Department of Surgery, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.
Department of Surgery, Canisius Wilhelmina Hospital, Nijmegen, The Netherlands.
Dis Esophagus. 2023 Sep 30;36(10). doi: 10.1093/dote/doad016.
Anastomotic leak (AL) is a common and severe complication after esophagectomy. This study aimed to assess the performance of a consensus-based algorithm for diagnosing AL after minimally invasive esophagectomy. This study used data of the ICAN trial, a multicenter randomized clinical trial comparing cervical and intrathoracic anastomosis, in which a predefined diagnostic algorithm was used to guide diagnosing AL. The algorithm identified patients suspected of AL based on clinical signs, blood C-reactive protein (cut-off value 200 mg/L), and/or drain amylase (cut-off value 200 IU/L). Suspicion of AL prompted evaluation with contrast swallow computed tomography and/or endoscopy to confirm AL. Primary outcome measure was algorithm performance in terms of sensitivity, specificity, and positive and negative predictive values (PPV, NPV), respectively. AL was defined according to the definition of the Esophagectomy Complications Consensus Group. 245 patients were included, and 125 (51%) patients were suspected of AL. The algorithm had a sensitivity of 62% (95% confidence interval [CI]: 46-75), a specificity of 97% (95% CI: 89-100), and a PPV and NPV of 94% (95% CI: 79-99) and 77% (95% CI: 66-86), respectively, on initial assessment. Repeated assessment in 19 patients with persisting suspicion of AL despite negative or inconclusive initial assessment had a sensitivity of 100% (95% CI: 77-100). The algorithm showed poor performance because the low sensitivity indicates the inability of the algorithm to confirm AL on initial assessment. Repeated assessment using the algorithm was needed to confirm remaining leaks.
吻合口漏（AL）是食管切除术后常见且严重的并发症。本研究旨在评估一种基于共识的算法在微创食管切除术后诊断 AL 的性能。本研究使用了 ICAN 试验的数据，这是一项比较颈段和胸内吻合的多中心随机临床试验，其中使用了预设的诊断算法来指导 AL 的诊断。该算法根据临床症状、血 C 反应蛋白（临界值 200mg/L）和/或引流淀粉酶（临界值 200IU/L）来识别疑似 AL 的患者。怀疑 AL 时，通过对比吞咽计算机断层扫描和/或内镜进行评估以确认 AL。主要观察指标是算法在灵敏度、特异性、阳性预测值（PPV）和阴性预测值（NPV）方面的性能。AL 根据食管切除术并发症共识组的定义进行定义。共纳入 245 例患者，其中 125 例（51%）患者疑似 AL。该算法的灵敏度为 62%（95%置信区间：46-75），特异性为 97%（95%置信区间：89-100），PPV 和 NPV 分别为 94%（95%置信区间：79-99）和 77%（95%置信区间：66-86）。在初始评估中，19 例持续怀疑 AL 的患者尽管初始评估为阴性或不确定，但进行了重复评估，其灵敏度为 100%（95%置信区间：77-100）。该算法的性能较差，因为低灵敏度表明该算法无法在初始评估中确认 AL。需要使用该算法进行重复评估以确认是否存在残留漏。
