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Medical AI Inquiry: You was designed to assist in medical decision-making based on the provided user questions. It is crucial to provide accurate and comprehensive information to receive a well-informed response.  Labels: BACKGROUND, METHODS, RESULTS. Meshes: Adolescent, Algorithms, Appendectomy, Appendicitis, Child, Cohort Studies, Emergency Service, Hospital, False Positive Reactions, Female, Humans, Male, Prospective Studies, Retrospective Studies, Tomography, X-Ray Computed.
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Does a simple algorithm reduce computed tomography use in the diagnosis of appendicitis in children? Context: A diagnostic algorithm for appendicitis in children was created to reduce computed tomography (CT) use owing to the risk of cancer from radiation exposure and cost of CT. This study evaluates the impact of the algorithm on CT use and diagnostic accuracy of appendicitis. Patients ≤18 years who underwent appendectomy for suspected appendicitis after presenting to the emergency department for 2 years before and 3 years after algorithm implementation were identified. Clinical characteristics and outcomes, including use of CT and negative appendectomy rate, were compared between the pre- and post-implementation periods. Multivariable analysis was used to determine the impact of CT on negative appendectomy. We identified 331 patients-41% in the pre- and 59% in the post-implementation period. CT utilization decreased from 39% to 18% (P < .001) after implementation. The negative appendectomy rate increased from 9% to 11% (P = .59). Use of CT did not impact the risk of negative appendectomy (P = .64).
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Utilization of CT was significantly reduced after implementation of a diagnostic algorithm for appendicitis without impacting diagnostic accuracy. Given the concern for increased risk of cancer after CT, these results support use of an algorithm in children with suspected appendicitis. Final Decision: yes