subsequent discovery of high-pressure electrides (HPEs), compounds assuming open structures where the valence electrons are localized in interstitial voids, required a paradigm shift. Our quantum chemical calculations on the iconic insulating Na-hP4 HPE show that increasing density causes a 3s→3pd electronic transition due to Pauli repulsion between the 1s2s and 3s states, and orthogonality of the 3pd states to the core. The large lobes of the resulting Na-pd hybrid orbitals point towards the center of an 11-membered penta-capped trigonal prism and overlap constructively, forming multicentered bonds, which are responsible for the emergence of the interstitial charge localization in Na-hP4. These multicentered bonds facilitate the increased density of this phase, which is key for its stabilization under pressure.

Confounders for prognostic accuracy of neuron-specific enolase after cardiac arrest: A retrospective cohort study.

AIM: To evaluate neuron-specific enolase (NSE) thresholds for prediction of neurological outcome after cardiac arrest and to analyze the influence of hemolysis and confounders. METHODS: Retrospective analysis from a cardiac arrest registry. Determination of NSE serum concentration and hemolysis-index (h-index) 48-96 hours after cardiac arrest. Evaluation of neurological outcome using the Cerebral Performance Category score (CPC) at hospital discharge. Separate analyses considering CPC 1-3 and CPC 1-2 as good neurological outcome. Analysis of specificity and sensitivity for poor and good neurological outcome prediction with and without exclusion of hemolytic samples (h-index larger than 50). RESULTS: Among 356 survivors three days after cardiac arrest, hemolysis was detected in 28 samples (7.9%). At a threshold of 60 µg/L, NSE predicted poor neurological outcome (CPC 4-5) in all samples with a specificity of 92% (86-95%) and sensitivity of 73% (66-79%). In non-hemolytic samples, specificity was 94% (89-97%) and sensitivity 70% (62-76%). At a threshold of 100 µg/L, specificity was 98% (95-100%, all samples) and 99% (95-100%, non-hemolytic samples), and sensitivity 58% (51-65%) and 55% (47-63%), respectively. Possible confounders for elevated NSE in patients with good neurological outcome were ECMO, malignancies, blood transfusions and acute brain diseases. Nine patients with NSE below 17 µg/L had CPC 5, all had plausible death causes other than hypoxic-ischemic encephalopathy. CONCLUSIONS: NSE concentrations higher than 100 µg/L predicted poor neurological outcome with high specificity. An NSE less than 17 µg/L indicated absence of severe hypoxic-ischemic encephalopathy. Hemolysis and other confounders need to be considered. INSTITUTIONAL PROTOCOL NUMBER: The local ethics committee (board name: Ethikkommission der Charité) approved this study by the number: EA2/066/23, approval date: 28th June 2023, study title "'ROSC' - Resuscitation Outcome Study."

Cortical somatosensory evoked potential amplitudes and clinical outcome after cardiac arrest: a retrospective multicenter study.

OBJECTIVE: Bilaterally absent cortical somatosensory evoked potentials (SSEPs) reliably predict poor outcome in comatose cardiac arrest (CA) patients. Cortical SSEP amplitudes are a recent prognostic extension; however, amplitude thresholds, inter-recording, and inter-rater agreement remain uncertain. METHODS: In a retrospective multicenter cohort study, we determined cortical SSEP amplitudes of comatose CA patients using a standardized evaluation pathway. We studied inter-recording agreement in repeated SSEPs and inter-rater agreement by four raters independently determining 100 cortical SSEP amplitudes. Primary outcome was assessed using the cerebral performance category (CPC) upon intensive care unit discharge dichotomized into good (CPC 1-3) and poor outcome (CPC 4-5). RESULTS: Of 706 patients with SSEPs with median 3 days after CA, 277 (39.2%) had good and 429 (60.8%) poor outcome. Of patients with bilaterally absent cortical SSEPs, one (0.8%) survived with CPC 3 and 130 (99.2%) had poor outcome. Otherwise, the lowest cortical SSEP amplitude in good outcome patients was 0.5 µV. 184 (42.9%) of 429 poor outcome patients had lower cortical SSEP amplitudes. In 106 repeated SSEPs, there were 6 (5.7%) with prognostication-relevant changes in SSEP categories. Following a standardized evaluation pathway, inter-rater agreement was almost perfect with a Fleiss' kappa of 0.88. INTERPRETATION: Bilaterally absent and cortical SSEP amplitudes below 0.5 µV predicted poor outcome with high specificity. A standardized evaluation pathway provided high inter-rater and inter-recording agreement. Regain of consciousness in patients with bilaterally absent cortical SSEPs rarely occurs. High-amplitude cortical SSEP amplitudes likely indicate the absence of severe brain injury.

ReSurveyGermany: Vegetation-plot time-series over the past hundred years in Germany.

Vegetation-plot resurvey data are a main source of information on terrestrial biodiversity change, with records reaching back more than one century. Although more and more data from re-sampled plots have been published, there is not yet a comprehensive open-access dataset available for analysis. Here, we compiled and harmonised vegetation-plot resurvey data from Germany covering almost 100 years. We show the distribution of the plot data in space, time and across habitat types of the European Nature Information System (EUNIS). In addition, we include metadata on geographic location, plot size and vegetation structure. The data allow temporal biodiversity change to be assessed at the community scale, reaching back further into the past than most comparable data yet available. They also enable tracking changes in the incidence and distribution of individual species across Germany. In summary, the data come at a level of detail that holds promise for broadening our understanding of the mechanisms and drivers behind plant diversity change over the last century.

More losses than gains during one century of plant biodiversity change in Germany.

Long-term analyses of biodiversity data highlight a 'biodiversity conservation paradox': biological communities show substantial species turnover over the past century1,2, but changes in species richness are marginal1,3-5. Most studies, however, have focused only on the incidence of species, and have not considered changes in local abundance. Here we asked whether analysing changes in the cover of plant species could reveal previously unrecognized patterns of biodiversity change and provide insights into the underlying mechanisms. We compiled and analysed a dataset of 7,738 permanent and semi-permanent vegetation plots from Germany that were surveyed between 2 and 54 times from 1927 to 2020, in total comprising 1,794 species of vascular plants. We found that decrements in cover, averaged across all species and plots, occurred more often than increments; that the number of species that decreased in cover was higher than the number of species that increased; and that decrements were more equally distributed among losers than were gains among winners. Null model simulations confirmed that these trends do not emerge by chance, but are the consequence of species-specific negative effects of environmental changes. In the long run, these trends might result in substantial losses of species at both local and regional scales. Summarizing the changes by decade shows that the inequality in the mean change in species cover of losers and winners diverged as early as the 1960s. We conclude that changes in species cover in communities represent an important but understudied dimension of biodiversity change that should more routinely be considered in time-series analyses.

Inter-rater agreement between humans and computer in quantitative assessment of computed tomography after cardiac arrest.

Background: Head computed tomography (CT) is used to predict neurological outcome after cardiac arrest (CA). The current reference standard includes quantitative image analysis by a neuroradiologist to determine the Gray-White-Matter Ratio (GWR) which is calculated via the manual measurement of radiodensity in different brain regions. Recently, automated analysis methods have been introduced. There is limited data on the Inter-rater agreement of both methods. Methods: Three blinded human raters (neuroradiologist, neurologist, student) with different levels of clinical experience retrospectively assessed the Gray-White-Matter Ratio (GWR) in head CTs of 95 CA patients. GWR was also quantified by a recently published computer algorithm that uses coregistration with standardized brain spaces to identify regions of interest (ROIs). We calculated intraclass correlation (ICC) for inter-rater agreement between human and computer raters as well as area under the curve (AUC) and sensitivity/specificity for poor outcome prognostication. Results: Inter-rater agreement on GWR was very good (ICC 0.82-0.84) between all three human raters across different levels of expertise and between the computer algorithm and neuroradiologist (ICC 0.83; 95% CI 0.78-0.88). Despite high overall agreement, we observed considerable, clinically relevant deviations of GWR measurements (up to 0.24) in individual patients. In our cohort, at a GWR threshold of 1.10, this did not lead to any false poor neurological outcome prediction. Conclusion: Human and computer raters demonstrated high overall agreement in GWR determination in head CTs after CA. The clinically relevant deviations of GWR measurement in individual patients underscore the necessity of additional qualitative evaluation and integration of head CT findings into a multimodal approach to prognostication of neurological outcome after CA.

Neurological pupil index and its association with other prognostic tools after cardiac arrest: A post hoc analysis.

INTRODUCTION: We evaluated the concordance of the Neurological pupil Index (NPi) with other predictors of outcome after cardiac arrest (CA). METHODS: Post hoc analysis of a prospective, international, multicenter study including adult CA patients. Predictors of unfavorable outcome (UO, Cerebral Performance Category of 3-5 at 3 months) included: a) worst NPi ≤ 2; b) presence of discontinuous encephalography (EEG) background; c) bilateral absence of N20 waves on somatosensory evoked potentials (N20ABS); d) peak neuron-specific enolase (NSE) blood levels > 60 mcg/L; e) myoclonus, which were all tested in a subset of patients who underwent complete multimodal assessment (MMM). RESULTS: A total of 269/456 (59 %) patients had UO and 186 (41 %) underwent MMM. The presence of myoclonus was assessed in all patients, EEG in 358 (78 %), N20 in 186 (41 %) and NSE measurement in 228 (50 %). Patients with discontinuous EEG, N20ABS or high NSE had a higher proportion of worst NPi ≤ 2. The accuracy for NPi to predict a discontinuous EEG, N20ABS, high NSE and the presence of myoclonus was moderate. Concordance with NPi ≤ 2 was high for NSE, and moderate for discontinuous EEG and N20ABS. Also, the higher the number of concordant predictors of poor outcome, the lower the observed NPi. CONCLUSIONS: In this study, NPi ≤ 2 had moderate to high concordance with other unfavorable outcome prognosticators of hypoxic-ischemic brain injury. This indicates that NPi measurement could be considered as a valid tool for coma prognostication after cardiac arrest.

Proteomics-Based Serum Alterations of the Human Protein Expression after Out-of-Hospital Cardiac Arrest: Pilot Study for Prognostication of Survivors vs. Non-Survivors at Day 1 after Return of Spontaneous Circulation (ROSC).

BACKGROUND: Targeted temperature management (TTM) is considered standard therapy for patients after out-of-hospital cardiac arrest (OHCA), cardiopulmonary resuscitation (CPR), and return of spontaneous circulation (ROSC). To date, valid protein markers do not exist to prognosticate survivors and non-survivors before the end of TTM. The aim of this study is to identify specific protein patterns/arrays, which are useful for prediction in the very early phase after ROSC. MATERIAL AND METHODS: A total of 20 adult patients with ROSC (19 male, 1 female; 69.9 ± 9.5 years) were included and dichotomized in two groups (survivors and non-survivors at day 30). Serum samples were drawn at day 1 after ROSC (during TTM). Three panels (organ failure, metabolic, neurology, inflammation; OLINK, Uppsala, Sweden) were utilised. A total of four proteins were found to be differentially regulated (>2- or <-0.5-fold decrease; t-test). Bioinformatic platforms were utilised to analyse pathways and identify signalling cascades and to screen for potential biomarkers. RESULTS: A total of 276 proteins were analysed and revealed only 11 statistically significant protein alterations (Siglec-9, LAYN, SKR3, JAM-B, N2DL-2, TNF-B, BAMBI, NUCB2, STX8, PTK7, and PVLAB). Following the Bonferroni correction, no proteins were found to be regulated as statistically significant. Concerning the protein fold change for clinical significance, four proteins (IL-1 alpha, N-CDase, IL5, CRH) were found to be regulated in a clinically relevant context. CONCLUSIONS: Early analysis at 1 day after ROSC was not sufficiently possible during TTM to prognosticate survival or non-survival after OHCA. Future studies should evaluate protein expression later in the course after ROSC to identify promising protein candidates.

Electrolyte profiles with induced hypothermia: A sub study of a clinical trial evaluating the duration of hypothermia after cardiac arrest.

BACKGROUND: Electrolyte disturbances can result from targeted temperature treatment (TTM) in out-of-hospital cardiac arrest (OHCA) patients. This study explores electrolyte changes in blood and urine in OHCA patients treated with TTM. METHODS: This is a sub-study of the TTH48 trial, with the inclusion of 310 unconscious OHCA patients treated with TTM at 33°C for 24 or 48 h. Over a three-day period, serum concentrations were obtained on sodium potassium, chloride, ionized calcium, magnesium and phosphate, as were results from a 24-h diuresis and urine electrolyte concentration and excretion. Changes over time were analysed with a mixed-model multivariate analysis of variance with repeated measurements. RESULTS: On admission, mean ± SD sodium concentration was 138 ± 3.5 mmol/l, which increased slightly but significantly (p < .05) during the first 24 h. Magnesium concentration stayed within the reference interval. Median ionized calcium concentration increased from 1.11 (IQR 1.1-1.2) mmol/l during the first 24 h (p < .05), whereas median phosphate concentration dropped to 1.02 (IQR 0.8-1.2) mmol/l (p < .05) and stayed low. During rewarming, potassium concentrations increased, and magnesium and ionizes calcium concentration decreased (p < .05). Median 24-h diuresis results on days one and two were 2198 and 2048 ml respectively, and the electrolyte excretion mostly stayed low in the reference interval. CONCLUSIONS: Electrolytes mostly remained within the reference interval. A temporal change occurred in potassium, magnesium and calcium concentrations with TTM's different phases. No hypothermia effect on diuresis was detected, and urine excretion of electrolytes mostly stayed low.

Computational signatures for post-cardiac arrest trajectory prediction: Importance of early physiological time series.

BACKGROUND: There is an unmet need for timely and reliable prediction of post-cardiac arrest (CA) clinical trajectories. We hypothesized that physiological time series (PTS) data recorded on the first day of intensive care would contribute significantly to discrimination of outcomes at discharge. PATIENTS AND METHODS: Adult patients in the multicenter eICU database who were mechanically ventilated after resuscitation from out-of-hospital CA were included. Outcomes of interest were survival, neurological status based on Glasgow motor subscore (mGCS) and surrogate functional status based on discharge location (DL), at hospital discharge. Three machine learning predictive models were trained, one with features from the electronic health records (EHR), the second using features derived from PTS collected in the first 24 h after ICU admission (PTS24), and the third combining PTS24 and EHR. Model performances were compared, and the best performing model was externally validated in the MIMIC-III dataset. RESULTS: Data from 2216 admissions were included in the analysis. Discrimination of prediction models combining EHR and PTS24 features was higher than models using either EHR or PTS24 for prediction of survival (AUROC 0.83, 0.82 and 0.79 respectively), neurological outcome (0.87, 0.86 and 0.79 respectively), and DL (0.80, 0.78 and 0.76 respectively). External validation in MIMIC-III (n = 86) produced similar model performance. Feature analysis suggested prognostic significance of previously unknown EHR and PTS24 variables. CONCLUSION: These results indicate that physiological data recorded in the early phase after CA resuscitation contain signatures that are linked to post-CA outcome. Additionally, they attest to the effectiveness of ML for post-CA predictive modeling.

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.

Automated Assessment of Brain CT After Cardiac Arrest-An Observational Derivation/Validation Cohort Study.

OBJECTIVES: Prognostication of outcome is an essential step in defining therapeutic goals after cardiac arrest. Gray-white-matter ratio obtained from brain CT can predict poor outcome. However, manual placement of regions of interest is a potential source of error and interrater variability. Our objective was to assess the performance of poor outcome prediction by automated quantification of changes in brain CTs after cardiac arrest. DESIGN: Observational, derivation/validation cohort study design. Outcome was determined using the Cerebral Performance Category upon hospital discharge. Poor outcome was defined as death or unresponsive wakefulness syndrome/coma. CTs were automatically decomposed using coregistration with a brain atlas. SETTING: ICUs at a large, academic hospital with circulatory arrest center. PATIENTS: We identified 433 cardiac arrest patients from a large previously established database with brain CTs within 10 days after cardiac arrest. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Five hundred sixteen brain CTs were evaluated (derivation cohort n = 309, validation cohort n = 207). Patients with poor outcome had significantly lower radiodensities in gray matter regions. Automated GWR_si (putamen/posterior limb of internal capsule) was performed with an area under the curve of 0.86 (95%-CI: 0.80-0.93) for CTs taken later than 24 hours after cardiac arrest (similar performance in the validation cohort). Poor outcome (Cerebral Performance Category 4-5) was predicted with a specificity of 100% (95% CI, 87-100%, derivation; 88-100%, validation) at a threshold of less than 1.10 and a sensitivity of 49% (95% CI, 36-58%, derivation) and 38% (95% CI, 27-50%, validation) for CTs later than 24 hours after cardiac arrest. Sensitivity and area under the curve were lower for CTs performed within 24 hours after cardiac arrest. CONCLUSIONS: Automated gray-white-matter ratio from brain CT is a promising tool for prediction of poor neurologic outcome after cardiac arrest with high specificity and low-to-moderate sensitivity. Prediction by gray-white-matter ratio at the basal ganglia level performed best. Sensitivity increased considerably for CTs performed later than 24 hours after cardiac arrest.

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

OBJECTIVES: Data on cardiac arrest survivors from developing countries are scarce. This study investigated clinical characteristics associated with in-hospital mortality in resuscitated patients following cardiac arrest in Brazil. DESIGN: Retrospective analysis of prospectively collected data. SETTING: Ninety-two general ICUs from 55 hospitals in Brazil between 2014 and 2015. PATIENTS: Adult patients with cardiac arrest admitted to the ICU. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We analyzed 2,296 patients (53% men; median 67 yr (interquartile range, 54-79 yr]). Eight-hundred patients (35%) had a primary admission diagnosis of cardiac arrest suggesting an out-of-hospital cardiac arrest; the remainder occurred after admission, comprising an in-hospital cardiac arrest cohort. Overall, in-hospital mortality was 83%, with only 6% undergoing withholding/withdrawal-of-life support. Random-effects multivariable Cox regression was used to assess associations with survival. After adjusting for age, sex, and severity scores, mortality was associated with shock (adjusted odds ratio, 1.25 [95% CI, 1.11-1.39]; p < 0.001), temperature dysregulation (adjusted odds ratio for normothermia, 0.85 [95% CI, 0.76-0.95]; p = 0.007), increased lactate levels above 4 mmol/L (adjusted odds ratio, 1.33 [95% CI, 1.1-1.6; p = 0.009), and surgical or cardiac cases (adjusted odds ratio, 0.72 [95% CI, 0.6-0.86]; p = 0.002). In addition, survival was better in patients with probable out-of-hospital cardiac arrest, unless ICU admission was delayed (adjusted odds ratio for interaction, 1.63 [95% CI, 1.21-2.21]; p = 004). CONCLUSIONS: In a large multicenter cardiac arrest cohort from Brazil, we found a high mortality rate and infrequent withholding/withdrawal of life support. We also identified patient profiles associated with worse survival, such as those with shock/hypoperfusion and arrest secondary to nonsurgical admission diagnoses. Our findings unveil opportunities to improve postarrest care in developing countries, such as prompt ICU admission, expansion of the use of targeted temperature management, and implementation of shock reversal strategies (i.e., early coronary angiography), according to modern guidelines recommendations.

Factors Associated With Rebound Hyperthermia After Targeted Temperature Management in Out-of-Hospital Cardiac Arrest Patients: An Explorative Substudy of the Time-Differentiated Therapeutic Hypothermia in Out-of-Hospital Cardiac Arrest Survivors Trial.

To investigate rebound hyperthermia following targeted temperature management after cardiac arrest and its impact on functional outcome. DESIGN: Post hoc analysis. SETTING: Ten European ICUs. PATIENTS: Patients included in the time-differentiated therapeutic hypothermia in out-of-hospital cardiac arrest survivors trial treated with targeted temperature management at 33°C for 48 or 24 hours. Favorable functional outcome was defined as a Cerebral Performance Category of 1 or 2 at 6 months. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of 338 included patients, 103 (30%) experienced rebound hyperthermia defined as a maximum temperature after targeted temperature management and rewarming exceeding 38.5°C. Using multivariate logistic regression analysis, increasing age (odds ratio, 0.97; 95% CI, 0.95-0.99; p = 0.02) and severe acute kidney injury within 72 hours of ICU admission (odds ratio, 0.35; 95% CI, 0.13-0.91; p = 0.03) were associated with less rebound hyperthermia, whereas male gender (odds ratio, 3.94; 95% CI, 1.34-11.57; p = 0.01), highest C-reactive protein value (odds ratio, 1.04; 95% CI, 1.01-1.07; p = 0.02), and use of mechanical chest compression during cardiopulmonary resuscitation (odds ratio, 2.00; 95% CI, 1.10-3.67; p = 0.02) were associated with more rebound hyperthermia. Patients with favorable functional outcome spent less time after rewarming over 38.5°C (2.5% vs 6.3%; p = 0.03), 39°C (0.14% vs 2.7%; p < 0.01), and 39.5°C (0.03% vs 0.71%; p < 0.01) when compared with others. Median time to rebound hyperthermia was longer in the unfavorable functional outcome group (33.2 hr; interquartile range, 14.3-53.0 hr vs 6.5 hr; interquartile range, 2.2-34.1; p < 0.01). In a predefined multivariate binary logistic regression model, rebound hyperthermia was associated with decreased odds of favorable functional outcome (odds ratio, 0.42; 95% CI, 0.22-0.79). CONCLUSIONS: One-third of targeted temperature management patients experience rebound hyperthermia, and it is more common in younger male patients with an aggravated inflammatory response and those treated with a mechanical chest compression device. Later onset of rebound hyperthermia and temperatures exceeding 38.5°C associate with unfavorable outcome.

Is the routine use of antipseudomonal antibiotics in acutely exacerbated COPD patients indicated: A retrospective analysis in 437 ICU patients.

PURPOSE: Chronic obstructive pulmonary disease (COPD) is a risk factor for acquiring multiple drug resistant bacteria. The main objective of this analysis was to question a beneficial outcome in the routine use of antipseudomonal antibiotics in the empiric treatment of severe AECOPD in Intensive Care Unit patients. MATERIAL AND METHODS: We report a retrospective, observational cohort study in adult patients with severe AECOPD admitted to ICU at a tertiary care university hospital. Antibiotic treatment on admission as well as microbiology samples were analyzed. The influence of SOFA score at admission, age, sex and antibiotic choice upon survival was investigated by multivariable analysis. RESULTS: 437 patients were included. Mean age was 68 years (±10), 46.5% were female. 271/437 patients (62%) were initially treated with antibiotics covering Pseudomonas aeruginosa. Overall, positive microbiology samples were found in 107 patients (24.5%). P. aeruginosa was only found in 3.7%. There was no significant difference in 30-day ICU mortality after adjusting for age, sex and severity of illness (20.4% ± 11.6 in patients with Pseudomonas inactive antibiotics versus 29.3% ± 10.8 in patients with PAA, p=0.113). CONCLUSIONS: Empiric use of antipseudomonal antibiotics did not result in improved ICU survival in this retrospective analysis.

Hypothermia versus Normothermia after Out-of-Hospital Cardiac Arrest.

BACKGROUND: Targeted temperature management is recommended for patients after cardiac arrest, but the supporting evidence is of low certainty. METHODS: In an open-label trial with blinded assessment of outcomes, we randomly assigned 1900 adults with coma who had had an out-of-hospital cardiac arrest of presumed cardiac or unknown cause to undergo targeted hypothermia at 33°C, followed by controlled rewarming, or targeted normothermia with early treatment of fever (body temperature, ≥37.8°C). The primary outcome was death from any cause at 6 months. Secondary outcomes included functional outcome at 6 months as assessed with the modified Rankin scale. Prespecified subgroups were defined according to sex, age, initial cardiac rhythm, time to return of spontaneous circulation, and presence or absence of shock on admission. Prespecified adverse events were pneumonia, sepsis, bleeding, arrhythmia resulting in hemodynamic compromise, and skin complications related to the temperature management device. RESULTS: A total of 1850 patients were evaluated for the primary outcome. At 6 months, 465 of 925 patients (50%) in the hypothermia group had died, as compared with 446 of 925 (48%) in the normothermia group (relative risk with hypothermia, 1.04; 95% confidence interval [CI], 0.94 to 1.14; P = 0.37). Of the 1747 patients in whom the functional outcome was assessed, 488 of 881 (55%) in the hypothermia group had moderately severe disability or worse (modified Rankin scale score ≥4), as compared with 479 of 866 (55%) in the normothermia group (relative risk with hypothermia, 1.00; 95% CI, 0.92 to 1.09). Outcomes were consistent in the prespecified subgroups. Arrhythmia resulting in hemodynamic compromise was more common in the hypothermia group than in the normothermia group (24% vs. 17%, P<0.001). The incidence of other adverse events did not differ significantly between the two groups. CONCLUSIONS: In patients with coma after out-of-hospital cardiac arrest, targeted hypothermia did not lead to a lower incidence of death by 6 months than targeted normothermia. (Funded by the Swedish Research Council and others; TTM2 ClinicalTrials.gov number, NCT02908308.).

Quality of targeted temperature management and outcome of out-of-hospital cardiac arrest patients: A post hoc analysis of the TTH48 study.

BACKGROUND: No data are available on the quality of targeted temperature management (TTM) provided to out-of-hospital cardiac arrest (OHCA) patients and its association with outcome. METHODS: Post hoc analysis of the TTH48 study (NCT01689077), which compared the effects of prolonged TTM at 33 °C for 48 h to standard 24-h TTM on neurologic outcome. Admission temperature, speed of cooling, rewarming rates, precision (i.e. temperature variability), overcooling and overshooting as post-cooling fever (i.e. >38.0 °C) were collected. A specific score, ranging from 1 to 9, was computed to define the "quality of TTM". RESULTS: On a total of 352 patients, most had a moderate quality of TTM (n = 217; 62% - score 4-6), while 80 (23%) patients had a low quality of TTM (score 1-3) and only 52 (16%) a high quality of TTM (score 7-9). The proportion of patients with unfavorable neurological outcome (UO; Cerebral Performance Category of 3-5 at 6 months) was similar between the different quality of TTM groups (p = 0.90). Although a shorter time from arrest to target temperature and a lower proportion of time outside the target ranges in the TTM 48-h than in the TTM 24-h group, quality of TTM was similar between groups. Also, the proportion of patients with UO was similar between the different quality of TTM groups when TTM 48-h and TTM 24-h were compared. CONCLUSIONS: In this study, high quality of TTM was provided to a small proportion of patients. However, quality of TTM was not associated with patients' outcome.

Measuring Core Body Temperature Using a Non-invasive, Disposable Double-Sensor During Targeted Temperature Management in Post-cardiac Arrest Patients.

Background: Precisely measuring the core body temperature during targeted temperature management after return of spontaneous circulation is mandatory, as deviations from the recommended temperature might result in side effects such as electrolyte imbalances or infections. However, previous methods are invasive and lack easy handling. A disposable, non-invasive temperature sensor using the heat flux approach (Double Sensor), was tested against the standard method: an esophagus thermometer. Methods: The sensor was placed on the forehead of adult patients (n = 25, M/F, median age 61 years) with return of spontaneous circulation after cardiac arrest undergoing targeted temperature management. The recorded temperatures were compared to the established measurement method of an esophageal thermometer. A paired t-test was performed to examine differences between methods. A Bland-Altman-Plot and the intraclass correlation coefficient were used to assess agreement and reliability. To rule out possible influence on measurements, the patients' medication was recorded as well. Results: Over the span of 1 year and 3 months, data from 25 patients were recorded. The t-test showed no significant difference between the two measuring methods (t = 1.47, p = 0.14, n = 1,319). Bland-Altman results showed a mean bias of 0.02°C (95% confidence interval 0.00-0.04) and 95% limits of agreement of -1.023°C and 1.066°C. The intraclass correlation coefficient was 0.94. No skin irritation or allergic reaction was observed where the sensor was placed. In six patients the bias differed noticeably from the rest of the participants, but no sex-based or ethnicity-based differences could be identified. Influences on the measurements of the Double Sensor by drugs administered could also be ruled out. Conclusions: This study could demonstrate that measuring the core body temperature with the non-invasive, disposable sensor shows excellent reliability during targeted temperature management after survived cardiac arrest. Nonetheless, clinical research concerning the implementation of the sensor in other fields of application should be supported, as well as verifying our results by a larger patient cohort to possibly improve the limits of agreement.

Prognostic value of 'late' electroencephalography recordings in patients with cardiopulmonal resuscitation after cardiac arrest.

BACKGROUND: Electroencephalography (EEG) significantly contributes to the neuroprognostication after resuscitation from cardiac arrest. Recent studies suggest that the prognostic value of EEG is highest for continuous recording within the first days after cardiac arrest. Early continuous EEG, however, is not available in all hospitals. In this observational study, we sought to evaluate the predictive value of a 'late' EEG recording 5-14 days after cardiac arrest without sedatives. METHODS: We retrospectively analyzed EEG data in consecutive adult patients treated at the medical intensive care units (ICU) of the Charité-Universitätsmedizin Berlin. Outcome was assessed as cerebral performance category (CPC) at discharge from ICU, with an unfavorable outcome being defined as CPC 4 and 5. RESULTS: In 187 patients, a 'late' EEG recording was performed. Of these patients, 127 were without continuous administration of sedative agents for at least 24 h before the EEG recording. In this patient group, a continuously suppressed background activity < 10 µV predicted an unfavorable outcome with a sensitivity of 31% (95% confidence interval (CI) 20-45) and a specificity of 99% (95% CI 91-100). In patients with suppressed background activity and generalized periodic discharges, sensitivity was 15% (95% CI 7-27) and specificity was 100% (95% CI 94-100). GPDs on unsuppressed background activity were associated with a sensitivity of 42% (95% CI 29-46) and a specificity of 92% (95% CI 82-97). CONCLUSIONS: A 'late' EEG performed 5 to 14 days after resuscitation from cardiac arrest can aide in prognosticating functional outcome. A suppressed EEG background activity in this time period indicates poor outcome.