Serum Neutrophil Gelatinase-Associated Lipocalin Predicts Survival After Resuscitation From Cardiac Arrest

Common Data Elements for Disorders of Consciousness: Recommendations from the Working Group on Biospecimens and Biomarkers

BACKGROUND

In patients with disorders of consciousness (DoC), laboratory and molecular biomarkers may help define endotypes, identify therapeutic targets, prognosticate outcomes, and guide patient selection in clinical trials. We performed a systematic review to identify common data elements (CDEs) and key design elements (KDEs) for future coma and DoC research.

METHODS

The Curing Coma Campaign Biospecimens and Biomarkers work group, composed of seven invited members, reviewed existing biomarker and biospecimens CDEs and conducted a systematic literature review for laboratory and molecular biomarkers using predetermined search words and standardized methodology. Identified CDEs and KDEs were adjudicated into core, basic, supplemental, or experimental CDEs per National Institutes of Health classification based on level of evidence, reproducibility, and generalizability across different diseases through a consensus process.

RESULTS

Among existing National Institutes of Health CDEs, those developed for ischemic stroke, traumatic brain injury, and subarachnoid hemorrhage were most relevant to DoC and included. KDEs were common to all disease states and included biospecimen collection time points, baseline indicator, biological source, anatomical location of collection, collection method, and processing and storage methodology. Additionally, two disease core, nine basic, 24 supplemental, and 59 exploratory biomarker CDEs were identified. Results were summarized and generated into a Laboratory Data and Biospecimens Case Report Form (CRF) and underwent public review. A final CRF version 1.0 is reported here.

CONCLUSIONS

Exponential growth in biomarkers development has generated a growing number of potential experimental biomarkers associated with DoC, but few meet the quality, reproducibility, and generalizability criteria to be classified as core and basic biomarker and biospecimen CDEs. Identification and adaptation of KDEs, however, contribute to standardizing methodology to promote harmonization of future biomarker and biospecimens studies in DoC. Development of this CRF serves as a basic building block for future DoC studies.

Predictive Performance of Neuron-Specific Enolase (NSE) for Survival after Resuscitation from Cardiac Arrest: A Systematic Review and Meta-Analysis

The prediction of outcomes following cardiac arrest continues to provide significant difficulties. A preferred strategy involves adopting a multimodal approach, which encompasses the careful evaluation of the biomarker neuron-specific enolase (NSE). This systematic review and meta-analysis aimed to gather and summarize new and existing evidence on the prediction effect of neuron-specific enolase for survival to hospital discharge among adult patients with cardiac arrest. We searched PubMed Central, Scopus, EMBASE databases, and the Cochrane Library without language restrictions from their inceptions until 30 October 2023 and checked the reference lists of the included studies. Pooled results were reported as standardized mean differences (SMDs) and were presented with corresponding 95% confidence intervals (CIs). The primary outcome was survival to hospital discharge (SHD). Eighty-six articles with 10,845 participants were included. NSE showed a notable degree of specificity in its ability to predict mortality as well as neurological status among individuals who experienced cardiac arrest (p < 0.05). This study demonstrates the ability to predict fatality rates and neurological outcomes, both during the time of admission and at various time intervals after cardiac arrest. The use of NSE in a multimodal neuroprognostication algorithm has promise in improving the accuracy of prognoses for persons who have undergone cardiac arrest.

Kidney-specific biomarkers for predicting acute kidney injury following cardiac arrest

AIM

To evaluate the performance of kidney-specific biomarkers (neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), and cystatin-C) in early detection of acute kidney injury (AKI) following cardiac arrest (CA) when compared to serum creatinine.

METHODS

Adult CA patients who had kidney-specific biomarkers of AKI collected within 12 h of return of spontaneous circulation (ROSC) were included. The association between renal biomarker levels post-ROSC and the development of KDIGO stage III AKI within 7 days of enrollment were assessed as well as their predictive value of future AKI development, neurological outcomes, and survival to discharge.

RESULTS

Of 153 patients, 54 (35%) developed stage III AKI within 7 days, and 98 (64%) died prior to hospital discharge. Patients who developed stage III AKI, compared to those who did not, had higher median levels of creatinine, NGAL, and cystatin-C (p < 0.001 for all). There was no statistically significant difference in KIM-1 between groups. No biomarker outperformed creatinine in the ability to predict stage III AKI, neurological outcomes, or survival outcomes (p > 0.05 for all). However, NGAL, cystatin-C, and creatinine all performed better than KIM-1 in their ability to predict AKI development (p < 0.01 for all).

CONCLUSION

In post-CA patients, creatinine, NGAL, and cystatin-C (but not KIM-1) measured shortly after ROSC were higher in patients who subsequently developed AKI. No biomarker was statistically superior to creatinine on its own for predicting the development of post-arrest AKI.

Association Between Procalcitonin Level at 72 Hours After Cardiac Arrest and Neurological Outcomes in Cardiac Arrest Survivors

The association between procalcitonin (PCT) level measured 72 hours after cardiac arrest (CA) and neurological outcomes is unknown. We aimed to examine the association of serial PCT levels up to 72 hours with neurological outcomes in patients who underwent targeted temperature management (TTM) after CA. This retrospective observational study included adult comatose patients with CA undergoing TTM (33℃ for 24 hours) at the Chonnam National University Hospital in Gwangju, Korea, between January 2018 and December 2020. PCT levels were measured at admission and at 24, 48, and 72 hours after CA. The presence of early-onset infections (within 7 days after CA) was confirmed by reviewing clinical, radiological, and microbiological data. The primary outcome was poor neurological outcomes at 6 months and was defined by cerebral performance category 3-5. Among the CA survivors, 118 were included and 67 (56.8%) had poor neurological outcomes. The PCT level at 72 hours in the poor outcome group (3.01 [0.88-12.71]) was higher than that in good outcome group (0.56 [0.18-1.32]). The multivariate analysis revealed that the PCT level at 72 hours (adjusted odds ratio 1.241; 95% confidence interval, 1.059-1.455) was independently associated with poor neurological outcomes, showed good performance for poor outcomes (area under the receiver operating characteristic curve of 0.823), and was not associated with early-onset infections. The PCT level at 72 hours after CA can be helpful in predicting prognosis, and it did not correlate with early-onset infections in the study.

Admission biomarkers among patients with acute myocardial-infarction related cardiogenic shock with or without out-of-hospital cardiac arrest an exploratory study

BACKGROUND

Acute myocardial infarction complicated by cardiogenic shock (AMICS) with or without out-of-hospital cardiac arrest (OHCA) have some pathophysiological differences and could potentially be considered as two individual clinical entities. Thus, there may also be differences in terms of blood borne biomarkers.

PURPOSE

To explore potential differences in concentrations of the biomarkers lactate, mid-regional proadrenomedullin (MRproADM), Copeptin, pro-atrial natriuretic peptide (proANP), Syndecan-1, soluble thrombomodulin (sTM), soluble suppression of tumorigenicity 2 (sST2) and neutrophil gelatinase-associated lipocalin (NGAL), in patients with AMICS with or without OHCA.

METHOD

Patients admitted for acute coronary angiography due to suspected ST-elevation myocardial infarction were enrolled during a 1-year period. In the present study 86 patients with confirmed AMICS at admission were included.

RESULTS

In the adjusted analysis OHCA patients had higher levels of lactate (p = 0.008), NGAL (p = 0.03) and sTM (p = 0.011) while the level of sST2 was lower (p = 0.029). There was little difference in 30-day mortality between the OHCA and non-OHCA groups (OHCA 37% vs. non-OHCA 38%).

CONCLUSION

AMICS patients with or without OHCA had similar 30-day mortality but differed in terms of Lactate, NGAL, sTM and sST2 levels. These findings support that non-OHCA and OHCA patients with CS could be considered as two individual clinical entities.

Urinary neutrophil gelatinase-associated lipocalin was a predictor from the day after intensive care unit entry, but not on the day of intensive care unit entry

BACKGROUND AND AIMS

Sepsis is the main cause of death from infection. This study aimed to determine whether neutrophil gelatinase-associated lipocalin (NGAL) values better predict mortality in septic patients when combined with inflammation-based prognostic scores.

MATERIAL AND METHODS

Forty-four adult patients diagnosed according to the Sepsis-3 definition and who were admitted to the ICU were prospectively examined from June 2018 to November 2018. Urine samples were collected from each patient with a urethral balloon bag to measure NGAL after ICU entry at the following time points: immediately after and 2, 3, and 4 days after ICU entry. The Glasgow Prognostic Score, the neutrophil to lymphocyte ratio (NLR), the platelet to lymphocyte ratio, the Prognostic Nutritional Index, the Prognostic Index (PI), the Sequential Organ Failure Assessment (SOFA), and quick SOFA were examined immediately after ICU entry. Predictors of mortality were assessed by receiver operating characteristics curve (ROC) analysis, log-rank test, and multivariate logistic regression analysis.

RESULTS

NGAL on day 4 (AUC: 0.94) and ΔNGAL from day 4 to day 1 (AUC: 0.9) for 28-day mortality; NGAL on day 4 (AUC: 0.94) and inflammation-NGAL score (iNS) NGAL-PI (AUC: 0.69) for 60-day mortality; ΔNGAL from day 3 to day 1 (AUC: 0.82) for 90-day mortality; and iNS NGAL-NLR (AUC: 0.71) and iNS NGAL-PI (AUC: 0.68) for in-hospital mortality were found to be predictors of mortality by ROC curve analysis. NLR (p = 0.02) for 28-day mortality; NGAL on day 2 (p = 0.031), ΔNGAL from day 2 to day 1 (p = 0.013), and NLR (p < 0.0001) for 60-day mortality; NGAL on day 2 (p = 0.017), ΔNGAL from day 2 to day 1 (p = 0.014), and NLR (p = 0.033) for 90-day mortality; and NGAL on day 2 (p = 0.007) for in-hospital mortality were found to be predictors of mortality by log-rank test. iNS NGAL-NLR (OR, 0.024; p = 0.019) for 60-day mortality and NGAL from day 3 to day 1 (OR, 1.005; p = 0.013) for 90-day mortality were found to be predictors of mortality by multivariate logistic regression analysis.

CONCLUSIONS

NGAL and ΔNGAL were predictors of mortality in sepsis patients on day 2 after ICU entry and thereafter, but not on day 1.

Plasma Adipokines in Patients Resuscitated from Cardiac Arrest: Difference of Visfatin between Survivors and Nonsurvivors

Background

Adipokines are a group of cytokines or peptides secreted by adipose tissue to exert numerous biological functions. In the present study, we measured the plasma levels of four adipokines (adiponectin, leptin, fatty acid-binding protein 4 (FABP4), and visfatin) in cardiac arrest patients following return of spontaneous circulation (ROSC).

Methods

Totally, 21 patients who experienced cardiac arrest and successful ROSC with expected survival of at least 48 hours (from January 2016 to December 2017) were consecutively enrolled into this prospective observational clinical study. Of the 21 enrolled patients, ten survived, and other eleven died between 2 days and 6 months post ROSC. Venous blood was drawn at three time points: baseline (<1 hour post ROSC), 2 days post ROSC, and 7 days post ROSC. Plasma concentrations of adiponectin, leptin, FABP4, and visfatin were determined using commercial enzyme-linked immunosorbent assays.

Results

The plasma visfatin levels at 2 or 7 days post ROSC increased significantly compared with the baseline (P < 0.01), while plasma levels of adiponectin, leptin, and FABP4 did not change. Moreover, plasma visfatin levels in survivors at 2 or 7 days post ROSC were higher than those in nonsurvivors (P < 0.01). Plasma visfatin levels at 2 or 7 days post ROSC were negatively correlated with Acute Physiology and Chronic Health Evaluation (APACHE) II score and time to ROSC. Moreover, receiver operating characteristic curve analysis showed that the plasma visfatin levels at 2 or 7 days post ROSC were good predictors for survival of the patients.

Conclusion

Elevated plasma visfatin levels may be a marker for better outcome of cardiac arrest patients post ROSC.

Determination of Cut-off Serum Values for Resistin and S100B Protein in Patients Who Survived a Cardiac Arrest

Introduction

In an attempt to identify patients who have successfully survived a resuscitated cardiac arrest (CA), attention is drawn to resistin and S100B protein, two biomarkers that have been studied in relation to CA.

Aim

The study aimed to identify the potential cut-off serum values for resistin and S100B in patients who had CA, compared to healthy volunteers, given that, currently, none of the markers have normal and pathological reference range limits for human assay levels related to this pathology.

Materials and Methods

Forty patients, resuscitated after out-of-hospital CA and forty healthy controls, were included in the study. All patients were followed up for seventy-two hours after CA or until death. Blood samples for biomarkers were collected on admission to the ED (0-time interval) and at 6, 12, 24, 48 and 72 hours following resuscitation. Only one blood sample was collected from the controls. The serum concentrations of biomarkers were measured.

Results

For each time interval, median serum levels of resistin and S100 B were ​ significantly higher in patients with CA compared to healthy controls. The cut-of value for resistin in patients with CA, at the 12-hours versus controls, was > 8.2 ng/ml. The cut-of value for S100B in patients with CA versus controls recorded at 6 hours, was > 11.6 pg/ml.

Conclusion

Serum levels of resistin and S100B are higher among resuscitated CA patients compared to controls.

Predictive performance of plasma neutrophil gelatinase-associated lipocalin for neurologic outcomes in out-of-hospital cardiac arrest patients treated with targeted temperature management: A prospective observational study

Few studies have demonstrated the prognostic potential of neutrophil gelatinase-associated lipocalin (NGAL) in post-cardiac arrest patients. This study evaluated the usefulness of plasma NGAL in predicting neurologic outcome and mortality in out-of-hospital cardiac arrest (OHCA) patients treated with targeted temperature management (TTM). A prospective observational study was conducted between October 2013 and April 2016 at a single tertiary hospital. We enrolled 75 patients treated with TTM and collected their demographic data, cardiopulmonary resuscitation-related information, data on plasma NGAL concentration, and prognostic test results. Plasma NGAL was measured at 4 hours after return of spontaneous circulation (ROSC). The primary endpoint was the neurologic outcome at discharge and the secondary outcome was 28-day mortality. Neurologic outcomes were analyzed using a stepwise multivariate logistic regression while 28-day mortality was analyzed using a stepwise Cox regression. The predictive performance of plasma NGAL for neurologic outcome was measured by the area under the receiver operating characteristic curve and the predictability of 28-day mortality was measured using Harrell C-index. We also compared the predictive performance of plasma NGAL to that of other traditional prognostic modalities for outcome variables. Thirty patients (40%) had good neurologic outcomes and 53 (70.7%) survived for more than 28 days. Plasma NGAL in patients with good neurologic outcomes was 122.7 ± 146.7 ng/ml, which was significantly lower than that in the poor neurologic outcome group (307.5 ± 269.6 ng/ml; P < .001). The probability of a poor neurologic outcome was more than 3.3-fold in the NGAL >124.3 ng/ml group (odds ratio, 3.321; 95% confidence interval [CI], 1.265-8.721]). Plasma NGAL in the survived group was significantly lower than that in the non-survived group (172.7 ± 191.6 vs 379.9 ± 297.8 ng/ml; P = .005). Plasma NGAL was significantly correlated with 28-day mortality (hazard ratio 1.003, 95% CI 1.001-1.004; P < .001). The predictive performance of plasma NGAL was not inferior to that of other prognostic modalities except electroencephalography. Plasma NGAL is valuable for predicting the neurologic outcome and 28-day mortality of patients with OHCA at an early stage after ROSC.This study was registered at ClinicalTrials.gov on November 19, 2013 (Identifier: NCT01987466).

Urine β-2-Microglobulin, Osteopontin, and Trefoil Factor 3 May Early Predict Acute Kidney Injury and Outcome after Cardiac Arrest

PURPOSE

Acute kidney injury (AKI) is a common complication after out-of-hospital cardiac arrest (OHCA), leading to increased mortality and challenging prognostication. Our aim was to examine if urine biomarkers could early predict postarrest AKI and patient outcome.

METHODS

A prospective observational study of resuscitated, comatose OHCA patients admitted to Oslo University Hospital in Norway. Urine samples were collected at admission and day three postarrest and analysed for β-2-microglobulin (β2M), osteopontin, and trefoil factor 3 (TFF3). Outcome variables were AKI within three days according to the Kidney Disease Improving Global Outcome criteria, in addition to six-month mortality and poor neurological outcome (PNO) (cerebral performance category 3-5).

RESULTS

Among 195 included patients (85% males, mean age 60 years), 88 (45%) developed AKI, 88 (45%) died, and 96 (49%) had PNO. In univariate analyses, increased urine β2M, osteopontin, and TFF3 levels sampled at admission and day three were independent risk factors for AKI, mortality, and PNO. Exceptions were that β2M measured at day three did not predict any of the outcomes, and TFF3 at admission did not predict AKI. In multivariate analyses, combining clinical parameters and biomarker levels, the area under the receiver operating characteristics curves (95% CI) were 0.729 (0.658-0.800), 0.797 (0.733-0.861), and 0.812 (CI 0.750-0.874) for AKI, mortality, and PNO, respectively.

CONCLUSIONS

Urine levels of β2M, osteopontin, and TFF3 at admission and day three were associated with increased risk for AKI, mortality, and PNO in comatose OHCA patients. This trail is registered with NCT01239420.

A novel methodological framework for multimodality, trajectory model-based prognostication

INTRODUCTION

Prognostic tools typically combine several time-invariant clinical predictors using regression models that yield a single, time-invariant outcome prediction. This results in considerable information loss as repeatedly or continuously sampled data are aggregated into single summary measures. We describe a method for real-time multivariate outcome prediction that accommodates both longitudinal data and time-invariant clinical characteristics.

METHODS

We included comatose patients treated after resuscitation from cardiac arrest who underwent ≥6 h of electroencephalographic (EEG) monitoring. We used Persyst v13 (Persyst Development Corp, Prescott AZ) to generate quantitative EEG (qEEG) features and calculated hourly summaries of whole brain suppression ratio and amplitude-integrated EEG. We randomly selected half of subjects as a training sample and used the other half as a test sample. We applied group-based trajectory modeling (GBTM) to the training sample to group patients based on qEEG evolution, then estimated the relationship of group membership and clinical covariates with awakening from coma and surviving to hospital discharge using logistic regression. We used these parameters to calculate posterior probabilities of group membership (PPGMs) in the test sample, and built three prognostic models: adjusted logistic regression (no GBTM), unadjusted GBTM (no clinical covariates) and adjusted GBTM (all data). We compared these models performance characteristics.

RESULTS

We included 723 patients. Group-specific outcome estimates from a 7-group GBTM ranged from 0 to 75%. Compared to unadjusted GBTM, adjusted GBTM calibration was significantly improved at 6 and 12 h, and time to an outcome estimate <10% and <5% were significantly shortened. Compared to simple logistic regression, adjusted GBTM identified a substantially larger proportion of subjects with outcome probability <1%.

CONCLUSIONS

We describe a novel methodology for combining GBTM output and clinical covariates to estimate patient-specific prognosis over time. Refinement of such methods should form the basis for new avenues of prognostication research that minimize loss of clinically important information.

Resistin-Can it be a new early marker for prognosis in patients who survive after a cardiac arrest? A pilot study

AIM

The aim of our study was to evaluate the potential role of resistin in estimating the 30 days prognosis in patients with hypoxic-ischemic organ injury who survived after a cardiac arrest (CA).

MATERIALS AND METHODS

The study included 40 patients resuscitated after a non-traumatic out-of-hospital CA admitted in Emergency Department (ED). All patients were followed for 30 days after CA or until death. Clinical data on admission were recorded. Blood samples were collected on admission in ED (0-time interval), and at 6, 12, 24, 48- and 72-hours following resuscitation. Serum concentrations of resistin, S100B and neuron specific enolase (NSE) were measured. Several predictive scores for the mortality at 30 days were created with logistic regressions.

RESULTS

At each time interval, median serum levels of resistin and S100 B were significantly higher in non-survivors compared to survivors. For NSE, plasma levels were significantly lower in survivors as compared to non-survivors at 48 and 72 hours, respectively. Accurate predictive scores for 30-days mortality were the ones which included the values of resistin and S100B measured at 12 hours after admittance [AUC 0.938 (0.813-0.989), sensitivity 85.71% (67.3%- 96%), specificity 91.67% (61.5%'99.8%), p<0.001], which included the values of all three markers measured at 12 hours after admittance [AUC 0.955 (0.839-0.995), sensitivity 82.14% (63.1%'93.9%), specificity 100.00% (73.5%'100.0%), p<0.001] and the that included the values of resistin and S-100B at 6 hours together with serum lactate on admission [AUC = 0.994 (0.901-1.0), sensitivity 96.4% (81.7%'99.9%), specificity 100.00% (73.5%'100.0%), p<0.001].

CONCLUSION

In our study, serum levels of resistin or a combination of resistin with S-100B or resistin with S-100B and lactate, were highly predictive for 30 days mortality in resuscitated patients after CA. Further studies on large number of patients are needed to confirm our data.

Serial NSE measurement identifies non-survivors following out of hospital cardiac arrest

AIMS

Prognostication following out-of-hospital cardiac arrest (OHCA) remains challenging. A multimodal approach is favoured, including consideration of the biomarker neuron-specific enolase (NSE) (Sandroni et al., 2014). Our objective was to investigate the utility of serial NSE measurements and to determine an appropriate cut-off value for prediction of death before hospital discharge using data from our tertiary care center.

METHODS

Retrospective analysis of patients admitted to the critical care unit of a tertiary center critical care unit in the UK following an out-of-hospital cardiac arrest.

MEASUREMENTS AND MAIN RESULTS

We analysed data from 72 patients admitted to our unit over 8 months following out-of-hospital cardiac arrest. Initial NSE level (NSE₀) was a poor predictor of outcome. Both NSE level at 48 h post-admission (NSE₄₈) and change in NSE from baseline to 48 h post-admission (Δ_NSE) were good predictors of outcome. A cut-off of NSE₄₈ > 69.8 ng/ml gave a specificity of 1.00 and sensitivity of 0.62 for prediction of death before hospital discharge in our patient group, whilst a cut-off of Δ_NSE > 31.3 ng/ml gave a specificity of 1.00 and sensitivity of 0.54. In patients who did not survive to hospital discharge, Δ_NSE > 9.4 ng/ml was associated with other poor prognostic factors (asytolic/PEA arrest, long downtime before ROSC) and with more rapid deterioration before death.

CONCLUSION

Serial measurement of NSE levels (at 0 and 48 h after admission) provides a useful tool to aid prognostication following out-of-hospital cardiac arrest.

Association of plasma neutrophil gelatinase-associated lipocalin with acute kidney injury and clinical outcome in cardiac arrest survivors depends on the time of measurement

PURPOSE

The optimal timing for measurement of neutrophil gelatinase-associated lipocalin (NGAL) level to predict acute kidney injury (AKI) and prognosis in cardiac arrest (CA) survivors has not been elucidated. We aimed to compare the diagnostic and prognostic performance of NGAL levels after return of spontaneous circulation (ROSC) and at 48 h after CA.

METHODS

We included 231 adult cardiac arrest survivors who underwent targeted temperature management between May 2013 and December 2016. The primary outcome was stage 2 and 3 AKI (high stage AKI), and the secondary outcomes were in-hospital mortality and neurologic outcome. Sixty-one (26.4%) developed high stage AKI, 50 (21.6%) died, and 152 (65.8%) had a poor neurologic outcome.

RESULTS

NGAL level at 48 h (0.876; 95% confidence interval [CI], 0.826-0.916) had a higher area under receiver operating characteristic curve than NGAL level after ROSC (0.694; 95% CI, 0.631-0.753). Both NGAL levels were independently associated with high stage AKI. NGAL level at 48 h (1.001; 95% CI, 1.000-1.002) remained a significant predictor for in-hospital mortality, while neither of the NGAL levels were independently associated with neurologic outcome.

CONCLUSIONS

NGAL at 48 h after CA seems to be a robust predictor for high stage AKI and in-hospital mortality.

Predicting long-term outcomes after cardiac arrest by using serum neutrophil gelatinase-associated lipocalin

OBJECTIVES

Neutrophil gelatinase-associated lipocalin (NGAL) is secreted by various tissues in pathologic states. Previous studies reported that post-cardiac arrest serum NGAL levels correlate with short-term neurologic outcomes and survival. The aim of this study was to examine the associations between NGAL levels post-cardiac arrest and long-term outcomes and survival.

METHODS

This prospective observational study and retrospective review included adult out-of-hospital cardiac arrest survivors who were treated by hypothermia-targeted temperature management. Serum NGAL was assessed at 0, 24, 48, and 72h after return of spontaneous circulation. The primary outcome was poor outcome at six months after cardiac arrest, defined as cerebral performance category score of 3-5. The secondary outcome was six-month mortality.

RESULTS

In total, 76 patients were analyzed. The patients with poor outcomes showed significantly higher NGAL levels at 24, 48 and 72h after cardiac arrest than the patients with good outcomes. Long-term survival rates were significantly lower in the high-NGAL group than in the low-NGAL group at each time point. Subgroup analysis of patients who survived 72h showed that only serum NGAL 72h after cardiac arrest had prognostic value for long-term outcomes (area under the receiver operating characteristic curve=0.72; p=0.02).

CONCLUSIONS

Post-cardiac arrest serum NGAL is associated with long-term outcomes and survival; particularly, three days post-cardiac arrest is the optimal time point for predicting long-term outcomes. However, the predictive power of NGAL is unsatisfactory, and it should be regarded as an additional prognostic modality.

Plasma Neutrophil Gelatinase-Associated Lipocalin Measured Immediately After Restoration of Spontaneous Circulation Predicts Acute Kidney Injury in Cardiac Arrest Survivors Who Underwent Therapeutic Hypothermia

Early diagnosis of acute kidney injury (AKI) after cardiac arrest (CA) is challenging. We aimed to identify the diagnostic and prognostic performance of neutrophil gelatinase-associated lipocalin (NGAL) for AKI and its clinical outcomes. A retrospective observational study, involving adult comatose CA survivors treated with therapeutic hypothermia between May 2013 and December 2016, was conducted. AKI was classified according to the guidelines of Kidney Disease Improving Global Outcomes. NGAL levels were measured after return of spontaneous circulation (ROSC). The primary outcome was development of AKI within 7 days after CA, and the secondary outcome was inhospital mortality. The study included 279 patients, of which 111 (39.8%) developed AKI and 61 (21.9%) died. Thirty-seven (33.3%) of patients in the AKI group had stage 3 AKI, and 45 (40.5%) patients received renal replacement therapy. The area under the curve of NGAL levels for diagnosing AKI was 0.725 (95% confidence interval [CI] 0.668-0.776), and NGAL levels were independently associated with the development of AKI (odds ratio [OR] 1.004; 95% CI 1.002-1.006). Nonsurvivors had significantly higher NGAL levels (221.0 ng/mL [154.0-355.5] vs. 148.5 ng/mL [97.0-232.9]; p < 0.001). The development of AKI was independently associated with mortality (OR 4.926; 95% CI 2.353-10.311); however, NGAL level was not associated with mortality (OR 1.000; 95% CI 0.999-1.001). Plasma NGAL level measured after ROSC can be an early predictor for the development of AKI after CA. The presence of AKI was associated with increased inhospital mortality.

Translating biomarkers from research to clinical use in pediatric neurocritical care: focus on traumatic brain injury and cardiac arrest

PURPOSE OF REVIEW

Traumatic brain injury (TBI) and cardiac arrest are important causes of morbidity and mortality in children. Improved diagnosis and outcome prognostication using validated biomarkers could allow clinicians to better tailor therapies for optimal efficacy.

RECENT FINDINGS

Contemporary investigation has yielded plentiful biomarker candidates of central nervous system (CNS) injury, including macromolecules, genetic, inflammatory, oxidative, and metabolic biomarkers. Biomarkers have yet to be validated and translated into bedside point-of-care or cost-effective and efficient laboratory tests. Validation testing should consider developmental status, injury mechanism, and time trajectory with patient-centered outcomes.

SUMMARY

Recent investigation of biomarkers of CNS injury may soon improve diagnosis, management, and prognostication in children with traumatic brain injury and cardiac arrest.

Serum neutrophil gelatinase-associated lipocalin levels predict the neurological outcomes of out-of-hospital cardiac arrest victims

Background

Serum neutrophil gelatinase-associated lipocalin (NGAL) is a well-known biomarker of acute kidney injury. Serum NGAL was recently proposed as a potential predictor of mortality in post cardiac arrest syndrome (PCAS) patients following out-of-hospital cardiac arrest (OHCA). However, the potential predictive value of NGAL for neurological outcomes is unknown. Therefore, we assessed the potential predictive value of NGAL for neurological outcomes after OHCA. We also compared its predictive value with that of neuron-specific enolase (NSE) as an established biomarker.

Methods

Blood samples were prospectively collected from 43 PCAS patients following OHCA. Serum NGAL was measured on days 1 and 2, and NSE was measured on day 2. These biomarkers were compared between patients with favourable (cerebral performance category [CPC] 1–2) and unfavourable (CPC 3–5) outcomes. Receiver operating characteristic (ROC) curve analysis was performed.

Results

Serum NGAL and NSE on day 2 (both P < 0.001), but not NGAL on day 1 (P = 0.609), were significantly different between the favourable and unfavourable groups. In ROC curve analysis, the sensitivity and specificity were 83% and 85%, respectively, for NGAL (day 2) at a cutoff value of 204 ng/mL and were 84% and 100% for NSE (day 2) at a cutoff value of 28.8 ng/mL. The area under the ROC curve of NGAL (day 2) was equivalent to that of NSE (day 2) (0.830 vs. 0.918). Additionally, the area under the ROC curve in subgroup of estimated glomerular filtration rate (eGFR) > 20 mL/min/1.73 m² (n = 38, 0.978 vs. 0.923) showed the potential of NGAL predictability.

Conclusions

Serum NGAL might predict the neurological outcomes of PCAS patients, and its predictive value was equivalent to that of NSE.

Combination of initial neurologic examination, quantitative brain imaging and electroencephalography to predict outcome after cardiac arrest

BACKGROUND

Prognosticating outcome following cardiac arrest is challenging and requires a multimodal approach. We tested the hypothesis that the combination of initial neurologic examination, quantitative analysis of head computed tomography (CT) and continuous EEG (cEEG) improve outcome prediction after cardiac arrest.

METHODS

Review of consecutive patients receiving head CT within 24h and cEEG monitoring between April 2010 and May 2013. Initial neurologic examination (Full Outline of UnResponsiveness_Brainstem reflexes (FOUR_B) score and initial Pittsburgh Post-Cardiac Arrest Category (PCAC)), gray matter to white matter attenuation ratio (GWR) on head CT and cEEG patterns were evaluated. The primary outcome was in-hospital mortality.

RESULTS

Of 240 subjects, 70 (29%) survived and 22 (9%) had a good neurologic outcome at hospital discharge. Combined determination of GW ratio and malignant cEEG had an incremental predictive value (AUC: 0.776 for mortality and 0.792 for poor neurologic outcome), with 0% false positive rate when compared with either test alone (AUC of GW ratio: 0.683 for mortality and 0.726 for poor outcome, AUC of malignant cEEG: 0.650 for mortality and 0.647 for poor outcome). Addition of FOUR_B or PCAC to this model improved prediction of mortality (p=0.014 for FOUR_B and 0.001 for PCAC) but not of poor outcome (p=0.786 for FOUR_B and 0.099 for PCAC).

CONCLUSIONS

Combining GWR with cEEG was superior to any individual test for predicting mortality and neurologic outcome. Addition of clinical variables further improved prognostication for mortality but not neurologic outcome. These preliminary data support a multi-modal prognostic workup in this population.

Effect of Erythropoietin on Postresuscitation Renal Function in a Swine Model of Ventricular Fibrillation

Purpose. To investigate the effect of EPO administration on postresuscitation renal function. Methods. Twenty-four female Landrace/Large-White piglets aged 10–15 weeks with average weight of 19 ± 2 kg were randomly assigned to 2 different groups of 12 subjects each. After the end of an 8-minute ventricular fibrillation, the control group (Group C) received saline as placebo, whereas the EPO group (Group E) received EPO 5000 U/kg. The animals were resuscitated according to the 2010 European Resuscitation Council Guidelines for Resuscitation. Results. Five animals (41.67%) from Group C and 11 animals (91.67%) from Group E achieved ROSC (p = 0.027). Eight animals (66.67%, 5 surviving and 3 nonsurviving) from Group C suffered severe kidney damage or AKI compared to animals from Group E, in which none of the swine had evidence of severe kidney damage or AKI (p = 0.001). There was a statistically significant difference in all tested biochemical markers between the two groups, as well as a positive correlation of creatinine with NGAL, L-FABP, and IL-18 (summed mean values' p = 0.049, 0.01, and 0.004, resp.). Conclusions. Administration of EPO protected swine from postresuscitation acute kidney injury.

Urine biomarkers give early prediction of acute kidney injury and outcome after out-of-hospital cardiac arrest

Background

Post-resuscitation care after out-of-hospital cardiac arrest (OHCA) is challenging due to the threat of organ failure and difficult prognostication. Our aim was to examine whether urine biomarkers could give an early prediction of acute kidney injury (AKI) and outcome.

Methods

This was a prospective observational study of comatose OHCA patients at Oslo University Hospital Ullevål, Norway. Risk factors were clinical parameters and biomarkers measured in spot urine (cystatin C, neutrophil gelatinase-associated lipocalin (NGAL) and the product of tissue inhibitor of metalloproteinase 2 (TIMP-2) and insulin-like growth factor-binding protein 7 (IGFBP7)) at admission and day 3. Outcome variables were AKI within 3 days using the Kidney Disease Improving Global Outcomes definition, 6-month mortality, and poor neurological outcome (PNO) defined as cerebral performance category 3–5.

Results

Among 195 included patients (85 % males, mean age 60 years), 88 (45 %) died, 96 (49 %) had PNO, and 88 (45 %) developed AKI. In univariate analysis, increased urine cystatin C and NGAL concentration sampled at admission and day 3 were independent risk factors for AKI, mortality and PNO. Increased urine TIMP-2 × IGFBP7 levels was associated with AKI only at admission. In multivariate analyses combining clinical parameters and biomarker concentrations, the area under the receiver operating characteristics curve (AuROC) with 95 % confidence interval (CI) were 0.774 (0.700–0.848), 0.812 (0.751–0.873), and 0.819 (0.759–0.878) for AKI, mortality and PNO, respectively.

Conclusions

In comatose OHCA patients, urine levels of cystatin C and NGAL at admission and day 3 were independent risk factors for AKI, 6-month mortality and PNO.

Trial registration

Clinicaltrials.gov NCT01239420. Registered 10 November 2010.

Electronic supplementary material

The online version of this article (doi:10.1186/s13054-016-1503-2) contains supplementary material, which is available to authorized users.