术后急性疼痛是常见的、痛苦的，并与发病率增加有关。有针对性的干预可以预防其发展。我们旨在开发和内部验证一种预测工具，以预先识别接受大手术后可能出现严重疼痛风险的患者。我们分析了英国围手术期质量改进计划的数据，使用术前变量开发和验证了一个逻辑回归模型，以预测术后第一天的严重疼痛。次要分析包括术中变量的使用。共有17,079名接受大手术的患者的数据被纳入研究。3140名（18.4%）患者报告了严重疼痛，在女性、癌症或胰岛素依赖型糖尿病患者、吸烟者和正在服用基线阿片类药物的患者中更为普遍。我们最终的模型包括25个术前预测因子，校正后的乐观统计量为0.66，良好的校准（平均绝对误差0.005，P = 0.35）。决策曲线分析表明，预测风险值20-30%是识别高风险个体的最佳截断值。潜在的可改变风险因素包括吸烟状态和患者自报的心理健康措施。不可改变的因素包括人口统计和外科因素。添加术中变量可以提高判别能力（似然比χ2 496.5，P < 0.001），但添加基线阿片药物数据没有提高判别能力。在内部验证中，我们的术前预测模型校准良好，但判别能力中等。包括围手术期协变量后，性能得以改善，表明单独使用术前变量无法充分预测术后疼痛。 ©2023 John Wiley ∧ Sons Ltd on behalf of Association of Anaesthetists，Anaesthesia的作者。

Acute postoperative pain is common, distressing and associated with increased morbidity. Targeted interventions can prevent its development. We aimed to develop and internally validate a predictive tool to pre-emptively identify patients at risk of severe pain following major surgery. We analysed data from the UK Peri-operative Quality Improvement Programme to develop and validate a logistic regression model to predict severe pain on the first postoperative day using pre-operative variables. Secondary analyses included the use of peri-operative variables. Data from 17,079 patients undergoing major surgery were included. Severe pain was reported by 3140 (18.4%) patients; this was more prevalent in females, patients with cancer or insulin-dependent diabetes, current smokers and in those taking baseline opioids. Our final model included 25 pre-operative predictors with an optimism-corrected c-statistic of 0.66 and good calibration (mean absolute error 0.005, p = 0.35). Decision-curve analysis suggested an optimal cut-off value of 20-30% predicted risk to identify high-risk individuals. Potentially modifiable risk factors included smoking status and patient-reported measures of psychological well-being. Non-modifiable factors included demographic and surgical factors. Discrimination was improved by the addition of intra-operative variables (likelihood ratio χ2 496.5, p < 0.001) but not by the addition of baseline opioid data. On internal validation, our pre-operative prediction model was well calibrated but discrimination was moderate. Performance was improved with the inclusion of peri-operative covariates suggesting pre-operative variables alone are not sufficient to adequately predict postoperative pain.© 2023 The Authors. Anaesthesia published by John Wiley & Sons Ltd on behalf of Association of Anaesthetists.