Model-based insulin sensitivity for early diagnosis of sepsis in critical care
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...
| Main Authors: | , , , |
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| Format: | Proceeding Paper |
| Language: | English |
| Published: |
2017
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/58199/ http://irep.iium.edu.my/58199/3/5.%20ASMIC2017_ModelBasedInsulin.pdf |
| _version_ | 1848785068810567680 |
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| author | Wan Shukeri, Wan Fadzlina Md Ralib, Azrina Jamaludin, Ummu Kulthum Mat Nor, Mohd Basri |
| author_facet | Wan Shukeri, Wan Fadzlina Md Ralib, Azrina Jamaludin, Ummu Kulthum Mat Nor, Mohd Basri |
| author_sort | Wan Shukeri, Wan Fadzlina |
| building | IIUM Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T16:47:16Z |
| format | Proceeding Paper |
| id | iium-58199 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T16:47:16Z |
| publishDate | 2017 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-581992017-08-29T06:31:04Z http://irep.iium.edu.my/58199/ Model-based insulin sensitivity for early diagnosis of sepsis in critical care Wan Shukeri, Wan Fadzlina Md Ralib, Azrina Jamaludin, Ummu Kulthum Mat Nor, Mohd Basri R Medicine (General) 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. 2017 Proceeding Paper NonPeerReviewed application/pdf en http://irep.iium.edu.my/58199/3/5.%20ASMIC2017_ModelBasedInsulin.pdf 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) http://msic.org.my/asmic2017/ |
| spellingShingle | R Medicine (General) Wan Shukeri, Wan Fadzlina Md Ralib, Azrina Jamaludin, Ummu Kulthum Mat Nor, Mohd Basri Model-based insulin sensitivity for early diagnosis of sepsis in critical care |
| title | Model-based insulin sensitivity for early diagnosis of sepsis
in critical care |
| title_full | Model-based insulin sensitivity for early diagnosis of sepsis
in critical care |
| title_fullStr | Model-based insulin sensitivity for early diagnosis of sepsis
in critical care |
| title_full_unstemmed | Model-based insulin sensitivity for early diagnosis of sepsis
in critical care |
| title_short | Model-based insulin sensitivity for early diagnosis of sepsis
in critical care |
| title_sort | model-based insulin sensitivity for early diagnosis of sepsis
in critical care |
| topic | R Medicine (General) |
| url | http://irep.iium.edu.my/58199/ http://irep.iium.edu.my/58199/ http://irep.iium.edu.my/58199/3/5.%20ASMIC2017_ModelBasedInsulin.pdf |