A novel predictor of unsustained return of spontaneous circulation in cardiac arrest patients through a combination of capnography and pulse oximetry: a multicenter observational study

BACKGROUND:Unsustained return of spontaneous circulation(ROSC)is a critical barrier to survival in cardiac arrest patients.This study examined whether end-tidal carbon dioxide(ETCO_(2))and pulse oximetry photoplethysmogram(POP)parameters can be used to identify unsustained ROSC.METHODS:We conducted a multicenter observational prospective cohort study of consecutive patients with cardiac arrest from 2013 to 2014.Patients’general information,ETCO_(2),and POP parameters were collected and statistically analyzed.RESULTS:The included 105 ROSC episodes(from 80 cardiac arrest patients)comprised 51 sustained ROSC episodes and 54 unsustained ROSC episodes.The 24-hour survival rate was significantly higher in the sustained ROSC group than in the unsustained ROSC group(29.2%vs.9.4%,P<0.05).The logistic regression analysis showed that the difference between after and before ROSC in ETCO_(2)(ΔETCO_(2))and the difference between after and before ROCS in area under the curve of POP(ΔAUCp)were independently associated with sustained ROSC(odds ratio[OR]=0.931,95%confi dence interval[95%CI]0.881-0.984,P=0.011 and OR=0.998,95%CI 0.997-0.999,P<0.001).The area under the receiver operating characteristic curve ofΔETCO_(2),ΔAUCp,and the combination of both to predict unsustained ROSC were 0.752(95%CI 0.660-0.844),0.883(95%CI 0.818-0.948),and 0.902(95%CI 0.842-0.962),respectively.CONCLUSION:Patients with unsustained ROSC have a poor prognosis.The combination ofΔETCO_(2) andΔAUCp showed signifi cant predictive value for unsustained ROSC.

Increased number of symptoms during the acute phase of SARS-CoV-2 infection in athletes is associated with prolonged time to return to full sports performance—AWAREⅧ

Purpose The aim of the study was to identify factors associated with prolonged time to return to full performance(RTFP)in athletes with recent severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)infection.Methods Prospective cohort study with cross sectional analysis.A total of 84 athletes with confirmed SARS-CoV-2 infection assessed at a coronavirus disease 2019 recovery clinic gave a history of age,sex,type/level of sport,co-morbidities,pre-infection training hours,and 26 acute SARS-CoV-2 symptoms from 3 categories(“nose and throat”,“chest and neck”,and“whole body”/systemic).Data on days to RTFP were obtained by structured interviews.Factors associated with RTFP were demographics,sport participation,history of co-morbidities,pre-infection training history,and acute symptoms(type,number).Outcomes were:(a)days to RTFP(median,interquartile range(IQR))in asymptomatic(n=7)and symptomatic athletes(n=77),and(b)hazard ratios(HRs;95%confidence interval)for symptomatic athletes with vs.without a factor(univariate,multiple models).HR<1 was predictive of higher percentage chance of prolonged RTFP.Significance was p<0.05.Results Days to RTFP were 30 days(IQR:23–40)for asymptomatic and 64 days(IQR:42–91)for symptomatic participants(p>0.05).Factors associated with prolonged RTFP(univariate models)were:females(HR=0.57;p=0.014),endurance athletes(HR=0.41;p<0.0001),co-morbidity number(HR=0.75;p=0.001),and respiratory disease history(HR=0.54;p=0.026).In symptomatic athletes,prolonged RTFP(multiple models)was significantly associated with increased“chest and neck”(HR=0.85;p=0.017)and“nose and throat”(HR=0.84;p=0.013)symptoms,but the association was more profound between prolonged RFTP and increased total number of“all symptoms”(HR=0.91;p=0.001)and“whole body”/systemic(HR=0.82;p=0.007)symptoms.Conclusion A larger number of total symptoms and specifically“whole body”/systemic symptoms during the acute phase of SARS-CoV-2 infection in athletes is associated with prolonged RTFP.

Gut microbiota affects the estrus return of sows by regulating the metabolism of sex steroid hormones

Background Sex hormones play important roles in the estrus return of post-weaning sows.Previous studies have demonstrated a complex and bi-directional regulation between sex hormones and gut microbiota.However,the extent to which the gut microbiota affects estrus return of post-weaning sows is largely unknown.Results In this study,we first screened 207 fecal samples from well-phenotyped sows by 16S rRNA gene sequencing and identified significant associations between microbes and estrus return of post-weaning sows.Using metagenomic sequencing data from 85 fecal samples,we identified 37 bacterial species that were significantly associated with estrus return.Normally returning sows were characterized by increased abundances of L.reuteri and P.copri and decreased abundances of B.fragilis,S.suis,and B.pseudolongum.The changes in gut microbial composition significantly altered the functional capacity of steroid hormone biosynthesis in the gut microbiome.The results were confirmed in a validation cohort.Significant changes in sex steroid hormones and related compounds were found between normal and non-return sows via metabolome analysis.An integrated analysis of differential bacterial species,metagenome,and fecal metabolome provided evidence that normal return-associated bacterial species L.reuteri and Prevotella spp.participated in the degradation of pregnenolone,progesterone,and testosterone,thereby promoting estrogen biosynthesis.Furthermore,the microbial metabolites related to sow energy and nutrient supply or metabolic disorders also showed relationships with sow estrus return.Conclusions An integrated analysis of differentially abundant bacterial species,metagenome,and fecal metabolome revealed the involvement of L.reuteri and Prevotella spp.in sow estrus return.These findings provide deep insight into the role of gut microbiota in the estrus return of post-weaning sows and the complex cross-talk between gut microbiota and sex hormones,suggesting that the manipulation of the gut microbiota could be an effective strategy to improve sow estrus return after weaning.

Early endotracheal intubation is not associated with the rate of return of spontaneous circulation following cardiac arrest at the emergency department:an exploratory analysis

Cardiac arrest poses a significant global public health challenge,manifesting in approximately 550,000 cases annually within the United States.[1]In-hospital cardiac arrest(IHCA)is commonly attributed to airways and respiratory issues.[2]Recommendations emphasize the expertise of responders in airway management.[3]Various options exist,such as chest compression-only cardiopulmonary resuscitation(CPR),bag-mask ventilation(BMV),and advanced airways.The BMV and advanced airways are not deemed equivalent or superior based on previous evidence.[4]Achieving consistency in choosing and timing the optimal airway approach during IHCA is crucial.The current American Heart Association guidelines suggest an advanced airway strategy when endotracheal intubation(ETI)success rates are high,but the optimal time for advanced airway management remains unclear.[5]Wong et al[6]revealed that survival improved by less than 5 min with advanced airway management.According to a subgroup analysis of IHCA patients in emergency departments(EDs),early intubation was associated with a 1.5-fold greater rate of return of spontaneous circulation(ROSC)than in other locations.[7]ED patients’constant monitoring and immediate management,with readily available intubation equipment,enhance early intubation and survival rates.[6]Nonetheless,IHCA patients intubated within the first 15 min had a lower ROSC rate.

Eight of ten patients return to daily activities, work, and sports after total knee arthroplasty

BACKGROUND Besides return to work(RTW)and return to sports(RTS),patients also prefer to return to daily activities(RTA)such as walking,sleeping,grocery shopping,and domestic work following total knee arthroplasty(TKA).However,evidence on the timelines and probability of patients’RTA is sparse.AIM To assess the percentage of patients able to RTA,RTW,and RTS after TKA,as well as the timeframe and influencing factors of this return.METHODS A retrospective cohort study with prospectively collected data was conducted at a medium-sized Dutch orthopedic hospital.Assessments of RTA,RTW,and RTS were performed at 3 mo and/or 6 mo following TKA.Investigated factors en-compassed patient characteristics,surgical characteristics,and preoperative patient-reported outcomes.RESULTS TKA patients[n=2063;66 years old(interquartile range[IQR]:7 years);47%male;28 kg/m2(IQR:4 kg/m2)]showed RTA ranging from 28%for kneeling to 94%for grocery shopping,with 20 d(IQR:27 d)spent for putting on shoes to 74 d(IQR:57 d)for kneeling.RTW rates varied from 62%for medium-impact work to 87%for low-impact work,taking 33 d(IQR:29 d)to 78 d(IQR:55 d).RTS ranged from 48%for medium-impact sports to 90%for low-impact sports,occurring within 43 d(IQR:24 d)to 90 d(IQR:60 d).One or more of the investigated factors influenced the return to each of the 14 activities examined,with R²values ranging from 0.013 to 0.127.CONCLUSION Approximately 80%of patients can RTA,RTW,and RTS within 6 mo after TKA.Return is not consistently in-fluenced by predictive factors.Results help set realistic pre-and postoperative expectations.

Fast solution to the free return orbit's reachable domain of the manned lunar mission by deep neural network

It is important to calculate the reachable domain(RD)of the manned lunar mission to evaluate whether a lunar landing site could be reached by the spacecraft. In this paper, the RD of free return orbits is quickly evaluated and calculated via the classification and regression neural networks. An efficient databasegeneration method is developed for obtaining eight types of free return orbits and then the RD is defined by the orbit’s inclination and right ascension of ascending node(RAAN) at the perilune. A classify neural network and a regression network are trained respectively. The former is built for classifying the type of the RD, and the latter is built for calculating the inclination and RAAN of the RD. The simulation results show that two neural networks are well trained. The classification model has an accuracy of more than 99% and the mean square error of the regression model is less than 0.01°on the test set. Moreover, a serial strategy is proposed to combine the two surrogate models and a recognition tool is built to evaluate whether a lunar site could be reached. The proposed deep learning method shows the superiority in computation efficiency compared with the traditional double two-body model.

Influencing Factors and Prediction of Risk of Returning to Ecological Poverty in Liupan Mountain Region,China

China has resolved its overall regional poverty in 2020 by attaining moderate societal prosperity.The country has entered a new development stage designed to achieve its second centenary goal.However,ecological fragility and risk susceptibility have increased the risk of returning to ecological poverty.In this paper,the Liupan Mountain Region of China was used as a case study,and the counties were used as the scale to reveal the spatiotempora differentiation and influcing factors of the risk of returning to poverty in study area.The indicator data for returning to ecological poverty from 2011-2020 were collected and summarized in three dimensions:ecological,economic and social.The autoregressive integrated moving average model(ARIMA)time series and exponential smoothing method(ES)were used to predict the multidimensional indicators of returning to ecological poverty for 61 counties(districts)in the Liupan Mountain Region for 2021-2030.The back propagation neural network(BPNN)and geographic information system(GIS)were used to generate the spatial distribution and time variation for the index of the risk of returning to ecological poverty(RREP index).The results show that 1)ecological factors were the main factors in the risk of returning to ecological poverty in Liupan Mountain Region.2)The RREP index for the 61 counties(districts)exhibited a downward trend from 2021-2030.The RREP index declined more in medium-and high-risk areas than in low-risk areas.From 2021 to 2025,the RREP index exhibited a slight downward trend.From 2026 to2030,the RREP index was expected to decline faster,especially from 2029-2030.3)Based on the RREP index,it can be roughly divided into three types,namely,the high-risk areas,the medium-risk areas,and the low-risk areas.The natural resource conditions in lowrisk areas of returning to ecological poverty,were better than those in medium-and high-risk areas.

Exploring influences and risk of bias of studies on return to sport and work after lateral ankle sprain:A systematic review and metaanalysis

BACKGROUND Lateral ankle sprains are the most common traumatic musculoskeletal injuries of the lower extremity,with an incidence rate of 15%-20%.The high incidence and prevalence highlights the economic impact of this injury.Ankle sprains lead to a high socioeconomic burden due to the combination of the high injury incidence and high medical expenses.Up to 40%of patients who suffer from an ankle sprain develop chronic ankle instability.Chronic instability can lead to prolonged periods of pain,immobility and injury recurrence.Identification of factors that influence return to work(RTW)and return to sports(RTS)after a lateral ankle sprain(LAS)may help seriously reduce healthcare costs.AIM To explore which factors may potentially affect RTW and RTS after sustaining an LAS.METHODS EMBASE and PubMed were systematically searched for relevant studies published until June 2023.Inclusion criteria were as follows:(1)Injury including LAS or chronic ankle instability;(2)Described any form of treatment;(3)Assessment of RTW or RTS;(4)Studies published in English;and(5)Study designs including randomized controlled clinical trials,clinical trials or cohort studies.Exclusion criteria were:(1)Studies involving children(age<16 year);or(2)Patients with concomitant ankle injury besides lateral ankle ligament damage.A quality assessment was performed for each of the included studies using established risk of bias tools.Additionally quality of evidence was assessed using the GRADEpro tool in cases where outcomes were included in the quantitative analysis.A best evidence synthesis was performed in cases of qualitative outcome analysis.For all studied outcomes suitable for quantitative analysis a forest plot was created to calculate the effect on RTW and RTS.RESULTS A total of 8904 patients were included in 21 studies,10 randomized controlled trials,7 retrospective cohort studies and 4 prospective cohort studies.Fifteen studies were eligible for meta-analysis.The overall RTS rate ranged were 80%and 83%in the all treatments pool and surgical treatments pool,respectively.The pooled mean days to RTS ranged from 23-93 d.The overall RTW rate was 89%.The pooled mean time to RTW ranged from 5.8-8.1 d.For patients with chronic ankle instability,higher preoperative motivation was the sole factor significantly and independently(P=0.001)associated with the rate of and time to RTS following ligament repair or reconstruction.Higher body mass index was identified as a significant factor(P=0.04)linked to not resuming sports or returning at a lower level(median 24,range 20-37),compared to those who resumed at the same or higher level(median 23,range 17-38).Patients with a history of psychological illness or brain injury,experienced a delay in their rehabilitation process for sprains with fractures and unspecified sprains.The extent of the delayed rehabilitation was directly proportional to the increased likelihood of experiencing a recurrence of the ankle sprain and the number of ankle-related medical visits.We also observed that 10%of athletes who did return to sport after lateral ankle sprain without fractures described non-ankle-related reasons for not returning.CONCLUSION All treatments yielded comparable results,with each treatment potentially offering unique advantages or benefits.Preoperative motivation may influence rehabilitation after LAS.Grading which factor had a greater impact was not possible due to the lack of comparability among the included patients.

Exploring the Relationship Between Patent Forward Citation and Stock Return Rate Using Empirical Data of China Stock Market

A novel indicator called price-citation was proposed.Based on the company integrated patent database of China listed companies of common stocks(A-shares)with the stock price and the stock return rate data,more than two thousand of A-shares from 2017 to 2020 were selected.The effect of the traditional patent forward citation and the price-citation for discriminating the stock return rate was thoroughly analyzed via ANOVA.The A-shares of forward citation counts above the average showed higher stock return rate means than the A-shares having patents but receiving no forward citations.The price-citation,combining both the financial and patent attributes,defined as the multiplication of the current stock price and the currently receiving forward citation count,showed its excellence in discriminating the stock return rate.The A-shares of higher price-citation showed significantly higher stock return rate means while the A-shares of lower price-citation showed significantly lowest stock return rate means.The price-citation effect had not been changed by COVID-19 though COVID-19 affected the social and economic environment to a considerable extent in 2020.

China's New Proposal of Returning Lost Cultural Objects Earns International Support Milestone in New Era

China launched a recommendation for the protection and return of cultural objects removed from colonial contexts or acquired by other unjustifiable or unethical means,winning a big applause from many countries which are seeking for more cooperation in solving this serious problem.

Analyzing the Impacts on East Asia of Trump’s Potential Return

The 2024 election is a pivotal and highly contested event in the United States.Donald Trump is expected to compete against Joe Biden without any doubts.A potential return of Trump to the White House would likely cause significant reactions in East Asia,particularly among the three major countries in the region.This analysis will explore the detailed implications of Trump’s return.

The Misdirection and Return of Graduate Course Teaching

Graduate course teaching plays an irreplaceable role in knowledge mastery,skill enhancement,and quality cultivation of graduate students.This paper addresses current issues in graduate course teaching,such as ambiguous objectives,formulaic content,formalistic operation,and oversimplified evaluation.It proposes corresponding solutions with the hope of steering graduate course teaching back to its original purpose and realizing its true significance.

Litter Productivity and Nutrient Return Characteristics of Three Typical Forest Stands in Golden Mountain

Objective: The paper aims to analyze the dynamic characteristics of litter production and nutrient return of the forest ecosystems in subtropical areas, and provide a theoretical basis for the nutrient cycling study in southwest Hubei Province and carbon sink function of the whole forest ecosystem. Methods: Three typical forest stands (Chinese fir plantation, Cryptomeria fortunei plantation and evergreen and deciduous broad-leaved mixed forest) in Golden Mountain Forest Farm in southwest Hubei Province were investigated and monitored continuously for the litter types and productivity and nutrient return. Results: The annual litter productivity of the three forest stands ranged from 161.77 to 396.26 kg·hm-2;Litters of branches, leaves and reproductive organs accounted for 14.14% - 20.85%, 33.26% - 78.33%, 7.52% - 42.18% of the total, respectively;The litter productivity and total litter productivity of each composition in the three forest stands show unimodal or bimodal changes over months, and the total litter productivity reached the highest value in January, April and October respectively. For different nutrient contents of the three forest stands, the common feature is C > N. The order of nutrient return amount from greatest to least is evergreen and deciduous broad-leaved mixed forest, Cryptomeria fortunei plantation and Chinese fir plantation. For different nutrient return amounts, the common feature is C > N, and the nutrient return amounts are 76.51-180.69 kg·hm-2 and 2.3 - 5.71 kg·hm-2 respectively. Conclusion: The annual litter productivity and nutrient return amount of the evergreen and deciduous broad-leaved mixed forest are the highest among the three forest stands. Therefore, protecting the evergreen and deciduous broad-leaved mixed forest and studying the litter changes of Chinese fir plantation and Cryptomeria fortunei plantation are of far-reaching significance for the development of sustainable forest management in this region and the further improvement of the carbon sequestration function of the whole forest ecosystem.

Straw return increases crop production by improving soil organic carbon sequestration and soil aggregation in a long-term wheat-cotton cropping system

Straw return is a promising strategy for managing soil organic carbon(SOC)and improving yield stability.However,the optimal straw return strategy for sustainable crop production in the wheat(Triticum aestivum L.)-cotton(Gossypium hirsutum L.)cropping system remains uncertain.The objective of this study was to quantify the long-term(10 years)impact of carbon(C)input on SOC sequestration,soil aggregation and crop yields in a wheat-cotton cropping system in the Yangtze River Valley,China.Five treatments were arranged with a single-factor randomized design as follows:no straw return(Control),return of wheat straw only(Wt),return of cotton straw only(Ct),return of 50%wheat and 50%cotton straw(Wh-Ch)and return of 100%wheat and 100%cotton straw(Wt-Ct).In comparison to the Control,the SOC content increased by 8.4 to 20.2%under straw return.A significant linear positive correlation between SOC sequestration and C input(1.42-7.19 Mg ha^(−1)yr^(−1))(P<0.05)was detected.The percentages of aggregates of sizes>2 and 1-2 mm at the 0-20 cm soil depth were also significantly elevated under straw return,with the greatest increase of the aggregate stability in the Wt-Ct treatment(28.1%).The average wheat yields increased by 12.4-36.0%and cotton yields increased by 29.4-73.7%,and significantly linear positive correlations were also detected between C input and the yields of wheat and cotton.The average sustainable yield index(SYI)reached a maximum value of 0.69 when the C input was 7.08 Mg ha^(−1)yr^(−1),which was close to the maximum value(SYI of 0.69,C input of 7.19 Mg ha^(−1)yr^(-1))in the Wt-Ct treatment.Overall,the return of both wheat and cotton straw was the best strategy for improving SOC sequestration,soil aggregation,yields and their sustainability in the wheat-cotton rotation system.

Effective Return Rate Prediction of Blockchain Financial Products Using Machine Learning

In recent times,financial globalization has drastically increased in different ways to improve the quality of services with advanced resources.The successful applications of bitcoin Blockchain(BC)techniques enable the stockholders to worry about the return and risk of financial products.The stockholders focused on the prediction of return rate and risk rate of financial products.Therefore,an automatic return rate bitcoin prediction model becomes essential for BC financial products.The newly designed machine learning(ML)and deep learning(DL)approaches pave the way for return rate predictive method.This study introduces a novel Jellyfish search optimization based extreme learning machine with autoencoder(JSO-ELMAE)for return rate prediction of BC financial products.The presented JSO-ELMAE model designs a new ELMAE model for predicting the return rate of financial products.Besides,the JSO algorithm is exploited to tune the parameters related to the ELMAE model which in turn boosts the classification results.The application of JSO technique assists in optimal parameter adjustment of the ELMAE model to predict the bitcoin return rates.The experimental validation of the JSO-ELMAE model was executed and the outcomes are inspected in many aspects.The experimental values demonstrated the enhanced performance of the JSO-ELMAE model over recent state of art approaches with minimal RMSE of 0.1562.

Robust monitoring machine:a machine learning solution for out‑of‑sample R_(2)‑hacking in return predictability monitoring

The out-of-sample R^(2) is designed to measure forecasting performance without look-ahead bias.However,researchers can hack this performance metric even without multiple tests by constructing a prediction model using the intuition derived from empirical properties that appear only in the test sample.Using ensemble machine learning techniques,we create a virtual environment that prevents researchers from peeking into the intuition in advance when performing out-of-sample prediction simulations.We apply this approach to robust monitoring,exploiting a dynamic shrink-age effect by switching between a proposed forecast and a benchmark.Considering stock return forecasting as an example,we show that the resulting robust monitoring forecast improves the average performance of the proposed forecast by 15%(in terms of mean-squared-error)and reduces the variance of its relative performance by 46%while avoiding the out-of-sample R^(2)-hacking problem.Our approach,as a final touch,can further enhance the performance and stability of forecasts from any models and methods.

MSCNN-LSTM Model for Predicting Return Loss of the UHF Antenna in HF-UHF RFID Tag Antenna

High-frequency(HF)and ultrahigh-frequency(UHF)dual-band radio frequency identification(RFID)tags with both near-field and farfield communication can meet different application scenarios.However,it is time-consuming to calculate the return loss of a UHF antenna in a dualband tag antenna using electromagnetic(EM)simulators.To overcome this,the present work proposes a model of a multi-scale convolutional neural network stacked with long and short-term memory(MSCNN-LSTM)for predicting the return loss of UHF antennas instead of EM simulators.In the proposed MSCNN-LSTM,the MSCNN has three branches,which include three convolution layers with different kernel sizes and numbers.Therefore,MSCNN can extract fine-grain localized information of the antenna and overall features.The LSTM can effectively learn the EM characteristics of different structures of the antenna to improve the prediction accuracy of the model.Experimental results show that the mean absolute error(0.0073),mean square error(0.00032),and root mean square error(0.01814)of theMSCNNLSTM are better than those of other prediction methods.In predicting the return loss of 100UHFantennas,compared with the simulation time of 4800 s for High Frequency Structure Simulator(HFSS),MSCNN-LSTM takes only 0.927519 s under the premise of ensuring prediction accuracy,significantly reducing the calculation time,which provides a basis for the rapid design of HF-UHF RFID tag antenna.ThenMSCNN-LSTM is used to determine the dimensions of the UHF antenna quickly.The return loss of the designed dualband RFID tag antenna is−58.76 and−22.63 dB at 13.56 and 915 MHz,respectively,achieving the desired goal.

A Critical Review of the Effects of Stock Returns and Market Timing on Capital Structure

Capital structure is regarded as the combination of debt and equity firms used to finance operations and investments.The choice of capital structure significantly impacts a company’s cost of capital,profitability,and risk profile.Among a series of factors that affect capital structure,this paper focuses on stock returns and market timing.In this review,an array of papers is analyzed to summarize what current research claims regarding the influence of stock returns and market timing on capital structure.This paper centers on the stock return and market timing theories and also discusses other theories like the trade-off theory,the pecking order theory,and the signaling theory.

A marathon,not a sprint:Increasing population physical activity as a legacy of sports mega-events

1.Legacy matters The withdrawal of Australia as hosts for the Commonwealth Games in 2026 demonstrates that large international sporting events are more than just sporting mastery,medals,and memories.Money also matters.1 The cost of hosting a major international tournament is eye-wateringly high.Host governments need to show that the billions of dollars of investment deliver a return beyond sporting glory to justify the resources that are spent.

Utilization of biomarkers for the prognostic prediction of cardiac arrest survivors using a multi-modal approach

International guidelines for post-cardiac arrest care recommend using multi-modal strategies to avoid the withdrawal of life-sustaining therapy(WLST)in patients with the potential for neurological recovery.[1]However,a clear methodology for multi-modal approaches has yet to be developed.Neuron-specific enolase(NSE)is currently the only recommended biomarker,and the European Resuscitation Council(ERC)and the European SocietyofIntensiveCareMedicine(ESICM)have proposed a cutoff value of 60μg/L at 48 and/or 72 h after the return of spontaneous circulation(ROSC)as a multimodal prognostic tool for predicting poor neurological outcomes.