Division of Vascular Surgery, Department of Surgery, Stanford, CA.
Division of Vascular and Endovascular Surgery, Department of Surgery, Long School of Medicine, University of Texas Health at San Antonio, San Antonio, TX.
Ann Vasc Surg. 2022 May;82:181-189. doi: 10.1016/j.avsg.2021.10.041. Epub 2021 Nov 14.
The American College of Surgeons Risk Calculator (ACS-RC) provides an assessment of a patient's risk of 30-day postoperative complications. The Surgeon Adjusted Risk (SAR) parameter of the calculator allows for ad hoc adjustment of risk based on risk factors not considered by the model. This study aims to evaluate the predictive accuracy of the ACS-RC in vascular surgery patients undergoing major lower-extremity amputation (LEA) and identify additional risk factors that warrant use of the SAR parameter.
This is a retrospective study of 298 sequential amputations at a single institution. At the population level, the mean of predicted 30-day outcomes from the ACS-RC with a SAR score of 1 (no adjustment necessary) and 2 (risk somewhat higher than estimate) were compared to the rate of observed outcomes. Predictive accuracy at the individual level was completed using receiver operating curve area under the curve (AUC). Logistic regression with respect to mortality was performed over variables not considered by the ACS-RC. Efficacy of selectively utilizing the SAR parameter in predicting mortality was analyzed with a stratified analysis in which patients with risk factors significant for mortality were assigned increased risk.
At the population level, ACS-RC grossly underpredicted serious complications, SSI, VTE, and unplanned RTOR, while overpredicting mortality and cardiac complications. At the individual level, SAR1 was more predictive for serious complications (AUC = 0.624), SSI (AUC = 0.610), and unplanned RTOR (AUC = 0.541). Conversely, SAR2 was more predictive for mortality (AUC = 0.709), cardiac complications (AUC = 0.561), and VTE (AUC = 0.539). Logistic regression identified history of CVA with a residual deficit (OR = 4.61, P = 0.033) and ischemic rest pain without tissue loss (OR = 4.497, P = 0.047) as independent risk factors for postoperative mortality. Stratified analysis with utilization of the SAR2 based on the 2 independent risk factors improved AUC in predicting mortality (AUC 0.792 from 0.709).
Major LEAs are associated with high perioperative morbidity and mortality. In a veteran population, the ACS-RC showed mixed predictability at the population level and fair predictability at the individual level with regards to postoperative outcomes. Rest pain without tissue loss and history of CVA with residual deficit were identified as risk factors for postoperative mortality. Although ad hoc adjustment with the subjective SAR modifier based on the presence of these 2 risk factors increased the calculator's accuracy, this study highlights some potential limitations of the ACS-RC when applied to vascular surgery patients undergoing major LEA.
美国外科医师学会风险计算器（ACS-RC）可评估患者术后 30 天内发生并发症的风险。该计算器的外科医生调整风险（SAR）参数允许根据模型未考虑的风险因素进行风险的临时调整。本研究旨在评估 ACS-RC 在接受大下肢截肢（LEA）的血管外科患者中的预测准确性，并确定需要使用 SAR 参数的其他风险因素。
这是对单机构 298 例连续截肢患者的回顾性研究。在人群水平上，与 ACS-RC 预测的 30 天结局的平均值（SAR 评分为 1（无需调整）和 2（风险略高于估计））相比，观察到的结局发生率。使用接收器操作曲线下面积（AUC）在个体水平上完成预测准确性。使用与 ACS-RC 无关的变量进行关于死亡率的 logistic 回归。通过分层分析分析选择性使用 SAR 参数预测死亡率的效果，其中将与死亡率相关的风险因素显著的患者分配为高风险。
在人群水平上，ACS-RC 严重低估了严重并发症、SSI、VTE 和非计划再手术时间（RTOR），而高估了死亡率和心脏并发症。在个体水平上，SAR1 对严重并发症（AUC=0.624）、SSI（AUC=0.610）和非计划 RTOR（AUC=0.541）的预测更准确。相反，SAR2 对死亡率（AUC=0.709）、心脏并发症（AUC=0.561）和 VTE（AUC=0.539）的预测更准确。Logistic 回归确定了伴有残留缺陷的 CVA 病史（OR=4.61，P=0.033）和无组织损失的缺血性静息痛（OR=4.497，P=0.047）是术后死亡率的独立危险因素。根据这 2 个独立危险因素，利用 SAR2 进行分层分析可提高死亡率预测的 AUC（AUC 从 0.709 提高至 0.792）。
大 LEA 与围手术期高发病率和死亡率相关。在退伍军人人群中，ACS-RC 在人群水平上的预测能力参差不齐，在个体水平上的预测能力尚可，可预测术后结局。无组织损失的静息痛和伴有残留缺陷的 CVA 病史被确定为术后死亡率的危险因素。尽管根据存在这 2 个危险因素，使用主观 SAR 修正因子进行临时调整可提高计算器的准确性，但本研究强调了 ACS-RC 在应用于接受大下肢截肢的血管外科患者时的一些潜在局限性。
