Abstract
Objective
To develop and test an automated surveillance algorithm (sepsis “sniffer”) for the
detection of severe sepsis and monitoring failure to recognize and treat severe sepsis
in a timely manner.
Patients and Methods
We conducted an observational diagnostic performance study using independent derivation
and validation cohorts from an electronic medical record database of the medical intensive
care unit (ICU) of a tertiary referral center. All patients aged 18 years and older
who were admitted to the medical ICU from January 1 through March 31, 2013 (N=587),
were included. The criterion standard for severe sepsis/septic shock was manual review
by 2 trained reviewers with a third superreviewer for cases of interobserver disagreement.
Critical appraisal of false-positive and false-negative alerts, along with recursive
data partitioning, was performed for algorithm optimization.
Results
An algorithm based on criteria for suspicion of infection, systemic inflammatory response
syndrome, organ hypoperfusion and dysfunction, and shock had a sensitivity of 80%
and a specificity of 96% when applied to the validation cohort. In order, low systolic
blood pressure, systemic inflammatory response syndrome positivity, and suspicion
of infection were determined through recursive data partitioning to be of greatest
predictive value. Lastly, 117 alert-positive patients (68% of the 171 patients with
severe sepsis) had a delay in recognition and treatment, defined as no lactate and
central venous pressure measurement within 2 hours of the alert.
Conclusion
The optimized sniffer accurately identified patients with severe sepsis that bedside
clinicians failed to recognize and treat in a timely manner.
Abbreviations and Acronyms:
CPOE (computerized physician order entry), CVP (central venous pressure), DNR/DNI (do-not-resuscitate/do-not-intubate), ED (emergency department), EGDT (early goal-directed therapy), EMR (electronic medical record), ICU (intensive care unit), LOS (length of stay), NPV (negative predictive value), PPV (positive predictive value), SIRS (systemic inflammatory response syndrome), SSC (Surviving Sepsis Campaign)To read this article in full you will need to make a payment
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Article Info
Publication History
Published online: January 06, 2015
Footnotes
Grant Support: This work was supported by grant 1C1CMS330964-01-00 from the Center for Medicare and Medicaid Innovation (Health Care Innovation Award “Patient Centered Cloud-based Electronic System: Ambient Warning and Response Evaluation [ProCCESs AWARE])”, grant UL1 TR 000135 from the National Center for Advancing Translational Sciences to the Mayo Clinic Center for Translational Science Activities, and doctoral dissertation grant 1 R36 HS 022799-01 from the Agency for Healthcare Research and Quality (A.M.H.).
Potential Competing Interests: AWARE is patent pending (US 2010/0198622, 12/697861, PCT/US2010/022750). Sepsis sniffer is patent number 20110137852. Drs Herasevich, Gajic, and Pickering and Mayo Clinic have a financial interest relating to licensed technology described in this article. This research has been reviewed by the Mayo Clinic Conflict of Interest Review Board and is being conducted in compliance with Mayo Clinic Conflict of Interest Policies.
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© 2015 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.
