Department of Neurosurgery, Johns Hopkins Hospital, Baltimore, Maryland, USA.
Department of Neurosurgery, Johns Hopkins Hospital, Baltimore, Maryland, USA.
World Neurosurg. 2021 Jul;151:e571-e578. doi: 10.1016/j.wneu.2021.04.086. Epub 2021 Apr 30.
Surgical-site infection (SSI) after spine surgery leads to increased length of stay, reoperation, and worse patient quality of life. We sought to develop a web-based calculator that computes an individual's risk of a wound infection following thoracolumbar spine surgery.
We performed a retrospective review of consecutive patients undergoing elective degenerative thoracolumbar spine surgery at a tertiary-care institution between January 2016 and December 2018. Patients who developed SSI requiring reoperation were identified. Regression analysis was performed and model performance was assessed using receiver operating curve analysis to derive an area under the curve. Bootstrapping was performed to check for overfitting, and a Hosmer-Lemeshow test was employed to evaluate goodness-of-fit and model calibration.
In total, 1259 patients were identified; 73% were index operations. The overall infection rate was 2.7%, and significant predictors of SSI included female sex (odds ratio [OR] 3.0), greater body mass index (OR 1.1), active smoking (OR 2.8), worse American Society of Anesthesiologists physical status (OR 2.1), and greater surgical invasiveness (OR 1.1). The prediction model had an optimism-corrected area under the curve of 0.81. A web-based calculator was created: https://jhuspine2.shinyapps.io/Wound_Infection_Calculator/.
In this pilot study, we developed a model and simple web-based calculator to predict a patient's individualized risk of SSI after thoracolumbar spine surgery. This tool has a predictive accuracy of 83%. Through further multi-institutional validation studies, this tool has the potential to alert both patients and providers of an individual's SSI risk to improve informed consent, mitigate risk factors, and ultimately drive down rates of SSIs.
脊柱手术后的手术部位感染（SSI）会导致住院时间延长、再次手术和患者生活质量下降。我们试图开发一种基于网络的计算器，以计算个体接受胸腰椎脊柱手术后发生伤口感染的风险。
我们对一家三级医疗机构在 2016 年 1 月至 2018 年 12 月期间连续进行的择期退行性胸腰椎脊柱手术的患者进行了回顾性分析。确定了需要再次手术的 SSI 患者。我们进行了回归分析，并通过接受者操作曲线分析评估模型性能，以获得曲线下面积。我们进行了 bootstrap 检查以检查过度拟合，并用 Hosmer-Lemeshow 检验评估拟合优度和模型校准。
共纳入 1259 例患者，73%为初次手术。总体感染率为 2.7%，SSI 的显著预测因素包括女性（比值比 [OR] 3.0）、更高的体重指数（OR 1.1）、吸烟（OR 2.8）、较差的美国麻醉医师协会身体状况（OR 2.1）和更高的手术侵袭性（OR 1.1）。经矫正后，预测模型的曲线下面积为 0.81。我们创建了一个基于网络的计算器：https://jhuspine2.shinyapps.io/Wound_Infection_Calculator/。
在这项初步研究中，我们开发了一种模型和简单的基于网络的计算器，以预测个体接受胸腰椎脊柱手术后 SSI 的风险。该工具的预测准确性为 83%。通过进一步的多机构验证研究，该工具有可能提醒患者和医务人员注意个体的 SSI 风险，以改善知情同意、减轻风险因素，并最终降低 SSI 发生率。
