Literature DB >> 19885212

Model-based insulin sensitivity as a sepsis diagnostic in critical care.

Amy Blakemore1, Sheng-Hui Wang, Aaron Le Compte, Geoffrey M Shaw, Xing-Wei Wong, Jessica Lin, Thomas Lotz, Christopher E Hann, J Geoffrey Chase.   

Abstract

BACKGROUND: Timely diagnosis and treatment of sepsis in critical care require significant clinical effort, experience, and resources. Insulin sensitivity is known to decrease with worsening condition and could thus be used to aid diagnosis. Some glycemic control protocols are able to identify insulin sensitivity in real time.
METHODS: Receiver operating characteristic curves and cutoff insulin sensitivity values for diagnosing sepsis were calculated for model-based insulin sensitivity (S(I)) and a simpler metric (SS(I)) that was estimated from glycemic control data of 30 patients with sepsis and can be calculated in real time without use of a computer. Results were compared to the insulin sensitivity profiles of a general intensive care unit population of 113 patients without sepsis and 30 patients with sepsis, comprising a total of 26,453 patient hours. Patients with sepsis were identified as having sepsis based on a sepsis score (ss) of 3 or higher (ss = 0 - 4 for increasing severity). Patients with type I or type II diabetes were excluded. Ethics approval for this study was granted by the South Island Regional Ethics Committee.
RESULTS: Receiver operating characteristic cutoff values of S(I) = 8 x 10-5 liter mU(-1) min(-1) and SS(I) = 2.8 x 10-4 liter mU(-1) min(-1) were determined for ss > or = 3. The model-based S(I) fell below this value in 15% of all patient hours. The S(I) test had a negative predictive value of 99.8%. The test sensitivity was 78% and specificity was 82%. However, the positive predictor value was 2.8%. Slightly lower sensitivity (68.8%) and specificity (81.7%), but equally good negative prediction (99.7%), were obtained for the estimated SS(I).
CONCLUSIONS: Insulin sensitivity provides a negative predictive diagnostic for sepsis. High insulin sensitivity rules out sepsis for the majority of patient hours and may be determined noninvasively in real time from glycemic control protocol data. Low insulin sensitivity is not an effective diagnostic, as it can equally mark the presence of sepsis or other conditions.

Entities:  

Keywords:  ICU; SPRINT; blood glucose; critical care; diagnosis; hyperglycemia; insulin sensitivity retrospective studies; sepsis

Year:  2008        PMID: 19885212      PMCID: PMC2769723          DOI: 10.1177/193229680800200317

Source DB:  PubMed          Journal:  J Diabetes Sci Technol        ISSN: 1932-2968


  31 in total

1.  Integral-based parameter identification for long-term dynamic verification of a glucose-insulin system model.

Authors:  Christopher E Hann; J Geoffrey Chase; Jessica Lin; Thomas Lotz; Carmen V Doran; Geoffrey M Shaw
Journal:  Comput Methods Programs Biomed       Date:  2005-03       Impact factor: 5.428

Review 2.  2001 SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference.

Authors:  Mitchell M Levy; Mitchell P Fink; John C Marshall; Edward Abraham; Derek Angus; Deborah Cook; Jonathan Cohen; Steven M Opal; Jean-Louis Vincent; Graham Ramsay
Journal:  Crit Care Med       Date:  2003-04       Impact factor: 7.598

3.  Multicentric, randomized, controlled trial to evaluate blood glucose control by the model predictive control algorithm versus routine glucose management protocols in intensive care unit patients.

Authors:  Johannes Plank; Jan Blaha; Jeremy Cordingley; Malgorzata E Wilinska; Ludovic J Chassin; Cliff Morgan; Stephen Squire; Martin Haluzik; Jaromir Kremen; Stepan Svacina; Wolfgang Toller; Andreas Plasnik; Martin Ellmerer; Roman Hovorka; Thomas R Pieber
Journal:  Diabetes Care       Date:  2006-02       Impact factor: 19.112

4.  Targeted glycemic reduction in critical care using closed-loop control.

Authors:  J Geoffrey Chase; Geoffrey M Shaw; Jessica Lin; Carmen V Doran; Chris Hann; Thomas Lotz; Graeme C Wake; Bob Broughton
Journal:  Diabetes Technol Ther       Date:  2005-04       Impact factor: 6.118

5.  Implementation of a tight glycaemic control protocol using a web-based insulin dose calculator.

Authors:  A N Thomas; A E Marchant; M C Ogden; S Collin
Journal:  Anaesthesia       Date:  2005-11       Impact factor: 6.955

6.  Effect of hyperglycemia and hyperinsulinemia on the response of IL-6, TNF-alpha, and FFAs to low-dose endotoxemia in humans.

Authors:  Rikke Krogh-Madsen; Kirsten Møller; Flemming Dela; Gitte Kronborg; Sune Jauffred; Bente Klarlund Pedersen
Journal:  Am J Physiol Endocrinol Metab       Date:  2004-01-13       Impact factor: 4.310

7.  Mechanisms of insulin resistance during acute endotoxemia.

Authors:  A Virkamäki; H Yki-Järvinen
Journal:  Endocrinology       Date:  1994-05       Impact factor: 4.736

Review 8.  Stress-hyperglycemia, insulin and immunomodulation in sepsis.

Authors:  Paul E Marik; Murugan Raghavan
Journal:  Intensive Care Med       Date:  2004-02-26       Impact factor: 17.440

9.  Implementation of a safe and effective insulin infusion protocol in a medical intensive care unit.

Authors:  Philip A Goldberg; Mark D Siegel; Robert S Sherwin; Joshua I Halickman; Michelle Lee; Valerie A Bailey; Sandy L Lee; James D Dziura; Silvio E Inzucchi
Journal:  Diabetes Care       Date:  2004-02       Impact factor: 19.112

10.  Tight glycaemic control: a prospective observational study of a computerised decision-supported intensive insulin therapy protocol.

Authors:  Rob Shulman; Simon J Finney; Caoimhe O'Sullivan; Paul A Glynne; Russell Greene
Journal:  Crit Care       Date:  2007       Impact factor: 9.097

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  9 in total

1.  Interface design and human factors considerations for model-based tight glycemic control in critical care.

Authors:  Logan Ward; James Steel; Aaron Le Compte; Alicia Evans; Chia-Siong Tan; Sophie Penning; Geoffrey M Shaw; Thomas Desaive; J Geoffrey Chase
Journal:  J Diabetes Sci Technol       Date:  2012-01-01

2.  Data entry errors and design for model-based tight glycemic control in critical care.

Authors:  Logan Ward; James Steel; Aaron Le Compte; Alicia Evans; Chia-Siong Tan; Sophie Penning; Geoffrey M Shaw; Thomas Desaive; J Geoffrey Chase
Journal:  J Diabetes Sci Technol       Date:  2012-01-01

3.  Estimating Increased EGP During Stress Response in Critically Ill Patients.

Authors:  Jennifer J Ormsbee; Jennifer L Knopp; J Geoffrey Chase
Journal:  J Diabetes Sci Technol       Date:  2020-06-01

4.  DISTq: An Iterative Analysis of Glucose Data for Low-Cost, Real-Time and Accurate Estimation of Insulin Sensitivity.

Authors:  Paul D Docherty; J Geoffrey Chase; Thomas Lotz; Christopher E Hann; Geoffrey M Shaw; Juliet E Berkeley; J I Mann; Kirsten McAuley
Journal:  Open Med Inform J       Date:  2009-12-02

5.  Validation of a model-based virtual trials method for tight glycemic control in intensive care.

Authors:  J Geoffrey Chase; Fatanah Suhaimi; Sophie Penning; Jean-Charles Preiser; Aaron J Le Compte; Jessica Lin; Christopher G Pretty; Geoffrey M Shaw; Katherine T Moorhead; Thomas Desaive
Journal:  Biomed Eng Online       Date:  2010-12-14       Impact factor: 2.819

6.  Physiological modeling, tight glycemic control, and the ICU clinician: what are models and how can they affect practice?

Authors:  J Geoffrey Chase; Aaron J Le Compte; J-C Preiser; Geoffrey M Shaw; Sophie Penning; Thomas Desaive
Journal:  Ann Intensive Care       Date:  2011-05-05       Impact factor: 6.925

7.  Increased FGF21 plasma levels in humans with sepsis and SIRS.

Authors:  Karim Gariani; Geneviève Drifte; Irène Dunn-Siegrist; Jérôme Pugin; François R Jornayvaz
Journal:  Endocr Connect       Date:  2013-09-17       Impact factor: 3.335

8.  Estimating Enhanced Endogenous Glucose Production in Intensive Care Unit Patients with Severe Insulin Resistance.

Authors:  Anane Yahia; Ákos Szlávecz; Jennifer L Knopp; Normy Norfiza Abdul Razak; Asma Abu Samah; Geoff Shaw; J Geoffrey Chase; Balazs Benyo
Journal:  J Diabetes Sci Technol       Date:  2021-06-02

9.  Levels and Diagnostic Value of Model-based Insulin Sensitivity in Sepsis: A Preliminary Study.

Authors:  Wan Fadzlina Wan Muhd Shukeri; Mohd Basri Mat-Nor; Ummu Kulthum Jamaludin; Fatanah Suhaimi; Normy Norafiza Abd Razak; Azrina Md Ralib
Journal:  Indian J Crit Care Med       Date:  2018-06
  9 in total

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