Borna Sahar, Ho Olivia A, Gomez-Cabello Cesar A, Haider Syed Ali, Genovese Ariana, Prabha Srinivasagam, Haider Clifton R, Felton Christopher L, McLeod Christopher J, Bruce Charles J, Carter Rickey E, Forte Antonio Jorge
Division of Plastic Surgery, Mayo Clinic, Jacksonville, FL 32224, USA.
Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN 55905, USA.
J Clin Med. 2024 Dec 25;14(1):37. doi: 10.3390/jcm14010037.
Effective pain management is crucial for both comfort and outcomes, yet predicting and managing this pain is difficult. This study aimed to analyze postoperative pain in patients undergoing hand surgery at the Mayo Clinic Florida, examining how patient characteristics and anxiety affect pain outcomes. We conducted a single-arm clinical trial at Mayo Clinic Florida, recruiting patients undergoing hand surgery. Preoperative pain and anxiety were assessed using the Pain Catastrophizing Scale (PCS) and State-Trait Anxiety Inventory (STAI). Postoperatively, patients used an iPhone app to record pain levels and medication use every four hours. Devices were collected three days after surgery. We analyzed the relationship between demographics, PCS, STAI scores, and pain levels using linear and logistic regression models. All statistical tests were two-sided with significance set at < 0.05, analyzed with R4.2.2. Data were collected from 62 patients (62.9% women, 37.1% men) undergoing hand surgery. Participants were mainly White (90.3%), with 50% being in the middle-aged adult group. Most had low anxiety levels (80.6% STAI-S, 82.3% STAI-T) and low catastrophizing (61.3% PCS). Postoperative pain was low, with median scores between 1.0 and 2.0 over three days. Demographics, anxiety, and catastrophizing were not significant predictors of pain levels. Logistic regression showed time as a significant factor, with pain levels peaking on Day 3. Postoperative pain after hand surgery was generally low, with time being a significant predictor of increased pain. Demographic factors, anxiety, and catastrophizing did not significantly affect pain levels. Pain management should emphasize time-sensitive interventions and ongoing monitoring.
有效的疼痛管理对于舒适度和治疗结果都至关重要，但预测和管理这种疼痛却很困难。本研究旨在分析佛罗里达州梅奥诊所接受手部手术患者的术后疼痛情况，研究患者特征和焦虑如何影响疼痛结果。我们在佛罗里达州梅奥诊所进行了一项单臂临床试验，招募接受手部手术的患者。术前使用疼痛灾难化量表（PCS）和状态-特质焦虑量表（STAI）评估疼痛和焦虑情况。术后，患者使用一款iPhone应用程序每四小时记录一次疼痛程度和用药情况。术后三天收集设备。我们使用线性和逻辑回归模型分析人口统计学、PCS、STAI评分与疼痛程度之间的关系。所有统计检验均为双侧检验，显著性设定为<0.05，使用R4.2.2进行分析。数据收集自62例接受手部手术的患者（女性62.9%，男性37.1%）。参与者主要为白人（90.3%），50%属于中年成年组。大多数人焦虑水平较低（STAI-S为80.6%，STAI-T为82.3%）且灾难化程度较低（PCS为61.3%）。术后疼痛程度较低，三天内中位数评分在1.0至2.0之间。人口统计学、焦虑和灾难化程度不是疼痛程度的显著预测因素。逻辑回归显示时间是一个显著因素，疼痛程度在第3天达到峰值。手部手术后的术后疼痛总体较低，时间是疼痛增加的显著预测因素。人口统计学因素、焦虑和灾难化程度并未显著影响疼痛程度。疼痛管理应强调时间敏感型干预措施和持续监测。
