ABSTRACT
Objective To evaluate the incidence of COVID-19 and its main outcomes in rheumatic disease (RD) patients on hydroxychloroquine (HCQ) compared to household cohabitants (HC).Methods This is a 24-week nationwide prospective multi-centre cohort with a control group without RD and not using HCQ. All participants were monitored through scheduled phone interviews performed by health professionals. Details regarding COVID-19 symptoms, and epidemiological, clinical, and demographic data were recorded on a specific web-based platform. COVID-19 was defined according to the Brazilian Ministry of Health criteria and classified as mild, moderate or severe.Results A total of 9,585 participants, 5,164 (53.9%) RD patients on HCQ and 4,421 (46.1%) HC were enrolled from March 29th, 2020 to September 30th, 2020, according to the eligibility criteria. COVID-19 confirmed cases were higher in RD patients than in cohabitants [728 (14.1%) vs. 427 (9.7%), p<0.001] in a 24-week follow-up. However, there was no significant difference regarding outcomes related to moderate/ severe COVID-19 (7.1% and 7.3%, respectively, p=0.896). After multiple adjustments, risk factors associated with hospitalisation were age over 65 (HR=4.5;95%CI 1.35-15.04, p=0.014) and cardiopathy (HR=2.57;95%CI 1.12-5.91, p=0.026). The final survival analysis demonstrated the probability of dying in 180 days after a COVID-19 diagnosis was significantly higher in patients over 65 years (HR=20.8;95%CI 4.5-96.1) and with 2 or more comorbidities (HR=10.8;95%CI 1.1-107.9 and HR=24.8;95%CI 2.5-249.3, p=0.006, respectively).Conclusion Although RD patients have had a higher COVID-19 incidence than individuals from the same epidemiological background, the COVID-19 severity was related to traditional risk factors, particularly multiple comorbidities and age, and not to underlying RD and HCQ.
ABSTRACT
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.
ABSTRACT
OBJECTIVES: To evaluate the incidence of COVID-19 and its main outcomes in rheumatic disease (RD) patients on hydroxychloroquine (HCQ) compared to household cohabitants (HC). METHODS: This is a 24-week nationwide prospective multi-centre cohort with a control group without RD and not using HCQ. All participants were monitored through scheduled phone interviews performed by health professionals. Details regarding COVID-19 symptoms, and epidemiological, clinical, and demographic data were recorded on a specific web-based platform. COVID-19 was defined according to the Brazilian Ministry of Health criteria and classified as mild, moderate or severe. RESULTS: A total of 9,585 participants, 5,164 (53.9%) RD patients on HCQ and 4,421 (46.1%) HC were enrolled from March 29th, 2020 to September 30th, 2020, according to the eligibility criteria. COVID-19 confirmed cases were higher in RD patients than in cohabitants [728 (14.1%) vs. 427 (9.7%), p<0.001] in a 24-week follow-up. However, there was no significant difference regarding outcomes related to moderate/ severe COVID-19 (7.1% and 7.3%, respectively, p=0.896). After multiple adjustments, risk factors associated with hospitalisation were age over 65 (HR=4.5;95%CI 1.35-15.04, p=0.014) and cardiopathy (HR=2.57;95%CI 1.12-5.91, p=0.026). The final survival analysis demonstrated the probability of dying in 180 days after a COVID-19 diagnosis was significantly higher in patients over 65 years (HR=20.8;95%CI 4.5-96.1) and with 2 or more comorbidities (HR=10.8;95%CI 1.1-107.9 and HR=24.8;95%CI 2.5-249.3, p=0.006, respectively). CONCLUSIONS: Although RD patients have had a higher COVID-19 incidence than individuals from the same epidemiological background, the COVID-19 severity was related to traditional risk factors, particularly multiple comorbidities and age, and not to underlying RD and HCQ.