Insulin sensitivity as a model-based marker for sepsis diagnosis

Fatanah M. Suhaimi, J. Geoffrey Chase, Christopher G. Pretty, Geoffrey M. Shaw, Normy Razak, Ummu Jamaludin

Research output: Contribution to journalConference article

2 Citations (Scopus)


Sepsis is highly associated with microcirculatory dysfunction, which normally results in organ failure and increased risk of death. Importantly, early goal-directed therapy observed lower mortality rates in septic shock patients compared to those assigned to standard therapy. Currently, it is almost impossible to diagnose a patient at the onset of sepsis due to the lack of real-time metrics with high sensitivity and specificity. Patient condition is mostly determined by clinician experience and observation of patient reaction to treatment. In this study, a model-based insulin sensitivity profile is used to identify the relation between individual metabolic conditions to their sepsis status. The hour-to-hour variation of insulin sensitivity is highly independent of the treatment received by the patient and may represent a metabolic status for real-time diagnosis of sepsis. The hour-to-hour variation of insulin sensitivity profile is analyzed with sepsis score calculated according to the definition provided by ACCP/SCCM. P-values of various sepsis score group are computed using Mann-Whitney test. Cumulative distribution function of insulin sensitivity shows separation between different sepsis score and more distinguishable at a higher sepsis score compared to the lower sepsis score.

Original languageEnglish
Pages (from-to)372-376
Number of pages5
Issue number20
Publication statusPublished - 01 Sep 2015
Event9th IFAC Symposium on Biological and Medical Systems, BMS 2015 - Berlin, Germany
Duration: 31 Aug 201502 Sep 2015


All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

Cite this

Suhaimi, F. M., Chase, J. G., Pretty, C. G., Shaw, G. M., Razak, N., & Jamaludin, U. (2015). Insulin sensitivity as a model-based marker for sepsis diagnosis. IFAC-PapersOnLine, 28(20), 372-376.