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Intraoperative Adverse Incident Classification (EAUiaiC) by the European Association of Urology ad hoc Complications
Chandra Shekhar Biyani1, Jakub Pecanka2, Morgan Rouprêt3
1Department of Urology, St. James's University Hospital, Leeds, UK.
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.
