A comparison of predictors for mortality and bacteraemia in patients suspected of infection

Steen Andreassen, Jens Kjølseth Møller, Noa Eliakim-Raz, Gorm Lisby, Logan Ward

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

BACKGROUND: Stratification by clinical scores of patients suspected of infection can be used to support decisions on treatment and diagnostic workup. Seven clinical scores, SepsisFinder (SF), National Early Warning Score (NEWS), Sequential Orgen Failure Assessment (SOFA), Mortality in Emergency Department Sepsis (MEDS), quick SOFA (qSOFA), Shapiro Decision Rule (SDR) and Systemic Inflammatory Response Syndrome (SIRS), were evaluated for their ability to predict 30-day mortality and bacteraemia and for their ability to identify a low risk group, where blood culture may not be cost-effective and a high risk group where direct-from-blood PCR (dfbPCR) may be cost effective.

METHODS: Retrospective data from two Danish and an Israeli hospital with a total of 1816 patients were used to calculate the seven scores.

RESULTS: SF had higher Area Under the Receiver Operating curve than the clinical scores for prediction of mortality and bacteraemia, significantly so for MEDS, qSOFA and SIRS. For mortality predictions SF also had significantly higher area under the curve than SDR. In a low risk group identified by SF, consisting of 33% of the patients only 1.7% had bacteraemia and mortality was 4.2%, giving a cost of € 1976 for one positive result by blood culture. This was higher than the cost of € 502 of one positive dfbPCR from a high risk group consisting of 10% of the patients, where 25.3% had bacteraemia and mortality was 24.2%.

CONCLUSION: This may motivate a health economic study of whether resources spent on low risk blood cultures might be better spent on high risk dfbPCR.

Original languageEnglish
Article number864
JournalBMC Infectious Diseases
Volume21
Issue number1
ISSN1471-2334
DOIs
Publication statusPublished - 23 Aug 2021

Bibliographical note

© 2021. The Author(s).

Keywords

  • Bacteraemia
  • Decision support
  • Predictive models
  • Risk-based stratification
  • Sepsis

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