SCCM Resource Library-Improving the Precision of Early Sepsis Detection

Video Transcription

Video Summary

In this video, Tiffany Osborne discusses the challenges of pre-hospital sepsis detection and treatment. She begins by highlighting the significant number of patients that arrive at the emergency department by ambulance, with many of them being elderly and at risk for sepsis. She explains that detecting sepsis in pre-hospital environments is difficult due to the variability and lack of clear criteria for differentiation. However, recent studies have shown improvements in pre-hospital sepsis detection strategies by incorporating additional physiological markers such as end-tidal CO2 and lactate. These markers have been found to improve the accuracy of identifying sepsis patients and predicting outcomes. Osborne also emphasizes the importance of collaboration between pre-hospital providers, emergency departments, and intensive care units in order to provide comprehensive care for sepsis patients. She concludes by stating that early detection of sepsis is associated with early treatment and better outcomes, and that integrating physiological and biomarker data can enhance the development of real-time intelligent learning systems for sepsis management. Overall, Osborne emphasizes the need for continued research and improvement in pre-hospital sepsis detection and treatment in order to provide the best care for patients.

Asset Subtitle

Sepsis, 2021

Asset Caption

The Society of Critical Care Medicine's Critical Care Congress features internationally renowned faculty and content sessions highlighting the most up-to-date, evidence-based developments in critical care medicine. This is a presentation from the 2021 Critical Care Congress held virtually from January 31-February 12, 2021.

Learning Objectives

Critique prehospital screening techniques that perform best for early sepsis detection
Explore new biomarkers that improve the accuracy of sepsis detection during the initial emergency department encounter and guide delivery of sepsis care bundles
Identify widely available parameters during the initial clinical encounter that could lead to earlier detection and treatment
Apply computer-based machine learning algorithms to electronic medical record data to detect vital sign and laboratory patterns that are highly predictive of sepsis

Earlier Sepsis Detection and Treatment Prior to ED Admission
Tiffany M. Osborn

Big Data Biomarkers
Rishikesan Kamaleswaran

Meta Tag

Content Type Presentation

Knowledge Area Sepsis

Knowledge Level Foundational

Knowledge Level Intermediate

Knowledge Level Advanced

Membership Level Select

Membership Level Nonmember

Membership Level Associate

Membership Level Professional

Tag Scoring Systems

Tag Shock

Year 2021

Keywords

Tiffany Osborne

pre-hospital sepsis detection

pre-hospital sepsis treatment

physiological markers

end-tidal CO2

lactate

sepsis patient identification

outcome prediction

collaboration

early detection of sepsis

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