Eslami Mohammad H, Rybin Denis V, Doros Gheorghe, Farber Alik
Division of Vascular Surgery, Department of Surgery, University of Pittsburgh Medical Center, Pittsburgh, Pa.
Department of Biostatistics, Boston University School of Public Health, Boston, Mass.
J Vasc Surg. 2017 Jan;65(1):65-74.e2. doi: 10.1016/j.jvs.2016.07.103. Epub 2016 Oct 5.
Despite vast improvement in the field of vascular surgery, elective abdominal aortic aneurysm (AAA) repair still leads to perioperative death. Patients with asymptomatic AAAs, therefore, would benefit from an individual risk assessment to help with decisions regarding operative intervention. The purpose of this study was to describe such a 30-day postoperative (POD) risk prediction model using American College of Surgeons National Surgical Quality Improvement Project (NSQIP) data.
The NSQIP database (2005-2011) was queried for patients undergoing elective AAA repair using open or endovascular techniques. Clinical variables and known predictors of mortality were included in a full prediction model. These variables included procedure type, patient's age, functional dependence and comorbidities, and surgeon's specialty. Backward elimination with alpha-level of 0.2 was used to construct a parsimonious model. Model discrimination was evaluated in equally sized risk quintiles.
The overall mortality rate for 18,917 elective AAA patients was 1.7%. In this model, surgeon's specialty was not predictive of POD. The most significant factors affecting POD included open repair (odds ratio [OR], 2.712; 95% confidence interval [CI], 2.119-3.469; P < .001), age >70 (OR, 2.243; 95% CI, 1.695-3.033; P < .001), functional dependency (OR, 2.290; 95% CI, 1.442-3.637; P < .001), creatinine above 2.0 mg/dL (OR, 2.1; 95% CI, 1.403-3.142; P < .001) and low hematocrit levels (OR, 2.157; 95% CI, 1.365-3.408; P = .001).The discriminating ability of the NSQIP model was reasonable (C-statistic = 0.751) and corrected to 0.736 after internal validation. The NSQIP model performed well predicting mortality among risk-group quintiles.
The NSQIP risk prediction model is a robust vehicle to predict POD among patient undergoing elective AAA repair. This model can be used for risk stratification of patients undergoing elective AAA repair.
尽管血管外科领域有了巨大进步，但择期腹主动脉瘤（AAA）修复术仍会导致围手术期死亡。因此，无症状AAA患者将受益于个体风险评估，以帮助做出有关手术干预的决策。本研究的目的是使用美国外科医师学会国家外科质量改进项目（NSQIP）的数据描述这样一个术后30天（POD）风险预测模型。
查询NSQIP数据库（2005 - 2011年）中接受开放或血管内技术择期AAA修复术的患者。临床变量和已知的死亡预测因素被纳入一个完整预测模型。这些变量包括手术类型、患者年龄、功能依赖和合并症以及外科医生的专业。使用α水平为0.2的向后剔除法构建一个简约模型。在大小相等的风险五分位数中评估模型的辨别力。
18917例择期AAA患者的总体死亡率为1.7%。在这个模型中，外科医生的专业不能预测POD。影响POD的最显著因素包括开放修复（比值比[OR]，2.712；95%置信区间[CI]，2.119 - 3.469；P <.001）、年龄>70岁（OR，2.243；95% CI，1.695 - 3.033；P <.001）、功能依赖（OR，2.290；95% CI，1.442 - 3.637；P <.001）、肌酐高于2.0mg/dL（OR，2.1；95% CI，1.403 - 3.142；P <.001）和低血细胞比容水平（OR，2.157；95% CI，1.365 - 3.408；P =.001）。NSQIP模型的辨别能力合理（C统计量 = 0.751），内部验证后校正为0.736。NSQIP模型在预测风险组五分位数中的死亡率方面表现良好。
NSQIP风险预测模型是预测择期AAA修复术患者POD的有力工具。该模型可用于择期AAA修复术患者的风险分层。
