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1.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22278550

RESUMO

IntroductionWith the COVID-19 pandemic, hospitals in low-income countries were faced with a triple challenge. First, a large number of patients required hospitalization because of the infections more severe symptoms. Second, there was a lack of systematic and broad testing policies for early identification of cases. Third, there were weaknesses in the integration of information systems, which led to the need to search for available information from the hospital information systems. Accordingly, it is also important to state that relevant aspects of COVID-19s natural history had not yet been fully clarified. The aim of this research protocol is to present the strategies of a Brazilian network of hospitals to perform systematized data collection on COVID-19 through the World Health Organization (WHO) Platform. Methods and AnalysisThis is a multicenter project among Brazilian hospitals to provide data on COVID-19 through the WHO global platform, which integrates patient care information from different countries. From October 2020 to March 2021, a committee worked on defining a flowchart for this platform, specifying the variables of interest, data extraction standardization and analysis. Ethics and DisseminationThis protocol was approved by the Research Ethics Committee (CEP) of the Research Coordinating Center of Brazil (CEP of the Hospital Nossa Senhora da Conceicao), on January 29, 2021, under approval No. 4.515.519 and by the National Research Ethics Commission (CONEP), on February 5, 2021, under approval No. 4.526.456. The project results will be explained in WHO reports and published in international peer-reviewed journals, and summaries will be provided to the funders of the study. Strengths and limitations of this studyAs the study involves a convenience and non-probabilistic sample of patients hospitalized in health units, it may not represent the population of patients with COVID-19 hospitalized in the country. However, the information generated by this research can serve as a basis for the development of maps of the evolution of SARS-CoV-2 infection and public policies to face pandemics. It is a study that uses secondary data, and therefore, information bias may occur, but on the other hand, it has a low cost and facilitates a population-based study with national coverage. Article SummaryThis is a multicenter project among Brazilian hospitals to provide data on COVID-19 through the WHO global platform. It is expected to deepen knowledge about the pandemic scenario and help hospital institutions to develop preventive measures, health service protocols and strengthen the training of teams in the existing complications.

2.
Milena Soriano Marcolino; Magda Carvalho Pires; Lucas Emanuel Ferreira Ramos; Rafael Tavares Silva; Luana Martins Oliveira; Rafael Lima Rodrigues de Carvalho; Rodolfo Lucas Silva Mourato; Adrian Sanchez Montalva; Berta Raventos; Fernando Anschau; Jose Miguel Chatkin; Matheus Carvalho Alves Nogueira; Milton Henriques Guimaraes Junior; Giovanna Grunewald Vietta; Helena Duani; Daniela Ponce; Patricia Klarmann Ziegelmann; Luis Cesar de Castro; Karen Brasil Ruschel; Christiane Correa Rodrigues Cimini; Saionara Cristina Francisco; Maiara Anschau Floriani; Guilherme Fagundes Nascimento; Barbara Lopes Farace; Luanna da Silva Monteiro; Maira Viana Rego Souza e Silva; Thais Lorenna Souza Sales; Karina Paula Medeiros Prado Martins; Israel Junior Borges do Nascimento; Tatiani Oliveira Fereguetti; Daniel Taiar Marinho Oliveira Ferrara; Fernando Antonio Botoni; Ana Paula Beck da Silva Etges; Eric Boersma; Carisi Anne Polanczyk; Alexandre Vargas Schwarbold; Amanda Oliveira Maurilio; Ana Luiza Bahia Alves Scotton; Andre Pinheiro Weber; Andre Soares de Moura Costa; Andressa Barreto Glaeser; Angelica Aparecida Coelho Madureira; Angelinda Rezende Bhering; Bruno Mateus Castro; Carla Thais Candida Alves da Silva; Carolina Marques Ramos; Caroline Danubia Gomes; Cintia Alcantara de Carvalho; Daniel Vitorio Silveira; Diego Henrique de Vasconcelos; Edilson Cezar; Elayne Crestani Pereira; Emanuele Marianne Souza Kroger; Felipe Barbosa Vallt; Fernanda Barbosa Lucas; Fernando Graca Aranha; Frederico Bartolazzi; Gabriela Petry Crestani; Gisele Alsina Nader Bastos; Glicia Cristina de Castro Madeira; Helena Carolina Noal; Heloisa Reniers Vianna; Henrique Cerqueira Guimaraes; Isabela Moraes Gomes; Israel Molina Romero; Joanna dArc Lyra Batista; Joice Coutinho de Alvarenga; Julia Di Sabatino Santos Guimaraes; Julia Drumond Parreiras de Morais; Juliana Machado Rugolo; Karen Cristina Jung Rech Pontes; Kauane Aline Maciel dos Santos; Leonardo Seixas de Oliveira; Lilian Santos Pinheiro; Liliane Souto Pacheco; Lucas de Deus Sousa; Luciana Siuves Ferreira Couto; Luciane Kopittke; Luis Cesar Souto de Moura; Luisa Elem Almeida Santos; Maderson Alvares de Souza Cabral; Maira Dias Souza; Marcela Goncalves Trindade Tofani; Marcelo Carneiro; Marcus Vinicius de Melo Andrade; Maria Angelica Pires Ferreira; Maria Aparecida Camargos Bicalho; Maria Clara Pontello Barbosa Lima; Mariana Frizzo de Godoy; Marilia Mastrocolla de Almeida Cardoso; Meire Pereira de Figueiredo; Natalia da Cunha Severino Sampaio; Natalia Lima Rangel; Natalia Trifiletti Crespo; Neimy Ramos de Oliveira; Pedro Ledic Assaf; Petronio Jose de Lima Martelli; Rafaela dos Santos Charao de Almeida; Raphael Castro Martins; Raquel Lutkmeier; Reginaldo Aparecido Valacio; Renan Goulart Finger; Ricardo Bertoglio Cardoso; Roberta Pozza; Roberta Xavier Campos; Rochele Mosmann Menezes; Roger Mendes de Abreu; Rufino de Freitas Silva; Silvana Mangeon Mereilles Guimaraes; Silvia Ferreira Araujo; Susany Anastacia Pereira; Talita Fischer Oliveira; Tatiana Kurtz; Thainara Conceicao de Oliveira; Thaiza Simonia Marinho Albino de Araujo; Thulio Henrique Oliveira Diniz; Veridiana Baldon dos Santos Santos; Virginia Mara Reis Gomes; Vitor Augusto Lima do Vale; Yuri Carlotto Ramires.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-21250306

RESUMO

ObjectiveTo develop and validate a rapid scoring system at hospital admission for predicting in-hospital mortality in patients hospitalized with coronavirus disease 19 (COVID-19), and to compare this score with other existing ones. DesignCohort study SettingThe Brazilian COVID-19 Registry has been conducted in 36 Brazilian hospitals in 17 cities. Logistic regression analysis was performed to develop a prediction model for in-hospital mortality, based on the 3978 patients that were admitted between March-July, 2020. The model was then validated in the 1054 patients admitted during August-September, as well as in an external cohort of 474 Spanish patients. ParticipantsConsecutive symptomatic patients ([≥]18 years old) with laboratory confirmed COVID-19 admitted to participating hospitals. Patients who were transferred between hospitals and in whom admission data from the first hospital or the last hospital were not available were excluded, as well those who were admitted for other reasons and developed COVID-19 symptoms during their stay. Main outcome measuresIn-hospital mortality ResultsMedian (25th-75th percentile) age of the model-derivation cohort was 60 (48-72) years, 53.8% were men, in-hospital mortality was 20.3%. The validation cohorts had similar age distribution and in-hospital mortality. From 20 potential predictors, seven significant variables were included in the in-hospital mortality risk score: age, blood urea nitrogen, number of comorbidities, C-reactive protein, SpO2/FiO2 ratio, platelet count and heart rate. The model had high discriminatory value (AUROC 0.844, 95% CI 0.829 to 0.859), which was confirmed in the Brazilian (0.859) and Spanish (0.899) validation cohorts. Our ABC2-SPH score showed good calibration in both Brazilian cohorts, but, in the Spanish cohort, mortality was somewhat underestimated in patients with very high (>25%) risk. The ABC2-SPH score is implemented in a freely available online risk calculator (https://abc2sph.com/). ConclusionsWe designed and validated an easy-to-use rapid scoring system based on characteristics of COVID-19 patients commonly available at hospital presentation, for early stratification for in-hospital mortality risk of patients with COVID-19. Summary boxesWhat is already known on this topic? O_LIRapid scoring systems may be very useful for fast and effective assessment of COVID-19 patients in the emergency department. C_LIO_LIThe majority of available scores have high risk of bias and lack benefit to clinical decision making. C_LIO_LIDerivation and validation studies in low- and middle-income countries, including Latin America, are scarce. C_LI What this study adds O_LIABC2-SPH employs seven well defined variables, routinely assessed upon hospital presentation: age, number of comorbidities, blood urea nitrogen, C reactive protein, Spo2/FiO2 ratio, platelets and heart rate. C_LIO_LIThis easy-to-use risk score identified four categories at increasing risk of death with a high level of accuracy, and displayed better discrimination ability than other existing scores. C_LIO_LIA free web-based calculator is available and may help healthcare practitioners to estimate the expected risk of mortality for patients at hospital presentation. C_LI

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