Development of a model-based clinical sepsis biomarker for critically ill patients

Jessica Lin, Jacquelyn D. Parente, J. Geoffrey Chase, Geoffrey M. Shaw, Amy J. Blakemore, Aaron J. LeCompte, Christopher Pretty, Normy N. Razak, Dominic S. Lee, Christopher E. Hann, Sheng Hui Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Sepsis occurs frequently in the intensive care unit (ICU) and is a leading cause of admission, mortality, and cost. Treatment guidelines recommend early intervention, however positive blood culture results may take up to 48 hours. Insulin sensitivity (SI) is known to decrease with worsening condition and could thus be used to aid diagnosis. Some glycemic control protocols are able to accurately identify insulin sensitivity in real-time. Receiver operator characteristic (ROC) curves and cut-off SI values for sepsis diagnosis were calculated for real-time model-based insulin sensitivity from glycemic control data of 36 patients with sepsis. Patients were identified as having sepsis based on a clinically validated sepsis score (ss) of 2 or higher (ss = 0-4 for increasing severity). A clinical biomarker was calculated from patient clinical data to maximize the discrimination between cohorts. Insulin sensitivity as a sepsis biomarker for diagnosis of severe sepsis achieves a 50% sensitivity, 76% specificity, 4.8% PPV, and 98.3% NPV at a SI cut-off value of 0.00013 L*mU min-1. A clinical biomarker combining SI, temperature, heart rate, respiratory rate, blood pressure, and their respective hourly rates of change achieves 73% sensitivity, 80% specificity, 8.4% PPV, and 99.2% NPV. Thus, a clinical biomarker provides an effective real-time negative predictive diagnostic for severe sepsis. Examination of both inter- and intra-patient statistical distribution of this biomarker and sepsis score show potential avenues to improve the positive predictive value.

Original languageEnglish
Title of host publication7th IFAC Symposium on Modelling and Control in Biomedical Systems (including Biological Systems) MCBMS'09 - Proceedings
Pages13-18
Number of pages6
EditionPART 1
DOIs
Publication statusPublished - 01 Dec 2009
Event7th IFAC Symposium on Modelling and Control in Biomedical Systems (including Biological Systems) MCBMS'09 - Aalborg, Denmark
Duration: 12 Aug 200914 Aug 2009

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
NumberPART 1
Volume7
ISSN (Print)1474-6670

Other

Other7th IFAC Symposium on Modelling and Control in Biomedical Systems (including Biological Systems) MCBMS'09
CountryDenmark
CityAalborg
Period12/08/0914/08/09

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All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

Cite this

Lin, J., Parente, J. D., Chase, J. G., Shaw, G. M., Blakemore, A. J., LeCompte, A. J., ... Wang, S. H. (2009). Development of a model-based clinical sepsis biomarker for critically ill patients. In 7th IFAC Symposium on Modelling and Control in Biomedical Systems (including Biological Systems) MCBMS'09 - Proceedings (PART 1 ed., pp. 13-18). (IFAC Proceedings Volumes (IFAC-PapersOnline); Vol. 7, No. PART 1). https://doi.org/10.3182/20090812-3-DK-2006.0076