The secrets of sepsis: A data-driven approach to improve its diagnostic work-up and treatment

M. Schinkel

The secrets of sepsis: A data-driven approach to improve its diagnostic work-up and treatment

M. Schinkel

Research output: PhD Thesis › Phd-Thesis - Research and graduation internal

Abstract

This thesis investigates sepsis management, focusing on diagnostic work-up, antibiotic treatment, and applying data and machine learning to optimize care. Despite decades of research, effective sepsis-specific therapies have yet to be found, limiting the treatment options to supportive therapy and antimicrobials. By implementing a sepsis response team in our hospital's emergency

Original language	English
Qualification	Doctor of Philosophy
Awarding Institution	University of Amsterdam
Supervisors/Advisors	Wiersinga, Willem, Supervisor Nanayakkara, Prabath W. B., Supervisor, External person Holleman, Frits, Co-supervisor
Award date	26 May 2023
Print ISBNs	9789493278431
Publication status	Published - 26 May 2023

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https://hdl.handle.net/11245.1/83a05a03-d32b-47d5-9870-4385c39fbf9a

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AB - This thesis investigates sepsis management, focusing on diagnostic work-up, antibiotic treatment, and applying data and machine learning to optimize care. Despite decades of research, effective sepsis-specific therapies have yet to be found, limiting the treatment options to supportive therapy and antimicrobials. By implementing a sepsis response team in our hospital's emergency

M3 - Phd-Thesis - Research and graduation internal

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The secrets of sepsis: A data-driven approach to improve its diagnostic work-up and treatment

Abstract

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