Abstract #317: Computer Based Insulin Infusion Algorithm Impact on Glycemic Control in Critically Ill Patients

2017 ◽  
Vol 23 ◽  
pp. 92-93
Author(s):  
Maha Abu Kishk ◽  
Majdi Hamarshi
Keyword(s):  
Glycemic Control ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Insulin Infusion ◽  
Computer Based

CLINICAL COMPARISON OF TWO INSULIN INFUSION ALGORITHMS FOR GLYCEMIC CONTROL IN CRITICALLY ILL PATIENTS.

2006 ◽  
Vol 34 ◽  
pp. A12
Author(s):  
Tuhin K Roy ◽  
M Molly McMahon ◽  
Robert A Rizza ◽  
Mark T Keegan ◽  
Francis X Whalen ◽  
...  
Keyword(s):  
Glycemic Control ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Insulin Infusion ◽  
Clinical Comparison

scholarly journals Second pilot trials of the STAR-Liege protocol for tight glycemic control in critically ill patients

2012 ◽  
Vol 11 (1) ◽  
pp. 58 ◽  
Author(s):  
Sophie Penning ◽  
Aaron J Le Compte ◽  
Paul Massion ◽  
Katherine T Moorhead ◽  
Christopher G Pretty ◽  
...  
Keyword(s):  
Glycemic Control ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Tight Glycemic Control ◽  
Pilot Trials

Guideline-Concordant Insulin Infusion Initiation Among Critically Ill Patients With Sepsis

2021 ◽  
Author(s):  
Nicholas A. Bosch ◽  
Kathryn L. Fantasia ◽  
Katherine L. Modzelewski ◽  
Sara M. Alexanian ◽  
Allan J. Walkey
Keyword(s):  
Critically Ill ◽  
Critically Ill Patients ◽  
Insulin Infusion

Association Effects Of Comorbid Versus Uncomorbid Diabetes And Blood Glucose Concentrations On Short-term Outcomes In Patients With Critical Illness: A Real-World Study Based On Propensity Score Analyses

2020 ◽  
Author(s):  
Shan Lin ◽  
Shanhui Ge ◽  
Wanmei He ◽  
Mian Zeng
Keyword(s):  
Critical Illness ◽  
Glycemic Control ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Cox Model ◽  
Inverse Probability Weighting ◽  
Probability Weighting ◽  
Optimal Range ◽  
Short Term ◽  
Inverse Probability

Abstract Background: The effects of combined diabetes and glycemic control strategies on the short-term prognosis in patients with a critical illness are currently ambiguous. The objectives of our study were to determine whether comorbid diabetes affects short-term prognosis and the optimal range of glycemic control in critically ill patients.Methods: We performed this study with the critical care database. The primary outcomes were 28-day mortality in critically ill patients with comorbid diabetes and the optimal range of glycemic control. Association of comorbid diabetes with 28-day mortality was assessed by multivariable Cox regression model with inverse probability weighting. Smooth curves were applied to fit the association for glucose and 28-day mortality.Results: Of the 33,680 patients enrolled in the study, 8,701 (25.83%) had diabetic comorbidity. Cox model with inverse probability weighting showed that the 28-day mortality rate was reduced by 29% (HR=0.71, 95% CI 0.67-0.76) in the group with diabetes in comparison to the group without diabetes. The E value of 2.17 indicated robustness to unmeasured confounders. The effect of the association between comorbid diabetes and 28-day mortality was generally in line for all subgroup variables, significant interactions were observed for glucose on first day, admission type, and use of insulin or not (Interaction P <0.05). A V-shaped relationship was observed between glucose concentrations and 28-day mortality in patients without diabetes, with the lowest 28-day mortality corresponding to the glucose level was 101.75 mg/dl (95% CI 94.64-105.80 mg/dl); whereas in patients with comorbid diabetes, the effect of glucose concentration on 28-day mortality was structurally softer than in those with uncomorbid diabetes. Lastly, of all patients, hyperglycemia had the greatest deleterious effect on patients admitted to CSRU.Conclusions: Our study further confirmed the protective effect of comorbid diabetes on the short-term prognosis of critically ill patients, resulting in an approximately 29% reduction in 28-day mortality. Besides, we also demonstrated the personalized glycemic control strategy for critically ill patients. Lastly, clinicians should be aware of the occurrence and the prompt management of hyperglycemia in critically ill patients admitted to the CSRU.

The Long and Winding Road to Personalized Glycemic Control in the Intensive Care Unit

2019 ◽  
Vol 40 (05) ◽  
pp. 571-579
Author(s):  
Mayanka Tickoo
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Glycemic Control ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Physiological Stress ◽  
Close Monitoring ◽  
Physiological Stress Response ◽  
Downstream Effects ◽  
Personalized Approach

AbstractIn the critically ill adult, dysglycemia is a marker of disease severity and is associated with worse clinical outcomes. Close monitoring of glucose and use of insulin in critically ill patients have been done for more than 2 decades, but the appropriate target glycemic range in critically ill patients remains controversial. Physiological stress response, levels of inflammatory cytokines, nutritional intake, and level of mobility affect glycemic control, and a more personalized approach to patients with dysglycemia is warranted in critically ill intensive care unit (ICU) patients. We discuss the pathophysiology and downstream effects of altered glycemic response in critical illness, management of glycemic control in the ICU, and future strategies toward personalization of critical care glycemic management.

scholarly journals Understanding safety differently: developing a model of resilience in the use of intravenous insulin infusions in hospital in-patients—a feasibility study protocol

BMJ Open ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. e029997
Author(s):  
Mais Hasan Iflaifel ◽  
Rosemary Lim ◽  
Kath Ryan ◽  
Clare Crowley ◽  
Rick Iedema
Keyword(s):  
Blood Glucose ◽  
Phase I ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Insulin Infusion ◽  
University Hospitals ◽  
Glucose Levels ◽  
Oxford University ◽  
Intravenous Insulin ◽  
Blood Glucose Levels

BackgroundIntravenous insulin infusions are considered the treatment of choice for critically ill patients and non-critically ill patients with persistent raised blood glucose who are unable to eat, to achieve optimal blood glucose levels. The benefits of using intravenous insulin infusions as well as the problems experienced are well described in the scientific literature. Traditional approaches for improving patient safety have focused on identifying errors, understanding their causes and designing solutions to prevent them. Such approaches do not take into account the complex nature of healthcare systems, which cannot be controlled solely by following standards. An emerging approach called Resilient Healthcare proposes that, to improve safety, it is necessary to focus on how work can be performed successfully as well as how work has failed.Methods and analysisThe study will be conducted at Oxford University Hospitals NHS Foundation Trust and will involve three phases. Phase I: explore how work is imagined by analysing intravenous insulin infusion guidelines and conducting focus group discussions with guidelines developers, managers and healthcare practitioners. Phase II: explore the interplay between how work is imagined and how work is performed using mixed methods. Quantitative data will include blood glucose levels, insulin infusion rates, number of hypoglycaemic and hyperglycaemic events from patients’ electronic records. Qualitative data will include video reflexive ethnography: video recording healthcare practitioners using intravenous insulin infusions and then conducting reflexive meetings with them to discuss selected video footage. Phase III: compare findings from phase I and phase II to develop a model for using intravenous insulin infusions.Ethics and disseminationEthical approvals have been granted by the South Central—Oxford C Research Ethics Committee, Oxford University Hospitals NHS Foundation Trust and University of Reading. The results will be disseminated through presentations at appropriate conferences and meetings, and publications in peer-reviewed journals.

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