Analysis and development of risk prediction models for chronic opioid use after surgery: a cohort study using the nationwide database

Background: Chronic opioid use has become a socioeconomic as well as a medical problem. This study aimed to identify risk factors and develop prediction models for postoperative chronic opioid use (PCOU).Methods: This retrospective cohort study used data from the Korean National Health Insurance Ser...

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Veröffentlicht in:	Korean journal of anesthesiology Jg. 78; H. 5; S. 429 - 442
Hauptverfasser:	Kim, Jonghae, Yang, Hyun-Lim, Kim, Eugene, Lee, Hyung-Chul, Yoon, Hyun-Kyu, Kim, Yun Jin, Kim, Kyu-Nam, Kim, Ji-Yoon, Sung, Jeong Min, Lee, Tagkeun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Korea (South) Korean Society of Anesthesiologists 01.10.2025 대한마취통증의학회
Schlagworte:	Adolescent Adult Aged Analgesics, Opioid - administration & dosage Analgesics, Opioid - adverse effects Child Cohort Studies Databases, Factual - trends dependence, opioid Female gradient boosting algorithms Humans Machine Learning Male Middle Aged Opioid-Related Disorders - diagnosis Opioid-Related Disorders - epidemiology Opioid-Related Disorders - etiology Pain, Postoperative - diagnosis Pain, Postoperative - drug therapy Pain, Postoperative - epidemiology postoperative period prediction methods, machine Republic of Korea - epidemiology Retrospective Studies Risk Assessment - methods Risk Factors surgical procedures, operative Young Adult 마취과학 Republic of Korea Gradient boosting algorithms Dependence, opioid Prediction methods, machine Surgical procedures, operative Postoperative period Machine learning
ISSN:	2005-6419, 2005-7563, 2005-7563
Online-Zugang:	Volltext
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