Dynamic biomarker trajectories in the first 72 h after infarct-related cardiac arrest: a novel approach to early risk stratification
In patients who survive the initial critical phase after cardiac arrest, early prognostication remains limited due to evolving clinical trajectories. Admission biomarkers alone are insufficient for making definitive decisions. The post-resuscitation period represents a critical "second hit" characterized by systemic inflammation and organ dysfunction. Integrating serial biomarker trends into dynamic risk models, such as with machine learning, offers a more individualized and accurate approach to post-cardiac arrest prognostication and care.
Authors
- Tobias Petzold (ORCID: https://orcid.org/0000-0001-7805-5632)
- Carsten Skurk (ORCID: https://orcid.org/0000-0003-4953-601X)
- Georg Girke
- Eva-Maria Dorsch (ORCID: https://orcid.org/0009-0002-5872-1268)
- Janina Boettel
- Susanne Neschen
- Andi Rroku (ORCID: https://orcid.org/0000-0003-2464-4129)
- Benjamin O’Brien (ORCID: https://orcid.org/0000-0001-7024-2337)
- Youssef S. Abdelwahed (ORCID: https://orcid.org/0000-0002-2708-4596)
- Steffen Desch (ORCID: https://orcid.org/0000-0002-1349-9969)
- Tharusan Thevathasan (ORCID: https://orcid.org/0000-0003-4698-4079)
- Ulf Landmesser
- Julian Mohsennia
Institutions
- Deutsches Herzzentrum der Charité (DE)
- Leipzig Heart Institute (DE)
- German Centre for Cardiovascular Research (DE)
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin (DE)
- Charité - Universitätsmedizin Berlin (DE)
Publication Details
- Journal
- Resuscitation Plus
- Published
- 2025-10-15
- DOI
- https://doi.org/10.1016/j.resplu.2025.101126
- Primary Topic
- Cardiac Arrest and Resuscitation
- Type
- article
- Field-Weighted Citation Impact
- 0.00