Armin Akbarzadeh; Hamid Namazi; Ayub Gharebeigi Tavabeh; Seyyed Arash Haghpanah; Doroudchi Alireza
Volume 12, Issue 3 , July 2024, , Pages 117-123
Abstract
Objective: Intra-articular screw penetration is a probable complication of coronoid fracture fixation. Thepresent study aimed to determine the best radiography technique for visualizing the proximal radioulnar joint(PRUJ) space. Moreover, it aimed to determine the safe angle and length of the screw to ...
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Objective: Intra-articular screw penetration is a probable complication of coronoid fracture fixation. Thepresent study aimed to determine the best radiography technique for visualizing the proximal radioulnar joint(PRUJ) space. Moreover, it aimed to determine the safe angle and length of the screw to avoid PRUJ penetrationduring coronoid fracture fixation.Methods: The Mimics software was used to construct a three-dimensional model of a healthy man’s forearmfrom a computer tomography scan. It was analyzed using the Solidworks software to determine the X-ray anglethat clearly showed the PRUJ space to detect penetration of screws from the coronoid process into the PRUJand determine the maximum screw angle and length that could be used without intra-articular penetration. Toverify these findings, a cadaveric study combined with radiographs was conducted.Results: To visualize PRUJ space, the optimal X-ray angle was 13º lateral to the perpendicular line when theforearm was positioned at full supination. If the coronoid process was segmented into zones 1 (closest to theradioulnar joint) to 4 (farthest from the joint), the screw could only be inserted at a right angle in zone 1. In zones2, 3, and 4, inclination angles less than 15, 35, and 60 would prevent intra-articular penetration, respectively.Conclusions: The X-rays could visualize the PRUJ space with an anteroposterior radiograph at an angle of13º ulnar deviation from the perpendicular plane. During coronoid process fracture fixation, shorter screwswith less lateral inclination were safer when inserting screws in the zones of the coronoid process adjacent tothe PRUJ.
Reza Safdari; Jaleh Shoshtarian Malak; Niloofar Mohammadzadeh; Azimeh Danesh Shahraki
Volume 5, Issue 3 , July 2017, , Pages 171-178
Abstract
Objective: To demonstrate an architecture to automate the prehospital emergency process to categorize the specialized care according to the situation at the right time for reducing the patient mortality and morbidity.Methods: Prehospital emergency process were analyzed using existing prehospital management ...
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Objective: To demonstrate an architecture to automate the prehospital emergency process to categorize the specialized care according to the situation at the right time for reducing the patient mortality and morbidity.Methods: Prehospital emergency process were analyzed using existing prehospital management systems, frameworks and the extracted process were modeled using sequence diagram in Rational Rose software. System main agents were identified and modeled via component diagram, considering the main system actors and by logically dividing business functionalities, finally the conceptual architecture for prehospital emergency management was proposed. The proposed architecture was simulated using Anylogic simulation software. Anylogic Agent Model, State Chart and Process Model were used to model the system. Results: Multi agent systems (MAS) had a great success in distributed, complex and dynamic problem solving environments, and utilizing autonomous agents provides intelligent decision making capabilities. The proposed architecture presents prehospital management operations. The main identified agents are: EMS Center, Ambulance, Traffic Station, Healthcare Provider, Patient, Consultation Center, National Medical Record System and quality of service monitoring agent.Conclusion: In a critical condition like prehospital emergency we are coping with sophisticated processes like ambulance navigation health care provider and service assignment, consultation, recalling patients past medical history through a centralized EHR system and monitoring healthcare quality in a real-time manner. The main advantage of our work has been the multi agent system utilization. Our Future work will include proposed architecture implementation and evaluation of its impact on patient quality care improvement.
Mahsa Dehghani; Nazila Moftian; Peyman Rezaei-hachesu; Taha Samad-soltani
Volume 5, Issue 2 , April 2017, , Pages 79-89
Abstract
Objective: To systematically review the current literature of simulation in healthcare including the structured steps in the emergency healthcare sector by proposing a framework for simulation in the emergency department.Methods: For the purpose of collecting the data, PubMed and ACM databases were used ...
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Objective: To systematically review the current literature of simulation in healthcare including the structured steps in the emergency healthcare sector by proposing a framework for simulation in the emergency department.Methods: For the purpose of collecting the data, PubMed and ACM databases were used between the years 2003 and 2013. The inclusion criteria were to select English-written articles available in full text with the closest objectives from among a total of 54 articles retrieved from the databases. Subsequently, 11 articles were selected for further analysis.Results: The studies focused on the reduction of waiting time and patient stay, optimization of resources allocation, creation of crisis and maximum demand scenarios, identification of overcrowding bottlenecks, investigation of the impact of other systems on the existing system, and improvement of the system operations and functions. Subsequently, 15 simulation steps were derived from the relevant studies after an expert’s evaluation.Conclusion: The 10-steps approach proposed on the basis of the selected studies provides simulation and planning specialists with a structured method for both analyzing problems and choosing best-case scenarios. Moreover, following this framework systematically enables the development of design processes as well as software implementation of simulation problems.
