摘要
目的探讨影响术后疼痛的高危因素,对术后早期疼痛的发生几率及严重程度做出预测。方法选择本院手术患者2 859例,采用Logistic多项多元回归分析筛选出构成评分系统的影响因素;通过ROC曲线确定预测不同术后疼痛发生率的分值界点;采用Kappa检验比较评分系统预测的术后疼痛发生率与实际疼痛发生率的一致性。结果 Logistic多元回归分析提示:性别、年龄、术前VAS评分、术前焦虑评分、术前心率、手术类型、手术切口大小、麻醉方式、手术时间为影响术后疼痛的高危因素;术后VAS评分的曲线下面积是0.90±0.01(P<0.01);疼痛评分在2.5时,灵敏度为100%,特异度为78.9%;Kappa指数为0.54。结论术后疼痛预测模型简单实用,对临床有一定参考价值。
Objective To investigate the high risk factors of postoperative pain, and to establish a prediction model to predict the probability and severity of early postoperative pain. Methods The total of 2859 surgery patients were enrolled. Influential factors of scoring system were screened by Logistic multiple regression analysis; train spacing point of the incidence of different postoperative pain was measured by ROC curve; predictive or actual incidence of postoperative pain was compared using Kappa analysis. Results Logistic multiple regression analysis showed that the high risk factors of postoperative pail) included sex. age, preoperative visual analog score (VAS), preoperative anxiety score, preoperative heart rate, operation type, anesthesia method, operation time. The AUC of postoperative pain score was 0.90±0.01 (P〈0. 01). When VAS was 2.5, the sensitivity and specificity was 100% and 78.9% respectively; Kappa index was 0.54. Conclusion The prediction model of postoperative pain was simple and useful in clinical practice.
出处
《临床麻醉学杂志》
CAS
CSCD
北大核心
2011年第4期353-355,共3页
Journal of Clinical Anesthesiology
基金
广东省卫生厅立项资助项目(编号:A2008698)