BACKGROUND A surgical adverse incident (AI) is defined as any deviation from the normal operative course. Current complication-grading systems mostly focus on postoperative events. OBJECTIVE To propose an intraoperative AI classification (EAUiaiC) to facilitate reporting. DESIGN, SETTING, AND PARTICIPANTS The classification was developed using a modified Delphi process in which experts answered two rounds of survey questionnaires organised by the European Association of Urology ad hoc Complications Guidelines Panel. Experts evaluated AI terminology using a 5-point Likert scale for clarity, exhaustiveness, hierarchical order, mutual exclusivity, clinical utility, and quality improvement. OUTCOME MEASURES AND STATISTICAL ANALYSIS We considered ≥70% agreement for inclusion or exclusion. The resultant EAUiaiC was evaluated using ten sample clinical scenarios. Numerical and graphical statistical techniques were used to report the results. RESULTS AND LIMITATIONS In total, 343 respondents participated. The proposed EAUiaiC system comprises eight AI grades ranging from grade 0 (no deviation and no consequence to the patient) to grade 5B (wrong surgery site or intraoperative death). In the validation stage, EAUiaiC was rated highly favourably in terms of relevance and reliability (consistency) by 126 experts. Ratings for self-reported ease of use were at acceptable levels. CONCLUSIONS We propose a novel intraoperative AI classification (EAUiaiC) for use for urological procedures. Both the initial assessment of feasibility and the subsequent assessment of reliability suggest that it is a simple and effective tool for classifying intraoperative complications. PATIENT SUMMARY Complications in surgery are common. It is helpful to classify complications in a uniform and objective manner so that surgeons can easily compare outcomes and learn from complications. Here we propose a new classification system for complications that occur during urological surgical procedures. An abstract of this work was presented at the 2018 congress of the European Association of Urology.

中文翻译：

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欧洲泌尿外科协会特别并发症指南小组的术中不良事件分类（EAUiaiC）。

背景技术手术不良事件（AI）被定义为与正常手术过程的任何偏离。当前的并发症分级系统主要集中于术后事件。目的提出术中AI分类（EAUiaiC）以利于报告。设计，地点和参与者该分类是使用改进的Delphi程序开发的，其中专家回答了由欧洲泌尿外科协会特设并发症指南小组组织的两轮调查问卷。专家使用5点Likert量表评估了AI术语的清晰度，详尽性，等级顺序，互斥性，临床效用和质量改进。观察指标和统计分析我们认为≥70％同意纳入或排除。使用十个样本临床方案评估了所得的EAUiaiC。使用数字和图形统计技术报告结果。结果与局限性共有343名受访者参加。拟议的EAUiaiC系统包括8个AI等级，范围从0级（无偏差，对患者无影响）到5B级（错误的手术部位或术中死亡）。在验证阶段，EAUiaiC在相关性和可靠性（一致性）方面得到126位专家的高度评价。自我报告的易用性等级为可接受的水平。结论我们提出了一种新的术中AI分类（EAUiaiC）用于泌尿外科手术。可行性的初步评估和可靠性的后续评估均表明，这是对术中并发症进行分类的简单有效的工具。病人总结手术中的并发症很普遍。以统一和客观的方式对并发症进行分类是有帮助的，以便外科医生可以轻松比较结果并从并发症中学习。在这里，我们为泌尿外科手术过程中发生的并发症提出了一种新的分类系统。在欧洲泌尿外科协会2018年大会上介绍了这项工作的摘要。在这里，我们针对泌尿外科手术过程中发生的并发症提出了一种新的分类系统。在欧洲泌尿外科协会2018年大会上介绍了这项工作的摘要。在这里，我们为泌尿外科手术过程中发生的并发症提出了一种新的分类系统。在欧洲泌尿外科协会2018年大会上介绍了这项工作的摘要。