Intensive Care Medicine Experimental (Sep 2024)

Multiomic biomarkers after cardiac arrest

  • Victoria Stopa,
  • Gabriele Lileikyte,
  • Anahita Bakochi,
  • Prasoon Agarwal,
  • Rasmus Beske,
  • Pascal Stammet,
  • Christian Hassager,
  • Filip Årman,
  • Niklas Nielsen,
  • Yvan Devaux

DOI
https://doi.org/10.1186/s40635-024-00675-y
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 11

Abstract

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Abstract 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.

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