Khoury Laila H, Stephens Josh, Brown Shimron, Chatha Kiran, Girshfeld Sarah, Lozano Leon Juan Manuel, Lavin Alessia, Sabesan Vani J
Charles E. Schmidt School of Medicine, Florida Atlantic University, Boca Raton, FL, USA.
NOVA Southeastern University Dr. Kiran C. Patel College of Osteopathic Medicine, Davie, FL, USA.
JSES Int. 2022 Jul 3;6(5):833-842. doi: 10.1016/j.jseint.2022.06.001. eCollection 2022 Sep.
Currently 128 people die daily from opioid-related overdoses in the United States. This burden has instigated a search for viable means to guide postoperative prescription decision-making. The Opioid Risk Tool (ORT) and the Screener and Opioid Assessment for Patient with Pain (SOAPP) are validated risk assessment tools to predict opioid usage in high-risk populations. The purpose of this study was to evaluate the accuracy of these opioid risk assessments and pain intensity scores, including the Patient-Reported Outcomes Measurement Information System (PROMIS), to predict postoperative opioid use and dependence in shoulder surgery.
A retrospective review of 81 patients who underwent shoulder surgery and completed 3 preoperative risk and pain assessments within a single hospital system from 2018 to 2020 was performed. Demographic variables and ORT-O, SOAPP-R (the revised version of the SOAPP assessment), and PROMIS 3a scores were recorded from preoperative assessments. Opioid prescriptions were recorded from Electronic-Florida Online Reporting of Controlled Substances Evaluation. Dependence was defined as opioid prescriptions at or greater than 3 months after surgery. Risk assessment scores were compared and tested against postoperative opioid prescriptions using statistical analyses and logistic regression modeling.
In the cohort, there were 36 female and 45 male patients with an average age of 64.5 years and body mass index of 28.0. Preoperatively, the average pain score was 6.2, and 7.8% of patients reported prolonged preoperative narcotics use. The average ORT-O score was 3.0, with 35.8% of patients defined as either medium or high risk, and the average PROMIS pain intensity preoperatively was 10.8. Neither the ORT-O nor the PROMIS pain score were good predictors of postoperative opioid dependence (area under curve = 0.39 and 0.43, respectively). The SOAPP-R performed slightly better (area under curve = 0.70) and was the only assessment with significantly different mean scores between patients with postoperative opioid dependence and those without (33.4 and 24.5, respectively, = .049) and a moderate correlation to postoperative total morphine equivalents (R = 0.46, = .007).
With recent focus on preoperative risk assessments to predict postoperative opioid use and dependence, it is important to understand how well these tools work when applied to orthopedic patients. While the ORT may be helpful in other fields, it does not seem to be a strong predictor of postoperative opioid use or dependence in patients undergoing various types of shoulder surgery. Future studies are needed to explore the utility of the SOAPP-R in a larger sample and identify tools applicable to the orthopedic population to assist surgeons in screening at-risk patients.
目前在美国，每天有128人死于与阿片类药物相关的过量用药。这一负担促使人们寻找可行的方法来指导术后处方决策。阿片类药物风险工具（ORT）和疼痛患者筛查与阿片类药物评估（SOAPP）是经过验证的风险评估工具，用于预测高危人群的阿片类药物使用情况。本研究的目的是评估这些阿片类药物风险评估和疼痛强度评分（包括患者报告结果测量信息系统（PROMIS））预测肩部手术术后阿片类药物使用和依赖的准确性。
对2018年至2020年在单一医院系统中接受肩部手术并完成3项术前风险和疼痛评估的81例患者进行回顾性研究。从术前评估中记录人口统计学变量、ORT - O、SOAPP - R（SOAPP评估的修订版）和PROMIS 3a评分。从电子佛罗里达受控物质评估在线报告中记录阿片类药物处方。依赖定义为术后3个月及以上的阿片类药物处方。使用统计分析和逻辑回归模型比较风险评估分数并与术后阿片类药物处方进行测试。
该队列中有36名女性和45名男性患者，平均年龄64.5岁，体重指数28.0。术前，平均疼痛评分为6.2，7.8%的患者报告术前长期使用麻醉药品。ORT - O平均评分为3.0，35.8%的患者被定义为中度或高风险，术前PROMIS疼痛强度平均为10.8。ORT - O和PROMIS疼痛评分均不是术后阿片类药物依赖的良好预测指标（曲线下面积分别为0.39和0.43）。SOAPP - R表现稍好（曲线下面积 = 0.70），并且是术后有阿片类药物依赖的患者与无依赖患者之间平均得分有显著差异的唯一评估指标（分别为33.4和24.5，P = 0.049），且与术后总吗啡当量有中度相关性（R = 0.46，P = 0.007）。
随着近期对术前风险评估以预测术后阿片类药物使用和依赖的关注，了解这些工具应用于骨科患者时的效果很重要。虽然ORT在其他领域可能有帮助，但它似乎不是各类肩部手术患者术后阿片类药物使用或依赖的有力预测指标。未来需要进行研究，以在更大样本中探索SOAPP - R的效用，并确定适用于骨科人群的工具，以协助外科医生筛查高危患者。
