Background: Digital games play an important role in the learning process, and are used to teach languages and train surgeons. Based on theoretical frameworks that prove the relevance of games in teaching, we began developing a computer game that simulates a hospital, so that medical students could analyze clinical cases from different areas of medical science, including neurology, while playing a game. Objectives: Create a game to teach medicine in a ludic manner. Design and Setting: The game is being developed by Doctors, Programmers, Engineers, students of Medicine, Information Technology (IT), Design and Architecture from Brazil and Peru, in a startup incubator from Centro Universitário de Belo Horizonte, in partnership with the Universidad Científica del Sur, Lima, Peru. Methods: Medical students, under the supervision of Doctors, defined behavioral algorithms, based on Brazilian guidelines, and outcomes (i.e. gain or loss of points, clinical improvement or worsening) addressing different topics in Medicine. Design students created the artistic elements. IT students programmed the prototype of the game using Unity software. Results: An expandable minimum viable product was obtained, with artistic elements of two characters, one being a non-playable character, a scenario, and a dialogue script based on a clinical examination of a patient. Conclusion: The software is running, with the launch of the pre-alpha version in December 2021. A scoring system will be included for qualitative assessment of the player, as well as feedback reports to educate the player. We speculate this game will improve accuracy and clinical skills of medical students.

Background: Small case series of patients with active cancer and coronavirus infection have been described since the beginning of the pandemic. The patients most affected by this infection are those with lung cancer but it also affects other types of cancer such as breast cancer. We described the characteristics of patients with breast cancer and COVID 19, their associated risk factors, treatment and evolution.Methods: We reviewed 2216 medical records of all patients admitted to hospitalization with COVID-19 diagnosis between 5 March and 13 May 2020. Study data were collected and managed using RedCap electronic data capture tools. We described breast cancer patients, associated risk factors, mortality and outcome.Results: We detected 85/2216patients cancer with a mortality rate 47% (40/85). Of all cancer patients, 11% (10/85) had breast cancer. Median age breast cancer patients was 70.5 years old (35-86). Most frecuent staging was locally advanced (50 %, 5/10) and most of them were on hormone therapy (50%, 5/10). As associated risk factors, 20% (2/10) had heart disease, 50% (5/10) had hypertension, 20 (2/10) were obese, 30% (3/10) had diabetes, 40% (4/10) had dyslipemia and only 10% (1/10) was smoker. Half the patients 50% (5/10) had bilateral pneumonia, none of them were admitted to the ICU and 20% (2/10) died. All patients were treated with the combination of azithromycin and hydroxychloroquine and 40% (4/10) with lopinavir/ritonavir. Mortality was associate with high LDH levels (1529 vs. 264 U/L, p¼0,0002), high PCR levels (159.15 vs. 29 mg/L, p¼0.0140), ARDS (1/1 vs. 1/9 without ARDS p¼0.035). A posible relation has been found with history of hypertension (2/5 vs. 0/5 without hypertension, p¼0.114) and bilateral pneumonia (2/5 vs. 0/5, p¼ 0.114).Conclusions: COVID 19 appears to have lower mortality in breast cancer patients than in other tumor types. High LDH and PCR levels and ARDS could be related with increased risk of death. Combined treatment in these patients with azithromycin and hydroxychloroquine might be a good option.Legal entity responsible for the study: The authors.

Background Brazillian authorities reported a total of 16.3 million cases and 454.000 deaths during COVID-19 pandemic in Brazil by may 2021. It became necessary to educate healthcare professionals on diagnosis and treatment of the syndrome. Game based learning surfaced as an effective alternative, since it promotes critical thinking and problem solving skills. A team of Brazilian and Peruvian students, physicians, designers and programmers gathered to create a decision based computer game that simulates a hospital scenario and allows medical students to analise, make decisions and receive feedback. This work describes the creative process and showcase the initial version of the software. Methods Professors and students of Medicine, Information Technology (IT), Design and Architecture from Brazil and Peru assembled a team in order to develop the computer game. Clinical cases were created by the medical students and professors, comprising medical procedures for the treatment and management of COVID 19, and a video game script was developed exploring gamification principles of challenge, objectivity, persistence, failure, reward and feedback. Algorithms (image 1) were created, under supervision of professors of Medicine, to define possible courses of action and outcomes (e.g. gain or loss of points, improvement or worsening of the patient). Students of Design created artistic elements, and IT students programmed with a game engine software. This fluxogram, written in portuguese, describes in detail all the possible courses of actions that can be exercised by the player. It is created by a team of Professors of Medicine and medical students, in accordance with evidence-based guidelines. Primarily, this document guides the programmers and designers throughout the development phase of the game. Results Initially, an expandable minimum viable product was obtained. The game, visualized on image 2, consists in a non-playable character and a playable character (i.e. doctor), with a scenario and a dialogue script simulating a clinical examination of a COVID 19 patient. The player can interact with certain elements within the game, e.g. the computer and other characters, to retrieve test results or start dialogues with relevant information. Hospital scenario and dialogue window between doctor (player in black) and patient (non playable character) are displayer in the game engine software (Unity 2D). On the bottom half of the screen, the dialogue box allows the player to collect the patient’s medical history. The player can interact with certain elements to obtain relevant information to make decision and progress in the game. Conclusion The game allows medical students to practice diagnosis and treatment of COVID 19. Future versions will include assessment reports of player’s actions, and a new score system will be implemented. New diseases will be incorporated in the gameplay to match the variety of scenarios offered by real hospitals and patients. Artificial intelligence will be employed to optimize gameplay, feedback and learning. Disclosures All Authors: No reported disclosures