医学
布里氏评分
足踝手术
Pacu公司
接收机工作特性
置信区间
外科
回顾性队列研究
队列
麻醉
脚踝
内科学
人工智能
计算机科学
作者
Tim T. H. Jen,Janny Xue Chen Ke,Kevin Wing,Justine Denomme,Daniel I. McIsaac,Shih-Chieh Huang,Ronald M Ree,Christopher Prabhakar,Stephan Schwarz,Cynthia H. Yarnold
标识
DOI:10.1016/j.bja.2022.03.030
摘要
BackgroundRebound pain occurs after up to 50% of ambulatory surgeries involving regional anaesthesia. To assist with risk stratification, we developed a model to predict severe rebound pain after foot and ankle surgery involving single-shot popliteal sciatic nerve block.MethodsAfter ethics approval, we performed a single-centre retrospective cohort study. Patients undergoing lower limb surgery with popliteal sciatic nerve block from January 2016 to November 2019 were included. Exclusion criteria were uncontrolled pain in the PACU, use of a perineural catheter, or loss to follow-up. We developed and internally validated a multivariable logistic regression model for severe rebound pain, defined as transition from well-controlled pain in the PACU (numerical rating scale [NRS] 3 or less) to severe pain (NRS ≥7) within 48 h. A priori predictors were age, sex, surgery type, planned admission, local anaesthetic type, dexamethasone use, and intraoperative anaesthesia type. Model performance was evaluated using area under the receiver operating characteristic curve (AUROC), Nagelkerke's R2, scaled Brier score, and calibration slope.ResultsThe cohort included 1365 patients (mean [standard deviation] age: 50 [16] yr). The primary outcome was abstracted in 1311 (96%) patients, with severe rebound pain in 652 (50%). Internal validation revealed poor model performance, with AUROC 0.632 (95% confidence interval [CI]: 0.602–0.661; bootstrap optimisation 0.021), Nagelkerke's R2 0.063, and scaled Brier score 0.047. Calibration slope was 0.832 (95% CI: 0.623–1.041).ConclusionsWe show that a multivariable risk prediction model developed using routinely collected clinical data had poor predictive performance for severe rebound pain after foot and ankle surgery. Prospective studies involving other patient-related predictors are needed.Clinical trial registrationNCT05018104.
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