Hitt James, Lee Robert, Elkin Peter
Veterans Healthcare Administration, Department of Anesthesiology, Western New York Healthcare System, Buffalo, NY, United States of America.
University at Buffalo, Jacobs School of Medicine, Department of Biomedical Informatics, Buffalo, NY, United States of America.
Surg Open Sci. 2023 Feb 23;12:29-34. doi: 10.1016/j.sopen.2023.02.003. eCollection 2023 Mar.
Acute postoperative pain is common following many types of surgery, and a significant subset of patients experience severe pain, which can be difficult to manage and result in postoperative complications. Opioid agonists are commonly used to treat severe postoperative pain, but their use has been associated with adverse outcomes. This retrospective study uses data from the Veterans Administration Surgical Quality Improvement Project (VASQIP) database to develop a postoperative Pain Severity Scale (PSS) based on subjective pain reports and postoperative opioid requirements.
Postoperative pain scores and opioid prescription data were extracted from the VASQIP database for surgeries occurring between 2010 and 2020. Procedures were grouped by surgical Common Procedural Terminology (CPT) codes, and a total of 165,321 surgical procedures were examined, representing 1141 distinct CPT codes. -means clustering analysis was used to group the surgeries based on 24-h maximum pain, 72-h average pain, and postoperative opioid prescriptions.
-means clustering analysis showed two optimal grouping strategies; one with 3 and the other with 5 groups. Both clustering strategies produced a PSS that categorized surgical procedures with generally increasing pain scores and opioid requirements. The 5-group PSS accurately captured typical postoperative pain experience across a range of procedures.
-means clustering produced a Pain Severity Scale that can distinguish typical postoperative pain for a large variety of surgical procedures based on subjective and objective clinical data. The PSS will facilitate research into the optimal postoperative pain management and could be used in the development of clinical decision support tools.
急性术后疼痛在多种手术类型后很常见，相当一部分患者会经历严重疼痛，这可能难以控制并导致术后并发症。阿片类激动剂常用于治疗严重的术后疼痛，但其使用与不良后果相关。这项回顾性研究使用退伍军人事务部外科质量改进项目（VASQIP）数据库中的数据，基于主观疼痛报告和术后阿片类药物需求制定术后疼痛严重程度量表（PSS）。
从VASQIP数据库中提取2010年至2020年期间手术的术后疼痛评分和阿片类药物处方数据。手术程序按手术通用程序术语（CPT）代码分组，共检查了165321例手术程序，代表1141个不同的CPT代码。采用均值聚类分析，根据24小时最大疼痛、72小时平均疼痛和术后阿片类药物处方对手术进行分组。
均值聚类分析显示了两种最佳分组策略；一种分为3组，另一种分为5组。两种聚类策略都产生了一个PSS，该量表将手术程序按疼痛评分和阿片类药物需求总体上递增的顺序进行分类。5组PSS准确地反映了一系列手术中典型术后疼痛经历。
均值聚类产生了一个疼痛严重程度量表，该量表可以根据主观和客观临床数据区分多种手术程序的典型术后疼痛。PSS将有助于对最佳术后疼痛管理进行研究，并可用于临床决策支持工具的开发。
