Predictors of new persistent opioid use after surgery in adults

• Published in: ANESTHESIOLOGY AND PERIOPERATIVE SCIENCE Vol. 3; no. 1; pp. 2 - 11
• Main Authors: Gessner, Kathryn H., Preisser, John S., Pfaff, Emily, Wang, Rujin, Walters, Kellie, Bradford, Robert, Clark, Marshall, Ehlers, Mark, Nielsen, Matthew
• Format: Journal Article
• Language: English
• Published: Singapore Springer Nature Singapore 01.01.2025; Springer
• Subjects: Anesthesiology; Critical Care Medicine; Intensive; Medicine; Medicine & Public Health; Monte-Carlo cross-validation; Neurosciences; Opioid dependency; Original Research; Pharmacology/Toxicology; Post-operative pain; Prediction modeling; Semantic technology; Surgery; Post-operative pain; Opioid dependency; Prediction modeling; Monte-Carlo cross-validation; Semantic technology

Purpose Persistent opioid use is one of the most common post-operative complications. Identification of at-risk patients pre-operatively is key to reducing post-operative opioid use. We sought to develop a predictive model for persistent post-operative opioid used and to determine if geographic fact...