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J Endourol ; 28(6): 717-21, 2014 Jun.
Article in English | MEDLINE | ID: mdl-24471449

ABSTRACT

BACKGROUND: With the increasing use of robot-assisted techniques for urologic and gynecologic surgery in patients with severe comorbidities, the risk of a critical incidence during surgery increases. Due to limited access to the patient the start of effective measures to treat a life-threatening emergency could be delayed. Therefore, we tested the management of an acute emergency in an operating room setting with a full-size simulator in six complete teams. METHODS: A full-size simulator (ISTAN, Meti, CA), modified to hold five trocars, was placed in a regular operating room and connected to a robotic system. Six teams (each with three nurses, one anesthesiologist, two urologists or gynecologists) were introduced to the scenario. Subsequently, myocardial fibrillation occurred. Time to first chest compression, removal of the robot, first defibrillation, and stabilization of circulation were obtained. After 7 weeks the simulation was repeated. RESULTS: The time to the start of chest compressions, removal of the robotic system, and first defibrillation were significantly improved at the second simulation. Time for restoration of stable circulation was improved from 417 ± 125 seconds to 224 ± 37 seconds (P=0.0054). Unexpected delays occurred during the first simulation because trocars had been removed from the patient but not from the robot, thus preventing the robot to be moved. CONCLUSION: Following proper training, resuscitation can be started within seconds. A repetition of the simulation significantly improved time for all steps of resuscitation. An emergency simulation of a multidisciplinary team in a real operating room setting can be strongly recommended.


Subject(s)
Arrhythmias, Cardiac/therapy , Cardiopulmonary Resuscitation/methods , Clinical Protocols , Emergencies , Intraoperative Complications/therapy , Operating Rooms , Patient Care Team/organization & administration , Robotics , Anesthesiology , Gynecology , Humans , Nurse Anesthetists , Robotics/instrumentation , Time-to-Treatment/statistics & numerical data , Urology
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