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

• Published in: Scientific data Vol. 8; no. 1; p. 80
• Main Authors: 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
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 10.03.2021; Nature Publishing Group; Nature Portfolio
• Subjects: 631/114/1314; 631/114/2164; 692/308/409; Blood glucose; Blood Glucose - analysis; Data Curation; Data Descriptor; Electronic Health Records; Electronic medical records; Glucose; Humanities and Social Sciences; Humans; Insulin; Insulin - analysis; Intensive care; Intensive Care Units; Medical records; multidisciplinary; Patients; Science; Science (multidisciplinary)
• ISSN: 2052-4463; 2052-4463
• DOI: 10.1038/s41597-021-00864-4

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. Measurement(s) Blood Glucose • insulin (human) Technology Type(s) glucose analyzer • glucometer • Electronic Medical Record Factor Type(s) glucose readings • insulin inputs Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.13564187