Dayan Danit, Nizri Eran, Keidar Andrei
Division of General Surgery, Bariatric Unit, Tel Aviv Medical Center, Affiliated to Sackler Faculty of Medicine, Tel Aviv University, 6, Weizman St, 6423906, Tel- Aviv, Israel.
Surg Endosc. 2025 Mar;39(3):1945-1951. doi: 10.1007/s00464-025-11556-0. Epub 2025 Jan 27.
Safety in one anastomosis gastric bypass (OAGB) is judged by outcomes, but it seems reasonable to utilize best practices for safety, whose performance can be evaluated and therefore improved. We aimed to test an artificial intelligence-based model in real world for the evaluation of adherence to best practices in OAGB.Please check and confirm that the authors and their respective affiliations have been correctly identified and amend if necessary.
A retrospective single-center study of 89 consecutive OAGB videos was captured and analyzed by an artificial intelligence platform (10/2020-12/2023). The platform currently provides assessment of four elements, including bougie insertion, full division of pouch, view of Treitz ligament, and leak test performed. Two bariatric surgeons viewed all videos, categorizing these elements into Yes/No adherence. Intra-rater and inter-rater agreements were computed. The estimates found in greatest consensus were used to determine the model's performance. Clinical data retrieval was performed.
Videos included primary (71.9%) and conversion (28.1%) OAGB. Patients' age was 41.5 ± 13.6y and body mass index 42.0 ± 5.7 kg/m2. Anastomosis width was 40 mm (IQR, 30-45), and biliopancreatic limb length was 200 cm (IQR, 180-200). Operative duration was 69.1 min (IQR 55.3-97.4), mainly spent on gastric transection (26%) and anastomosis (45%). Surgeons' intra-rater overall agreements ranged 93-100% (kappa 0.57-1). Inter-rater overall agreements increased to 99-100% (kappa 0.95-1) in the second review, set as reference point to the model. The model's overall accuracy ranged 82-98%, sensitivity 91-94%, and positive predictive value 88-99%. Specificity ranged 17-92% and negative predictive value 20-68%.
The model appears to have high accuracy, sensitivity, and positive predictive value for evaluating adherence to best practices for safety in OAGB. Considering the paucity of negative estimates in our study, more low-performance cases are needed to reliably define the model's specificity and negative predictive value. Adding more best practices, tested in multi-center studies will enable cross-border standardization of the procedure.
单吻合口胃旁路术（OAGB）的安全性通过手术结果来判断，但采用安全方面的最佳实践似乎是合理的，其实施情况可以得到评估并因此得到改进。我们旨在在现实世界中测试一个基于人工智能的模型，以评估OAGB中对最佳实践的遵循情况。请检查并确认作者及其各自的单位已被正确识别，如有必要请进行修改。
对89段连续的OAGB手术视频进行回顾性单中心研究，由一个人工智能平台（2020年10月至2023年12月）进行采集和分析。该平台目前提供对四个要素的评估，包括探条插入、胃囊完全离断、Treitz韧带视野以及进行的渗漏试验。两位减重外科医生观看了所有视频，将这些要素归类为是否遵循。计算了评分者内和评分者间的一致性。在最大共识中发现的估计值用于确定模型的性能。进行了临床数据检索。
视频包括初次（71.9%）和转换（28.1%）OAGB。患者年龄为41.5±13.6岁，体重指数为42.0±5.7kg/m²。吻合口宽度为40mm（四分位间距，30 - 45），胆胰支长度为200cm（四分位间距，180 - 200）。手术时长为69.1分钟（四分位间距55.3 - 97.4），主要花费在胃切断（26%）和吻合（45%）上。外科医生的评分者内总体一致性范围为93 - 100%（kappa值0.57 - 1）。在第二次审查中，评分者间总体一致性提高到99 - 100%（kappa值0.95 - 1），将其作为模型的参考点。模型的总体准确率范围为82 - 98%，敏感性为91 - 94%，阳性预测值为88 - 99%。特异性范围为17 - 92%，阴性预测值为20 - 68%。
该模型在评估OAGB中对安全最佳实践的遵循情况时似乎具有较高的准确性、敏感性和阳性预测值。考虑到我们研究中负面估计较少，需要更多低绩效病例来可靠地确定模型的特异性和阴性预测值。增加更多在多中心研究中测试的最佳实践将实现该手术的跨境标准化。
