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Thesis

Predicting In-hospital Mortality for Sepsis Utilizing the Clinical Tools: SIRS, qSOFA, & NEWS

7 August 2020

Abstract

Background: The sepsis-3 guidelines suggest use of the quick Sequential Organ Failure Assessment (qSOFA) score for patients with sepsis to determine organ dysfunction. To validate the qSOFA score, it was compared against systemic inflammatory response syndrome (SIRS) and National Early Warning Signs (NEWS) for predicting in-hospital mortality. This critically appraised topic will help identify which clinical tool should be utilized in the hospital setting.

Methods: An exhaustive search of available medical literature was performed on MEDLINE-PubMed, Web of Science, and CINAHL using the keywords (sepsis OR septic shock OR severe sepsis) AND (mortality OR in-hospital mortality OR hospital mortality or inhospital mortality) AND (NEWS OR national early warning signs OR early warning scores) AND (SIRS or systemic inflammatory response syndrome) AND (qSOFA OR Quick Sepsis-related Organ Failure Assessment OR Quick Sepsis Organ Failure Assessment). A risk of bias assessment was performed.

Results: Fifteen studies were found using the search criteria related to clinical tools for NEWS, SIRS, and qSOFA for sepsis. Four studies were relevant for predicting in-hospital mortality. The risk of bias for the studies was high. For predicting in-hospital mortality, NEWS was most accurate for area underneath the curve [AUC]. In comparing in-hospital mortality, the sensitivity for SIRS was highest (0.77 – 91), followed by NEWS (0.68 – 0.74), and qSOFA (0.28 – 0.54). For specificity, qSOFA was highest (0.67 – 93.7), followed by NEWS (0.43 – 66.5), and SIRS (0.13 – 37.6).

Conclusion: NEWS is more accurate or at least equivalent at predicting in-hospital mortality than SIRS or qSOFA. This calls into question the practicality of adopting qSOFA, as suggested in sepsis-3, in hospitals where NEWS has already been implemented. For hospitals utilizing SIRS, adopting NEWS instead of qSOFA should also be considered.

Keywords: Predicting in-hospital mortality, sepsis, clinical tools, SIRS, qSOFA, NEWS

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Fielding_R_Situ_G_Final_Draft.docx
2 Aug 2020
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