College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK.
Institute of Translational Medicine, University Hospitals Birmingham NHS Trust, Birmingham, UK.
Dis Esophagus. 2020 Jan 16;33(1). doi: 10.1093/dote/doz041.
Predicting major anastomotic leak (AL) and major complications (Clavien-Dindo 3-5) following esophagectomy improves postoperative management of patients. The role of the NUn score in their prediction is controversial. This study aims to evaluate the predictive ability of this simple score. Data were retrospectively collected for consecutive esophagectomies over a 10-year period, and NUn scores were retrospectively calculated for each patient from informatics data. A standardized definition of major AL was used, excluding minor asymptomatic, radiologically detected leaks. The predictive accuracy of the NUn score and its constituent parts, for major AL and major complications, was assessed using area under receiver operating characteristics curves (AUROCs). Of 382 patients, 48 (13%) developed major AL and 123 (32%) developed major complications. The NUn score calculated on postoperative day 4 was significantly predictive of both outcomes, with AUROCs of 0.77 and 0.71, respectively (both P < 0.001). A NUn score cut-off of 10 had a negative predictive value of 95% for major AL. The NUn score was predictive of major complications on multivariable analysis. The NUn score was found to be a significant predictor of major AL, suggesting that this is a useful early warning score for major AL. The score may also be useful in identifying patients that are the most likely to benefit from enhanced recovery protocols.
预测食管切除术后主要吻合口漏(AL)和主要并发症(Clavien-Dindo 3-5)可改善患者的术后管理。NUn 评分在其预测中的作用存在争议。本研究旨在评估该简单评分的预测能力。回顾性收集了 10 年内连续进行的食管切除术的数据,并从信息学数据中为每位患者回顾性计算了 NUn 评分。使用标准化的主要 AL 定义,排除了无症状、放射学检测到的轻微漏诊。使用受试者工作特征曲线下面积(AUROCs)评估 NUn 评分及其组成部分对主要 AL 和主要并发症的预测准确性。在 382 例患者中,48 例(13%)发生了主要 AL,123 例(32%)发生了主要并发症。术后第 4 天计算的 NUn 评分对这两种结局均具有显著预测能力,AUROCs 分别为 0.77 和 0.71(均 P<0.001)。NUn 评分>10 的截断值对主要 AL 的阴性预测值为 95%。NUn 评分在多变量分析中可预测主要并发症。NUn 评分是主要 AL 的显著预测指标,表明这是一种有用的主要 AL 早期预警评分。该评分可能还有助于识别最有可能从强化康复方案中受益的患者。