Data-driven curation process for describing the blood glucose management in the intensive care unit
Name
s41597-021-00864-4.pdf
Description
Published version
Size
1.99 MB
Format
Adobe PDF
Checksum (MD5)
2a7a9c7a67bb07276d245a016df58d09
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
Date Issued
2021
Journal
Scientific Data
Publisher
Springer Science and Business Media LLC
Version
Final published version
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.
MIT 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
Terms of Use
Creative Commons Attribution 4.0 International license
Persistent DSpace Link
DOI of Published Version
10.1038/s41597-021-00864-4
https://doi.org/10.1038/s41597-021-00864-4
