Department of Surgery, McGovern Medical School at the University of Texas Health Science Center, Houston, Texas, USA.
Center for Surgical Trials and Evidence-based Practice, McGovern Medical School at the University of Texas Health Science Center, Houston, Texas, USA.
Surg Infect (Larchmt). 2021 Sep;22(7):697-704. doi: 10.1089/sur.2020.242. Epub 2021 Jan 5.
Superficial surgical site infections (S-SSIs) are common after trauma laparotomy, leading to morbidity, increased costs, and prolonged length of stay (LOS). Opportunities to mitigate S-SSI risks are limited to the intra-operative and post-operative periods. Accurate S-SSI risk stratification is paramount at the time of operation to inform immediate management. We aimed to develop a risk calculator to aid in surgical decision-making at the time of emergency laparotomy. A retrospective cohort study of patients requiring emergency trauma laparotomy between 2011 and 2017 at a single, level 1 trauma center was performed. Operative factors, skin management strategy, and outcomes were determined by chart review. Bayesian multilevel logistic regression was utilized to create a risk calculator with variables available upon closure of the laparotomy. Models were validated on a 30% test cohort and discrimination reported as an area under the receiver operating characteristics curve (AUROC). Of 1,322 patients, the majority were male (77%) with median age of 33 years, injured by blunt mechanism (54%), and median injury severity score of 19. Eighty-eight (7%) patients developed an S-SSI. Patients who developed S-SSI had higher final lactate, blood loss, transfusion requirements, and wound classification. Patients with S-SSI more frequently had mesenteric or large bowel injury than those without S-SSI. Superficial SSI was associated with increased complications and prolonged length of stay (LOS). The S-SSI predictive model demonstrated moderate discrimination with an AUROC of 0.69 (95% confidence interval [CI], 0.56-0.81). Parameters contributing the most to the model were damage control laparotomy, full-thickness large bowel injury, and large bowel resection. A predictive model for S-SSI was built using factors available to the surgeon upon index emergency trauma laparotomy closure. This calculator may be used to standardize intra- and post-operative care and to identify high-risk patients in whom to test novel preventative strategies and improve overall outcomes for patients requiring emergency trauma laparotomy.
术后浅层切口感染(S-SSI)在创伤性剖腹手术后很常见,会导致发病率增加、医疗费用增加和住院时间延长。减轻 S-SSI 风险的机会仅限于手术期间和术后。在手术时准确分层 S-SSI 风险对于指导即时管理至关重要。我们旨在开发一种风险计算器,以帮助在紧急剖腹手术时做出手术决策。
对 2011 年至 2017 年期间在一家单一的 1 级创伤中心接受紧急创伤性剖腹手术的患者进行了回顾性队列研究。通过图表回顾确定了手术因素、皮肤管理策略和结果。利用贝叶斯多层次逻辑回归创建了一个风险计算器,该计算器具有在剖腹手术后可获得的变量。在 30%的测试队列上验证了模型,并报告了接收者操作特征曲线下的面积(AUROC)作为区分度。
在 1322 名患者中,大多数为男性(77%),中位年龄为 33 岁,受伤机制为钝性(54%),损伤严重程度评分中位数为 19 分。88 名(7%)患者发生了 S-SSI。发生 S-SSI 的患者最终乳酸水平更高、失血更多、输血需求更多,伤口分类更高。发生 S-SSI 的患者比未发生 S-SSI 的患者更频繁地出现肠系膜或大肠损伤。浅层 SSI 与并发症增加和住院时间延长(LOS)相关。SSI 预测模型具有中等的区分度,AUROC 为 0.69(95%置信区间 [CI],0.56-0.81)。对模型贡献最大的参数是损伤控制性剖腹手术、全层大肠损伤和大肠切除术。
使用指数紧急创伤性剖腹手术后关闭时外科医生可获得的因素构建了 S-SSI 预测模型。该计算器可用于标准化围手术期护理,并识别高危患者,以便对新的预防策略进行测试,并改善需要紧急创伤性剖腹手术的患者的整体结果。