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Data-driven curation process for describing the blood glucose management in the intensive care unit

Author(s)
Robles Arévalo, Aldo; Maley, Jason H; Baker, Lawrence; da Silva Vieira, Susana M; da Costa Sousa, João M; Finkelstein, Stan; Mateo-Collado, Roselyn; Raffa, Jesse D; Celi, Leo Anthony; DeMichele, Francis; ... Show more Show less
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Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/
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Abstract
© 2021, The Author(s). Analysis of real-world glucose and insulin clinical data recorded in electronic medical records can provide insights into tailored approaches to clinical care, yet presents many analytic challenges. This work makes publicly available a dataset that contains the curated entries of blood glucose readings and administered insulin on a per-patient basis during ICU admissions in the Medical Information Mart for Intensive Care (MIMIC-III) database version 1.4. Also, the present study details the data curation process used to extract and match glucose values to insulin therapy. The curation process includes the creation of glucose-insulin pairing rules according to clinical expert-defined physiologic and pharmacologic parameters. Through this approach, it was possible to align nearly 76% of insulin events to a preceding blood glucose reading for nearly 9,600 critically ill patients. This work has the potential to reveal trends in real-world practice for the management of blood glucose. This data extraction and processing serve as a framework for future studies of glucose and insulin in the intensive care unit.
Date issued
2021
URI
https://hdl.handle.net/1721.1/133705
Department
Massachusetts Institute of Technology. Institute for Data, Systems, and Society; Harvard--MIT Program in Health Sciences and Technology. Laboratory for Computational Physiology; Massachusetts Institute of Technology. Institute for Medical Engineering & Science
Journal
Scientific Data
Publisher
Springer Science and Business Media LLC

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