Brain-derived extracellular vesicles as serologic markers of brain injury following cardiac arrest: A pilot feasibility study

Multiomic biomarkers after cardiac arrest

Cardiac arrest is a sudden cessation of heart function, leading to an abrupt loss of blood flow and oxygen to vital organs. This life-threatening emergency requires immediate medical intervention and can lead to severe neurological injury or death. Methods and biomarkers to predict neurological outcome are available but lack accuracy. Such methods would allow personalizing healthcare and help clinical decisions. Extensive research has been conducted to identify prognostic omic biomarkers of cardiac arrest. With the emergence of technologies allowing to combine different levels of omics data, and with the help of artificial intelligence and machine learning, there is a potential to use multiomic signatures as prognostic biomarkers after cardiac arrest. This review article delves into the current knowledge of cardiac arrest biomarkers across various omic fields and suggests directions for future research aiming to integrate multiple omics data layers to improve outcome prediction and cardiac arrest patient's care.

Unraveling the Emerging Niche Role of Extracellular Vesicles (EVs) in Traumatic Brain Injury (TBI)

Extracellular vesicles or exosomes, often known as EVs, have acquired significant attention in the investigations of traumatic brain injury (TBI) and have a distinct advantage in actively researching the fundamental mechanisms underlying various clinical symptoms and diagnosing the wide range of traumatic brain injury cases. The mesenchymal stem cells (MSCs) can produce and release exosomes, which offer therapeutic benefits. Exosomes are tiny membranous vesicles produced by various cellular entities originating from endosomes. Several studies have reported that administering MSC-derived exosomes through intravenous infusions improves neurological recovery and promotes neuroplasticity in rats with traumatic brain damage. The therapeutic advantages of exosomes can be attributed to the microRNAs (miRNAs), which are small non-coding regulatory RNAs that significantly impact the regulation of posttranscriptional genes. Exosome-based therapies, which do not involve cells, have lately gained interest as a potential breakthrough in enhancing neuroplasticity and accelerating neurological recovery for various brain injuries and neurodegenerative diseases. This article explores the benefits and drawbacks of exosome treatment for traumatic brain injury while emphasizing the latest advancements in this field with clinical significance.

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.