J
Joon Lee
Researcher at University of Calgary
Publications - 126
Citations - 3451
Joon Lee is an academic researcher from University of Calgary. The author has contributed to research in topics: Intensive care & Intensive care unit. The author has an hindex of 32, co-authored 122 publications receiving 2735 citations. Previous affiliations of Joon Lee include Massachusetts Institute of Technology & Toronto Rehabilitation Institute.
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Journal ArticleDOI
Outcome of critically ill patients with acute kidney injury using the Acute Kidney Injury Network criteria.
Tal Mandelbaum,Daniel Scott,Joon Lee,Roger G. Mark,Atul Malhotra,Sushrut S. Waikar,Michael D. Howell,Daniel Talmor +7 more
TL;DR: It is found that in patients who developed acute kidney injury, urine output alone was a better mortality predictor than creatinine alone or the combination of both and re-evaluation of the Acute Kidney Injury Network staging criteria should be considered.
Journal ArticleDOI
Proton-pump Inhibitor Use Is Associated With Low Serum Magnesium Concentrations
John Danziger,Jeffrey H. William,Daniel J. Scott,Joon Lee,Li-wei H. Lehman,Roger G. Mark,Michael D. Howell,Leo Anthony Celi,Leo Anthony Celi,Kenneth J. Mukamal +9 more
TL;DR: Case reports of the association between PPI use and hypomagnesemia in those concurrently taking diuretics are verified and serum magnesium concentrations should be followed in susceptible individuals on chronic PPI therapy.
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Smart Devices for Older Adults Managing Chronic Disease: A Scoping Review
TL;DR: A scoping review of smart device-based research activities found self-monitoring, automated feedback, and patient education were commonly used as self-management support strategies and the impact on patient outcomes was consistent with studies that used cellular phones.
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Personalized Mortality Prediction Driven by Electronic Medical Data and a Patient Similarity Metric
TL;DR: It is proved that analyzing only similar patients leads to better outcome prediction performance than analyzing all available patients, and the trade-off between training data size and the degree of similarity between the training data and the index patient for whom prediction is to be made.
Journal ArticleDOI
Red cell distribution width improves the simplified acute physiology score for risk prediction in unselected critically ill patients.
Sabina Hunziker,Sabina Hunziker,Leo Anthony Celi,Leo Anthony Celi,Leo Anthony Celi,Joon Lee,Michael D. Howell,Michael D. Howell +7 more
TL;DR: RDW is a promising independent short- and long-term prognostic marker in ICU patients and significantly improves risk stratification of SAPS, and further research is needed to understand the pathophysiology underlying these effects.