TiME OUT: Time-specific machine-learning evaluation to optimize ultramassive transfusion

From the Department of Trauma and Surgical Critical Care (C.H.M., J.N., T.S., J.G., J.D.S., J.S., C.D., C.N., R.N.S.), Grady Health System; Department of Surgery (C.H.M., T.S., J.G., J.D.S., J.S., C.D., J.L., C.M.C., R.N.S.), Emory University School of Medicine; Department of Behavioral, Social and Health Sciences (C.H.M., R.N.S.), Rollins School of Public Health, Emory University; Department of Surgery (J.N.), Morehouse School of Medicine; Department of Operations Research (A.E.), Georgia Institute of Technology, Atlanta, Georgia; Department of Biomedical Engineering (N.V.), University of Texas at Austin, Austin, Texas; and Department of Surgery and Emory Critical Care Center (J.L., C.M.C.), Emory University School of Medicine, Atlanta, Georgia.

Submitted: August 20, 2023, Revised: October 6, 2023, Accepted: October 16, 2023, Published online: November 13, 2023.

This study was a presented as a brief oral presentation at AAST in Anaheim, CA on September 23, 2023.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text, and links to the digital files are provided in the HTML text of this article on the journal’s Web site (www.jtrauma.com).

Address for correspondence: Courtney H. Meyer, MD, MPH, Emory University School of Medicine, Glen Memorial Building, 69 Jesse Hill Jr. Drive SE, Suite 102, Atlanta, GA 30303; email: [email protected].

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