@article{JECCM5329,
author = {Gemma Phillips and Amisha Cameron and Tamas Szakmany},
title = {Defining the high-risk patient},
journal = {Journal of Emergency and Critical Care Medicine},
volume = {3},
number = {0},
year = {2019},
keywords = {},
abstract = {As the volume of surgery continues to grow worldwide, the identification of high-risk patients is an important goal to guide clinical decision making in the perioperative period. Risk stratification evolved over the last decade from simple risk stratification tools, still used widely in the clinical arena to more sophisticated risk prediction models based on machine learning and latent class analysis, which can be incorporated into a well-developed electronic patient record or critical care clinical information system. As the debate about which patients will benefit most from critical care admission and interventions is still ongoing, the identification of the high-risk patient is a continuing challenge. In this review we will summarise the latest developments in the use of these risk stratification tools and risk prediction models, which can be utilised to identify the high-risk surgical candidate.},
issn = {2521-3563}, url = {https://jeccm.amegroups.org/article/view/5329}
}