Jacqueline C Stocking, Sandra L Taylor, Sili Fan, Theodora Wingert, Christiana Drake, J Matthew Aldrich, Michael K Ong, Alpesh N Amin, Rebecca A Marmor, Laura Godat, Maxime Cannesson, Michael A Gropper, Garth H Utter, Christian E Sandrock, Christian Bime, Jarrod Mosier, Vignesh Subbian, Jason Y Adams, Nicholas J Kenyon, Timothy E Albertson, Joe G N Garcia, Ivo Abraham
BACKGROUND: Postoperative respiratory failure (PRF) is associated with increased hospital charges and worse patient outcomes. Reliable prediction models can help to guide postoperative planning to optimize care, to guide resource allocation, and to foster shared decision-making with patients. RESEARCH QUESTION: Can a predictive model be developed to accurately identify patients at high risk of PRF? STUDY DESIGN AND METHODS: In this single-site proof-of-concept study, we used structured query language to extract, transform, and load electronic health record data from 23,999 consecutive adult patients admitted for elective surgery (2014-2021)...
December 2023: CHEST Crit Care