Background and Aims:Anaesthesia practice demands medical knowledge and skills as essential components for patient management in peri-operative emergencies. Since all residents are not exposed to such situations during their residency, training them using simulation technology could bridge this knowledge and skill gap. The aim of this study was to train and evaluate residents to manage anaesthesia emergencies on high fidelity simulators.Methods:Kirkpatrick model of program evaluation was carried out. Resident reaction was captured using a satisfaction questionnaire and the change in knowledge was assessed using pre-test and post-test Multiple Choice Questions (MCQs). Six scenarios were created and executed on a human patient simulator (HPS). All 22 residents participated in this teaching learning method. The steps of simulation teaching included pre-test, pre-briefing, orientation to manikins, performing/scribe, debriefing, feedback questionnaire, and post-test. The satisfaction questionnaire was administered following the second and fourth scenario.Results:95% residents agreed on overall satisfaction, that it helps in building team dynamics and clinical reasoning. All students agreed that this teaching had positive professional impact. 14% residents felt they were anxious during the class. The items in the questionnaire had a Cronbach's α value of 0.9. The mean score for pre-test was 24.22 ± 7 (Mean ± SD) and the post-test was 47.18 ± 5.6, the difference between the scores were statistically significant (P = 0.007).Conclusion:The use of high-fidelity simulation to train anaesthesia residents resulted in greater satisfaction scores and improved the residents' reasoning skills.

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Chest wall hemangiomas are rare tumors that may originate within the soft tissue or from the ribs. Intramuscular hemangioma is infrequent, representing less than 1 % of all hemangiomas, and the localization in the chest wall is even less frequent. They are typically cutaneous in location, large, and poorly circumscribed and can be locally destructive. We present a case of a 34-year-old lady presented with firm lump 3 × 3 cm in left upper and inner quadrant of left breast well defined borders, non-pulsatile and restricted mobility. Sono-mammogram was suggestive of ill-defined lesion at 10 o'clock position. CT chest was conclusive of chest wall hemangioma. The patient underwent excision of the lump. HPE was suggestive of cavernous hemangioma. Cavernous hemangioma typically manifest at birth or before the age of 30 years. CT is more sensitive than plain radiography in detecting phleboliths, which are present in approximately 30 % of cavernous hemangiomas. Surgical excision would be treatment of choice. In this case, the site of the lesion was in the breast clinically mimicking that of a fibroadenoma which warrants hemangioma as a differential diagnosis.

Background: The responsibility of nurses is early clinical deterioration and taking appropriate action. Knowledge and proficiency in Code Blue protocols come handy, which lacks in most nurses recognizing. Simulation-based learning plays a role in improving performance and confidence in handling such situations. This goal-based method of program evaluation aims to examine Code Blue training programs and compare them with current literature and established professional standards while assessing participants’ experience and change in knowledge to this educational method. Materials and methods: Following ethical approval, a prospective interventional study was conducted in the simulation center of a private medical college in Mangalore on 65 nursing students. A pretest was given to the participants on the day of the session to assess their baseline understanding followed by prebriefing, all previously having received didactic lectures on Code Blue protocol, crash cart, and cardiac arrest algorithms. They were divided into three batches and each batch performed on crash cart and cardiac arrest stations using an electrocardiogram simulator. A simulated drill was enacted by the faculty on managing a Code Blue event and a discussion was followed. Nurses underwent two simulated scenarios, shockable and nonshockable cardiac arrest algorithms, followed by debriefing. Posttest and feedback form was asked to be filled. Results: A significant increase in mean% from pretest to posttest (55.69–77.33%) following simulated drills. Conclusion: The use of simulation to train nurses in Code Blue scenarios records greater satisfaction and improvement in clinical reasoning, knowledge, and skills. Hence, the incorporation of simulation teaching in training of those involved in caring for high-risk patients is the need of the hour. How to cite this article: D’Cunha RJ, Fernandes SF, Sherif L. Utility of Simulation as a Teaching Tool for Nursing Staff Involved in Code Blue Management. Indian J Crit Care Med 2021;25(8):878–880.

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