- Record: found
- Abstract: not found
- Article: not found
Precision Care in Cardiac Arrest: ICECAP (PRECICECAP) Study Protocol and Informatics Approach
Jonathan Elmer ,
Zihuai He ,
Teresa May ,
Elizabeth Osborn ,
Richard Moberg ,
Stephanie Kemp ,
Jesse Stover ,
Ethan Moyer ,
Romergryko G. Geocadin ,
Karen G. Hirsch ,
the PRECICECAP Study Team
March 01 2022
Read this article at
There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.
Abstract
Most trials in critical care have been neutral, in part because between-patient heterogeneity
means not all patients respond identically to the same treatment. The Precision Care
in Cardiac Arrest: Influence of Cooling duration on Efficacy in Cardiac Arrest Patients
(PRECICECAP) study will apply machine learning to high-resolution, multimodality data
collected from patients resuscitated from out-of-hospital cardiac arrest. We aim to
discover novel biomarker signatures to predict the optimal duration of therapeutic
hypothermia and 90-day functional outcomes. In parallel, we are developing a freely
available software platform for standardized curation of intensive care unit-acquired
data for machine learning applications.