scholarly journals A fast and accurate diagnostic test for severe sepsis using model-based insulin sensitivity and clinical data

Critical Care ◽  
2010 ◽  
Vol 14 (Suppl 2) ◽  
pp. P13
Author(s):  
JD Parente ◽  
D Lee ◽  
J Lin ◽  
JG Chase ◽  
GM Shaw
2021 ◽  
Vol 20 (2) ◽  
Author(s):  
Wan Fadzlina Wan Muhd Shukeri ◽  
Mohd Basri Mat-Nor ◽  
Azrina Md. Ralib ◽  
Ummu Kulthum Jamaludin

INTRODUCTION: Currently, there is a lack of real-time biomarker to diagnose sepsis. Insulin sensitivity (SI) may be determined in real-time using mathematical glucose-insulin models, but its effectiveness as a diagnostic test of sepsis remains unexplored. We aimed to explore the diagnostic value of model-based SI as a new biomarker of sepsis in a mixed cohort of diabetic and non-diabetic patients newly admitted to the intensive care unit (ICU). MATERIALS AND METHODS: In this cross-sectional study, we analysed SI levels derived from the Intensive[1]Control-of-Insulin-Nutrition-Glucose model in septic (n=45) and non-septic (n = 41) patients upon their ICU admission. The diagnostic value of model-based SI for sepsis was determined through analysis of the area under the curve (AUC) of the receiver operating characteristic curve. RESULTS: Baseline SI levels were significantly lower in patients with sepsis than those without sepsis (0.560 (SD=0.676) vs. 1.097 (SD=1.473) x 10-4 L/mU/min, P = 0.037). However, the AUC of 0.588 revealed that model-based SI was a poor diagnostic test of sepsis in the mixed cohort of diabetics and non-diabetics. In a separate analysis among the non-diabetics (n=19), model-based SI predicted sepsis with clinically valid performance (AUC 0.911). CONCLUSION: Presence of sepsis significantly reduced SI in the critically ill patients but a low SI could predict sepsis only in the non-diabetic cohort.


2017 ◽  
Vol 32 ◽  
pp. 112-123
Author(s):  
Fatanah M. Suhaimi ◽  
J. Geoffrey Chase ◽  
Christopher G. Pretty ◽  
Geoffrey M. Shaw ◽  
Normy N. Razak ◽  
...  

2005 ◽  
Vol 3 (3) ◽  
pp. 137-145 ◽  
Author(s):  
M. A. Hillman ◽  
R. A. Wilke ◽  
S. H. Yale ◽  
H. J. Vidaillet ◽  
M. D. Caldwell ◽  
...  

2018 ◽  
Vol 51 (15) ◽  
pp. 311-316 ◽  
Author(s):  
Vincent Uyttendaele ◽  
Jennifer L. Dickson ◽  
Sophie Morton ◽  
Geoffrey Shaw ◽  
Thomas Desaive ◽  
...  

2015 ◽  
Vol 48 (20) ◽  
pp. 372-376 ◽  
Author(s):  
Fatanah M. Suhaimi ◽  
J. Geoffrey Chase ◽  
Christopher G. Pretty ◽  
Geoffrey M. Shaw ◽  
Normy Razak ◽  
...  

Brachytherapy ◽  
2014 ◽  
Vol 13 ◽  
pp. S69-S70
Author(s):  
Dorin Todor ◽  
Mitchell S. Anscher ◽  
Michael P. Hagan ◽  
Sebastian Kaden ◽  
Frank-Andre Siebert
Keyword(s):  

2012 ◽  
Vol 45 (18) ◽  
pp. 349-354
Author(s):  
Ummu K. Jamaludin ◽  
Paul D. Docherty ◽  
J. Geoffrey Chase ◽  
Aaron Le Compte ◽  
Geoffrey M. Shaw

2014 ◽  
Vol 47 (3) ◽  
pp. 11595-11598
Author(s):  
J Homlok ◽  
J G Chase ◽  
B Benyó

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