Copeptin as a marker of outcome after cardiac arrest: a sub-study of the TTM trial

Recovery and Survival of Patients After Out-of-Hospital Cardiac Arrest: A Literature Review Showcasing the Big Picture of Intensive Care Unit-Related Factors

As an important public health issue, out-of-hospital cardiac arrest (OHCA) requires several stages of high quality medical care, both on-field and after hospital admission. Post-cardiac arrest shock can lead to severe neurological injury, resulting in poor recovery outcome and increased risk of death. These characteristics make this condition one of the most important issues to deal with in post-OHCA patients hospitalized in intensive care units (ICUs). Also, the majority of initial post-resuscitation survivors have underlying coronary diseases making revascularization procedure another crucial step in early management of these patients. Besides keeping myocardial blood flow at a satisfactory level, other tissues must not be neglected as well, and maintaining mean arterial pressure within optimal range is also preferable. All these procedures can be simplified to a certain level along with using targeted temperature management methods in order to decrease metabolic demands in ICU-hospitalized post-OHCA patients. Additionally, withdrawal of life-sustaining therapy as a controversial ethical topic is under constant re-evaluation due to its possible influence on overall mortality rates in patients initially surviving OHCA. Focusing on all of these important points in process of managing ICU patients is an imperative towards better survival and complete recovery rates.

ST2 and copeptine – modern biomarkers for monitoring the effectiveness of treatment of decompensated heart failure in patients after acute myocardial infarction

The aim of the study was to increase the efficiency of diagnostic methods to find means to improve the treatment of patients with decompensated heart failure in the post-infarction period. Materials and methods. This study is based on an examination of 120 patients with decompensated HF (60 patients with STEMI and 60 with non-STEMI). Patients with previous STEMI complicated by decompensated heart failure were divided into groups, depending on their treatment. The studied groups were homogeneous in terms of age, sex, the severity of the course of the disease, duration of the post-infarction period, and the presence of clinical manifestations of decompensation. The patients were observed on the first day after hospitalization, after 1 and 2 months after treatment. Copeptin serum levels were assayed using the EK 065-32, EIA Copeptine kit (RayBiotech, Inc., USA). ST-2 in blood serum was determined with the help of the Presage ST-2 kit (Critical Diagnostics, USA). The level of ST2 was determined in ng/ml. Results. We analysed the effect of therapy on the level of ST2 in the blood serum of examined patients with STEMI and non-STEMI complicated by decompensated heart failure. All the treatment regimens we proposed led to a significant decrease in the level of this peptide in blood serum after the end of the treatment. In patients of group I who received basic therapy drugs, the average ST2 concentration was (49.47±1.77) ng/ml before treatment. After 1 and 2 months of therapy, it was (44.92±1.22) ng/ml and (41.67±1.18) ng/ml, respectively (p˂0.05). The patients with decompensated heart failure after non-STEMI from group I had a copeptin level of (18.13±0.10) pg/ml before treatment and probably decreased to levels of (16.29±0.15) pg/ml and (15.09±0.14) pg/ml after 1 and 2 months under the influence standard therapy. Conclusions. We found the dependence of copeptin and ST2 levels on decompensated HF in the early and late post-infarction periods. It was established that the use of the therapy with a combination of the studied drugs led to a more intense decrease in serum copeptin, compared to therapy with succinic acid, arginine drugs, and standard therapy (p˂0.05). Using a differentiated treatment algorithm for patients with decompensated heart failure in the post-infarction period, copeptin and ST2 in blood serum increases the effectiveness of treatment and prevents complications.

Copeptin and Stress

Vasopressin (AVP) and copeptin are released in equimolar amounts from the same precursor. Due to its molecular stability and countless advantages as compared with AVP, copeptin perfectly mirrors AVP presence and has progressively emerged as a reliable marker of vasopressinergic activation in response to osmotic and hemodynamic stimuli in clinical practice. Moreover, evidence highlighting the prognostic potential of copeptin in several acute diseases, where the activation of the AVP system is primarily linked to stress, as well as in psychologically stressful conditions, has progressively emerged. Furthermore, organic stressors induce a rise in copeptin levels which, although non-specific, is unrelated to plasma osmolality but proportional to their magnitude: suggesting disease severity, copeptin proved to be a reliable prognostic biomarker in acute conditions, such as sepsis, early post-surgical period, cardiovascular, cerebrovascular or pulmonary diseases, and even in critical settings. Evidence on this topic will be briefly discussed in this article.

Elevated Plasma Soluble PD-L1 Levels in Out-of-Hospital Cardiac Arrest Patients

Background: A deregulated immune system has been implicated in the pathogenesis of post-cardiac arrest syndrome (PCAS). A soluble form of programmed cell death-1 (PD-1) ligand (sPD-L1) has been found at increased levels in cancer and sustained inflammation, thereby deregulating immune functions. Here, we aim to study the possible involvement of sPD-L1 in PCAS. Methods: Thirty out-of-hospital cardiac arrest (OHCA) patients consecutively admitted to the ER of Mie University Hospital were prospectively enrolled. Plasma concentrations of sPD-L1 were measured by an enzyme-linked immunosorbent assay in blood samples of all 30 OHCA patients obtained during cardiopulmonary resuscitation (CPR). In 13 patients who achieved return-of-spontaneous-circulation (ROSC), sPD-L1 levels were also measured daily in the ICU. Results: The plasma concentrations of sPD-L1 in OHCA were significantly increased; in fact, to levels as high as those observed in sepsis. sPD-L1 levels during CPR correlated with reduced peripheral lymphocyte counts and increased C-reactive protein levels. Of 13 ROSC patients, 7 cases survived in the ICU for more than 4 days. A longitudinal analysis of sPD-L1 levels in the 7 ROSC cases revealed that sPD-L1 levels occurred in parallel with organ failure. Conclusions: This study suggests that ischemia- reperfusion during CPR may aberrantly activate immune and endothelial cells to release sPD-L1 into circulation, which may play a role in the pathogenesis of immune exhaustion and organ failures associated with PCAS.

Prognostic Performance of Peripheral Blood Biomarkers in Identifying Seropositive Individuals at Risk of Developing Clinically Symptomatic Chagas Cardiomyopathy

Biomarkers for prognosis-based detection of Trypanosoma cruzi-infected patients presenting no clinical symptoms to cardiac Chagas disease (CD) are not available. In this study, we examined the performance of seven biomarkers in prognosis and risk of symptomatic CD development. T. cruzi-infected patients clinically asymptomatic (C/A; n = 30) or clinically symptomatic (C/S; n = 30) for cardiac disease and humans who were noninfected and healthy (N/H; n = 24) were enrolled (1 - β = 80%, α = 0.05). Serum, plasma, and peripheral blood mononuclear cells (PBMCs) were analyzed for heterogeneous nuclear ribonucleoprotein A1 (hnRNPA1), vimentin, poly(ADP-ribose) polymerase (PARP1), 8-hydroxy-2-deoxyguanosine (8-OHdG), copeptin, endostatin, and myostatin biomarkers by enzyme-linked immunosorbent assay (ELISA) and Western blotting. Secreted hnRNPA1, vimentin, PARP1, 8-OHdG, copeptin, and endostatin were increased by 1.4- to 7.0-fold in CD subjects versus N/H subjects (P < 0.001) and showed excellent predictive value in identifying the occurrence of infection (area under the receiver operating characteristic [ROC] curve [AUC], 0.935 to 0.999). Of these, vimentin, 8-OHdG, and copeptin exhibited the best performance in prognosis of C/S (versus C/A) CD, determined by binary logistic regression analysis with the Cox and Snell test (R2C&S = 0.492 to 0.688). A decline in myostatin and increase in hnRNPA1 also exhibited good predictive value in identifying C/S and C/A CD status, respectively. Furthermore, circulatory 8-OHdG (Wald χ2 = 15.065), vimentin (Wald χ2 = 14.587), and endostatin (Wald χ2 = 17.902) levels exhibited a strong association with changes in left ventricular ejection fraction and diastolic diameter (P = 0.001) and predicted the risk of cardiomyopathy development in CD patients. We have identified four biomarkers (vimentin, 8-OHdG, copeptin, and endostatin) that offer excellent value in prognosis and risk of symptomatic CD development. Decline in these four biomarkers and increase in hnRNPA1 would be useful in monitoring the efficacy of therapies and vaccines in halting CD. IMPORTANCE There is a lack of validated biomarkers for diagnosis of T. cruzi-infected individuals at risk of developing heart disease. Of the seven potential biomarkers that were screened, vimentin, 8-OHdG, copeptin, and endostatin exhibited excellent performance in distinguishing the clinical severity of Chagas disease. A decline in these four biomarkers can also be used for monitoring the therapeutic responses of infected patients to established or newly developed drugs and vaccines and precisely inform the patients about their progress. These biomarkers can easily be screened using the readily available plasma/serum samples in the clinical setting by an ELISA that is inexpensive, fast, and requires low-tech resources at the facility, equipment, and personnel levels.

Serum markers of brain injury can predict good neurological outcome after out-of-hospital cardiac arrest

Purpose

The majority of unconscious patients after cardiac arrest (CA) do not fulfill guideline criteria for a likely poor outcome, their prognosis is considered “indeterminate”. We compared brain injury markers in blood for prediction of good outcome and for identifying false positive predictions of poor outcome as recommended by guidelines.

Methods

Retrospective analysis of prospectively collected serum samples at 24, 48 and 72 h post arrest within the Target Temperature Management after out-of-hospital cardiac arrest (TTM)-trial. Clinically available markers neuron-specific enolase (NSE) and S100B, and novel markers neurofilament light chain (NFL), total tau, ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) and glial fibrillary acidic protein (GFAP) were analysed. Normal levels with a priori cutoffs specified by reference laboratories or defined from literature were used to predict good outcome (no to moderate disability, Cerebral Performance Category scale 1–2) at 6 months.

Results

Seven hundred and seventeen patients were included. Normal NFL, tau and GFAP had the highest sensitivities (97.2–98% of poor outcome patients had abnormal serum levels) and NPV (normal levels predicted good outcome in 87–95% of patients). Normal S100B and NSE predicted good outcome with NPV 76–82.2%. Normal NSE correctly identified 67/190 (35.3%) patients with good outcome among those classified as “indeterminate outcome” by guidelines. Five patients with single pathological prognostic findings despite normal biomarkers had good outcome.

Conclusion

Low levels of brain injury markers in blood are associated with good neurological outcome after CA. Incorporating biomarkers into neuroprognostication may help prevent premature withdrawal of life-sustaining therapy.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00134-021-06481-4.

Predicting neurological outcome after out-of-hospital cardiac arrest with cumulative information; development and internal validation of an artificial neural network algorithm

Background

Prognostication of neurological outcome in patients who remain comatose after cardiac arrest resuscitation is complex. Clinical variables, as well as biomarkers of brain injury, cardiac injury, and systemic inflammation, all yield some prognostic value. We hypothesised that cumulative information obtained during the first three days of intensive care could produce a reliable model for predicting neurological outcome following out-of-hospital cardiac arrest (OHCA) using artificial neural network (ANN) with and without biomarkers.

Methods

We performed a post hoc analysis of 932 patients from the Target Temperature Management trial. We focused on comatose patients at 24, 48, and 72 h post-cardiac arrest and excluded patients who were awake or deceased at these time points. 80% of the patients were allocated for model development (training set) and 20% for internal validation (test set). To investigate the prognostic potential of different levels of biomarkers (clinically available and research-grade), patients’ background information, and intensive care observation and treatment, we created three models for each time point: (1) clinical variables, (2) adding clinically accessible biomarkers, e.g., neuron-specific enolase (NSE) and (3) adding research-grade biomarkers, e.g., neurofilament light (NFL). Patient outcome was the dichotomised Cerebral Performance Category (CPC) at six months; a good outcome was defined as CPC 1–2 whilst a poor outcome was defined as CPC 3–5. The area under the receiver operating characteristic curve (AUROC) was calculated for all test sets.

Results

AUROC remained below 90% when using only clinical variables throughout the first three days in the ICU. Adding clinically accessible biomarkers such as NSE, AUROC increased from 82 to 94% (p < 0.01). The prognostic accuracy remained excellent from day 1 to day 3 with an AUROC at approximately 95% when adding research-grade biomarkers. The models which included NSE after 72 h and NFL on any of the three days had a low risk of false-positive predictions while retaining a low number of false-negative predictions.

Conclusions

In this exploratory study, ANNs provided good to excellent prognostic accuracy in predicting neurological outcome in comatose patients post OHCA. The models which included NSE after 72 h and NFL on all days showed promising prognostic performance.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13054-021-03505-9.

Neurohumoral, cardiac and inflammatory markers in the evaluation of heart failure severity and progression

Heart failure is common in adult population, accounting for substantial morbidity and mortality worldwide. The main risk factors for heart failure are coronary artery disease, hypertension, obesity, diabetes mellitus, chronic pulmonary diseases, family history of cardiovascular diseases, cardiotoxic therapy. The main factor associated with poor outcome of these patients is constant progression of heart failure. In the current review we present evidence on the role of established and candidate neurohumoral biomarkers for heart failure progression management and diagnostics. A growing number of biomarkers have been proposed as potentially useful in heart failure patients, but not one of them still resembles the characteristics of the “ideal biomarker.” A single marker will hardly perform well for screening, diagnostic, prognostic, and therapeutic management purposes. Moreover, the pathophysiological and clinical significance of biomarkers may depend on the presentation, stage, and severity of the disease. The authors cover main classification of heart failure phenotypes, based on the measurement of left ventricular ejection fraction, including heart failure with preserved ejection fraction, heart failure with reduced ejection fraction, and the recently proposed category heart failure with mid-range ejection fraction. One could envisage specific sets of biomarker with different performances in heart failure progression with different left ventricular ejection fraction especially as concerns prediction of the future course of the disease and of left ventricular adverse/reverse remodeling. This article is intended to provide an overview of basic and additional mechanisms of heart failure progression will contribute to a more comprehensive knowledge of the disease pathogenesis.

Copeptin as a Prognostic Marker in Prolonged Targeted Temperature Management After Out-of-Hospital Cardiac Arrest

The aim was to investigate blood concentrations of copeptin and the prognostication in 24 versus 48 hours of targeted temperature management (TTM) in patients resuscitated after out-of-hospital cardiac arrest. This is an exploratory biomarker substudy of the trial entitled; "Targeted temperature management for 48 vs 24 hours and neurologic outcome after out-of-hospital-cardiac-arrest: A randomized clinical trial." Patients were randomized to target temperature of 33°C ± 1°C for 24 (TTM24) or 48 (TTM48) hours. The primary outcome was copeptin concentrations compared with TTM at admission, 24, 48, and 72 hours (t24, t48, and t72) after reaching target temperature. Secondary outcomes were the association between copeptin and cerebral performance category (CPC) score after 6 months, and copeptin level between cerebral or noncerebral causes of death. Blood samples from 117 patients were analyzed from two Scandinavian sites. No significant differences in copeptin concentrations were found between TTM24 versus TTM48 at admission 211.3 μg/L (148-276.6) versus 179.8 μg/L (127-232.6) (p = 0.45), t24: 23.3 μg/L (16.5-30.2) versus 18.6 μg/L (13.3-23.9) (p = 0.25), t48: 28.8 μg/L (20.6-36.9) versus 19.7 μg/L (14.3-25.1) (p = 0.06), and t72: 23.3 μg/L (13.8-26.8) versus 31.6 μg/L (22-41.2) (p = 0.05). Copeptin concentrations were significantly higher in poor neurological outcome group at t24, t48, and t72 (p < 0.01), but not at admission (p = 0.19). The prognostic ability of copeptin (area under the receiver operating characteristic curve) was at admission: 0.59 (95% confidence intervals: 0.46-0.72), t24: 0.74 (0.63-0.86), t48: 0.8 (0.7-0.9), and t72: 0.76 (0.65-0.87). Copeptin levels were not significantly different in noncerebral compared with cerebral causes at admission: p = 0.41, t24: p = 0.52, t48: p = 0.15, and t72: p = 0.38. There were no differences in the level of copeptin in TTM24 versus TTM48. Blood concentrations of copeptin were associated with CPC at 6 months, and no association between levels of copeptin and cerebral versus noncerebral causes of death was observed.