Abstract
Risk stratification is an important metric for a mature surgical system. It not only is the development of comparative outcome data but serves as an important tool for is a tool for goal concordant care discussions with patients. As we move to an Emergency General Surgery (EGS) regional system that mirrors the existing trauma system risk stratification will allow for triage of high-risk patients to receive appropriate preoperative and postoperative care. Evidence has shown that the EGS population has unique physiology with markedly different outcomes than their elective counterparts. The tools we use to measure the outcomes in this challenging population are still evolving. An ideal risk stratification system will provide accurate prediction from readily obtainable objective data in all populations and can be used easily in clinical practice. There are many different types of risk stratification systems which use a combination of patient comorbidity, physiology, and disease mechanism to predict outcomes, with varying levels of accuracy. An ideal tool would incorporate variables from all these non-modifiable factors yet still be easy enough to use in real time by the clinician. Currently there is no idealized EGS risk stratification system. An ideal model may combine comorbidity factors, physiologic factors, and emergent pathology factors to clarify the degree of severity based more on a mechanistic model. Here in, we review the existing literature on the above factors and propose the direction EGS risk stratification may take in the future. There are many different scoring systems providing stratification of risk in EGS patients created over the previous 80 years. Accuracy of outcome prediction varies based on the system chosen and the components the system uses. As prediction models become more accurate, the complexity typically increases. Recent literature suggests that linear regression for prediction of outcomes may not be the most accurate risk stratification technique. Further research is necessary to determine which outcomes bear the most clinical significance. Benchmarking EGS systems by risk stratification of outcomes also requires further analysis. Each risk stratification system has advantages and disadvantages to use. Pathology in EGS patients suggests outcomes are dependent on the mechanism of disease, physiology of patients on presentation, as well as current comorbidities. An idealized EGS risk stratification system will provide accurate prediction from readily obtainable objective data in all EGS populations and can be used easily in clinical practice. Further research is necessary to provide integration of these factors into a user-friendly and easily applicable interface.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.