The Sepsis-3 task force recommended the quick Sequential (Sepsis-Related) Organ Failure Assessment score for identifying patients with suspected infection who are at greater risk of poor outcomes, but many hospitals already use the National Early Warning Score to identify high-risk patients, irrespective of diagnosis. We sought to compare the performance of quick Sequential (Sepsis-Related) Organ Failure Assessment and National Early Warning Score in hospitalized, non-ICU patients with and without an infection.
Retrospective cohort study.
Large U.K. General Hospital.
Adults hospitalized between January 1, 2010, and February 1, 2016.
We applied the quick Sequential (Sepsis-Related) Organ Failure Assessment score and National Early Warning Score to 5,435,344 vital signs sets (241,996 hospital admissions). Patients were categorized as having no infection, primary infection, or secondary infection using International Classification of Diseases, 10th Edition codes. National Early Warning Score was significantly better at discriminating in-hospital mortality, irrespective of infection status (no infection, National Early Warning Score 0.831 [0.825–0.838] vs quick Sequential [Sepsis-Related] Organ Failure Assessment 0.688 [0.680–0.695]; primary infection, National Early Warning Score 0.805 [0.799–0.812] vs quick Sequential [Sepsis-Related] Organ Failure Assessment 0.677 [0.670–0.685]). Similarly, National Early Warning Score performed significantly better in all patient groups (all admissions, emergency medicine admissions, and emergency surgery admissions) for all outcomes studied. Overall, quick Sequential (Sepsis-Related) Organ Failure Assessment performed no better, and often worse, in admissions with infection than without.
The National Early Warning Score outperforms the quick Sequential (Sepsis-Related) Organ Failure Assessment score, irrespective of infection status. These findings suggest that quick Sequential (Sepsis-Related) Organ Failure Assessment should be reevaluated as the system of choice for identifying non-ICU patients with suspected infection who are at greater risk of poor outcome.
1Centre for Healthcare Modelling & Informatics, School of Computing, University of Portsmouth, Portsmouth, United Kingdom.
2Centre of Postgraduate Medical Research and Education (CoPMRE), Faculty of Health and Social Sciences, University of Bournemouth, Bournemouth, United Kingdom.
3Department of Research & Innovation, Portsmouth Hospitals NHS Trust, Portsmouth, United Kingdom.
4Acute Medical Unit, Department of Medicine, Hampshire Hospitals NHS Foundation Trust, Winchester, United Kingdom.
5Acute Medical Unit, Department of Medicine, Portsmouth Hospitals NHS Trust, Portsmouth, United Kingdom.
This work was performed at Portsmouth Hospitals National Health Service Trust & University of Portsmouth.
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Drs. Redfern’s and Meredith's and Professor Prytherch’s institutions received funding from the National Institute for Health Research (project relating to research into nurse staffing and vital signs observations commenced in April 2015) and from Wellcome Trust/Department of Health (project relating to predicting intensive care admission (Hospital Alerting via Electronic Noticeboard [HAVEN] project) commenced August 2015). Professors Smith and Prytherch, and Dr. Meredith received other support from Vitalpac (the system used to collect vital signs data in the submitted research project) as a collaborative development of The Learning Clinic Ltd (TLC) and Portsmouth Hospitals National Health Service (NHS) Trust. At the time of the research, Portsmouth Hospitals NHS Trust (PHT) had a royalty agreement with TLC to pay for the use of PHT intellectual property within the Vitalpac product. Drs. Meredith and Schmidt are employed by PHT. Professor Smith was an employee of PHT until March 31, 2011. Professor Prytherch was an employee of PHT until July 31, 2016. Until October 2015, Dr. Schmidt and the wives of Professors Smith and Prytherch were minority shareholders in TLC. Until October 2015, Dr. Schmidt and Professors Smith and Prytherch were unpaid research advisors to TLC and received reimbursement of travel expenses from TLC for attending symposia in the United Kingdom. Professor Smith is a member of the Royal College of Physicians of London’s National Early Warning Score (NEWS) Development and Implementation Group, which developed NEWS. Professor Prytherch assisted the Royal College of Physicians of London in the analysis of data validating NEWS. Dr. Inada-Kim is the U.K. National Clinical Advisor for Sepsis and one of the authors of the publication describing the use of routine data to define and measure suspicion of sepsis that is used in the current research. Dr. Inada-Kim is also U.K. National Clinical Advisor to the NHS for deterioration. Dr. Inada-Kim received funding from Relias (educational seminar), and he disclosed that his institution is paid for his time to lead the region on deterioration and sepsis care.
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