Improvement of sepsis identification through multi-year comparison of sepsis and early warning scores

Sepsis remains a leading cause of death among inpatients. Scoring systems designed to identify inpatients with sepsis currently have limited effectiveness. This single institution, retrospective, case-control study aims to improve sepsis decision support tool performance using temporal analyses of s...

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Veröffentlicht in:The American journal of emergency medicine 2022-01, Vol.51, p.239-247
Hauptverfasser: McGrath, Susan P., Perreard, Irina, MacKenzie, Todd, Calderwood, Michael
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Sprache:eng
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Zusammenfassung:Sepsis remains a leading cause of death among inpatients. Scoring systems designed to identify inpatients with sepsis currently have limited effectiveness. This single institution, retrospective, case-control study aims to improve sepsis decision support tool performance using temporal analyses of sepsis-specific and general deterioration scoring systems. Sequential Organ Failure Assessment, National Early Warning Scores (NEWS), and Modified Early Warning Scores were calculated using four years of inpatient data. Sensitivity and specificity analyses compared performance of each score, calculated as a function of both various score cut-off values and time before sepsis diagnosis using established proxies for identifying clinical suspicion for sepsis. NEWS had the best sensitivity-specificity performance (AUROC 82.7) when examining various score cutoffs and time intervals during which diagnosis criteria were met. Comparison of false positives/negatives with various score thresholds showed a low rate of false positives with a NEWS of 7. Score trends in the hours leading up to sepsis criteria being met showed a marked increase for the sepsis group while for the cases there was a decrease during a comparable period. Temporal analyses of scores for patients coded as having sepsis provides novel insights into patterns of deterioration. The methods and results provide practical details demonstrating how general deterioration algorithms can be used to alert trained responders to potential cases of sepsis to improve sepsis recognition and treatment opportunities. •Current sepsis identification scoring systems have limited effectiveness.•This study offers novel insights into sepsis diagnosis support tools via temporal pattern analysis prior to sepsis identification.•Detailed performance comparison for various scores to improve clinical score application is presented.•The methods and results presented can be used to guide improvement efforts for sepsis identification in the hospital setting.
ISSN:0735-6757
1532-8171
DOI:10.1016/j.ajem.2021.10.046