https://scholars.lib.ntu.edu.tw/handle/123456789/636431
標題: | The Skeletal Oncology Research Group Machine Learning Algorithm (SORG-MLA) for predicting prolonged postoperative opioid prescription after total knee arthroplasty: an international validation study using 3,495 patients from a Taiwanese cohort | 作者: | Tsai, Cheng-Chen CHUAN-CHING HUANG Lin, Ching-Wei Ogink, Paul T Su, Chih-Chi Chen, Shin-Fu Yen, Mao-Hsu Verlaan, Jorrit-Jan Schwab, Joseph H CHEN-TI WANG Groot, Olivier Q MING-HSIAO HU HONGSEN CHIANG |
關鍵字: | Acetaminophen use; Asian group; Machine learning; Prediction model; Prolonged opioid use; Total knee arthroplasty | 公開日期: | 5-七月-2023 | 卷: | 24 | 期: | 1 | 來源出版物: | BMC musculoskeletal disorders | 摘要: | Preoperative prediction of prolonged postoperative opioid use (PPOU) after total knee arthroplasty (TKA) could identify high-risk patients for increased surveillance. The Skeletal Oncology Research Group machine learning algorithm (SORG-MLA) has been tested internally while lacking external support to assess its generalizability. The aims of this study were to externally validate this algorithm in an Asian cohort and to identify other potential independent factors for PPOU. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/636431 | ISSN: | 1471-2474 | DOI: | 10.1186/s12891-023-06667-5 |
顯示於: | 醫學系 |
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