Real-world characterization of blood glucose control and insulin use in the intensive care unit

The heterogeneity of critical illness complicates both clinical trial design and real-world management. This complexity has resulted in conflicting evidence and opinion regarding the optimal management in many intensive care scenarios. Understanding this heterogeneity is essential to tailoring manag...

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Bibliographic Details
Main Authors: Baker, Lawrence (Author), Maley, Jason H. (Author), Arévalo, Aldo (Author), DeMichele, Francis (Author), Mateo-Collado, Roselyn (Author), Finkelstein, Stan (Author), Celi, Leo Anthony G. (Author)
Other Authors: Harvard University- (Contributor), Harvard- (Contributor)
Format: Article
Language:English
Published: Springer Science and Business Media LLC, 2020-11-05T21:23:22Z.
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Summary:The heterogeneity of critical illness complicates both clinical trial design and real-world management. This complexity has resulted in conflicting evidence and opinion regarding the optimal management in many intensive care scenarios. Understanding this heterogeneity is essential to tailoring management to individual patients. Hyperglycaemia is one such complication in the intensive care unit (ICU), accompanied by decades of conflicting evidence around management strategies. We hypothesized that analysis of highly-detailed electronic medical record (EMR) data would demonstrate that patients vary widely in their glycaemic response to critical illness and response to insulin therapy. Due to this variability, we believed that hyper- and hypoglycaemia would remain common in ICU care despite standardised approaches to management. We utilized the Medical Information Mart for Intensive Care III v1.4 (MIMIC) database. We identified 19,694 admissions between 2008 and 2012 with available glucose results and insulin administration data. We demonstrate that hyper- and hypoglycaemia are common at the time of admission and remain so 1 week into an ICU admission. Insulin treatment strategies vary significantly, irrespective of blood glucose level or diabetic status. We reveal a tremendous opportunity for EMR data to guide tailored management. Through this work, we have made available a highly-detailed data source for future investigation.