IIUM Repository

Model-based insulin sensitivity for early diagnosis of sepsis in critical care

Wan Shukeri, Wan Fadzlina and Md Ralib, Azrina and Jamaludin, Ummu Kulthum and Mat Nor, Mohd Basri (2017) Model-based insulin sensitivity for early diagnosis of sepsis in critical care. In: Annual Scientific Meeting on Intensive Care (ASMIC 2017) : 1st Asian Pediatric Mechanical Ventilation Forum, 18th-20th August 2017, Kuala Lumpur. (Unpublished)

[img] PDF - Published Version
Restricted to Repository staff only

Download (3MB) | Request a copy


OBJECTIVES To determine the diagnostic value of model-based insulin sensitivity (SI) as a new sepsis biomarker in critically ill patients, and compare its performance to classical inflammatory parameters. METHODS We monitored hourly SI levels in septic (n=19) and non-septic (n=19) critically ill patients in a 24-hour follow-up study. Patients with type I or type II diabetes mellitus were excluded. SI levels were calculated by a validated glycemic control software, STAR TGC (Stochastic TARgeted Tight Glycemic Controller) (Christchurch, NZ). STAR TGC uses a physiological glucose-insulin system model coupled with stochastic models that capture SI variability in real time. RESULTS The median SI levels were lower in the sepsis group than in the non-sepsis group (1.9 x 10-4 L/mU/min vs 3.7 x 10-4 L/mU/min, P <0.0001). The areas under the receiver operating characteristic curve (AUROC) of the model-based SI for distinguishing non-sepsis from sepsis was 0.911, superior to white cells count (AUROC 0.611) and temperature (AUROC 0.618). The optimal cut-off value of the test was 2.9 x 10-4 L/mU/min. At this cut-off value, the sensitivity and specificity was 88.9% and 84.2%, respectively. The positive predictive value was 84.2%, while the negative predictive value was 88.9%. CONCLUSION The early and relevant decrease of SI in sepsis suggests that it might be a promising novel biomarker of sepsis in critical care. Low SI is diagnostic of sepsis, while high SI rules out sepsis, and these may be determined non-invasively in real time from glycemic control protocol data.

Item Type: Conference or Workshop Item (Speech/Talk)
Additional Information: 3934/58199
Uncontrolled Keywords: insulin sensitivity, early diagnosis, sepsis, critical care
Subjects: R Medicine > R Medicine (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Medicine > Department of Anaesthesiology & Intensive Care
Depositing User: Prof Azrina Md Ralib
Date Deposited: 29 Aug 2017 14:31
Last Modified: 29 Aug 2017 14:31
URI: http://irep.iium.edu.my/id/eprint/58199

Actions (login required)

View Item View Item


Downloads per month over past year