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ABC2-SPH risk score for in-hospital mortality in COVID-19 patients: development, external validation and comparison with other available scores

Authors :
Natalia Lima Rangel
Daniel Taiar Marinho Oliveira Ferrara
Natalia da Cunha Severino Sampaio
Máderson Alvares de Souza Cabral
Angelinda Rezende Bhering
Emanuele Marianne Souza Kroger
Rafael Lima Rodrigues de Carvalho
Lucas de Deus Sousa
Ana Luiza Bahia Alves Scotton
Roger Mendes de Abreu
Fernando Graca Aranha
Meire Pereira de Figueiredo
Guilherme Fagundes Nascimento
Luanna da Silva Monteiro
Frederico Bartolazzi
Juliana Machado Rugolo
Maria Aparecida Camargos Bicalho
Luciana Siuves Ferreira Couto
Rochele Mosmann Menezes
Luciane Kopittke
Natalia Trifiletti Crespo
Daniela Ponce
Eric Boersma
Patricia Klarmann Ziegelmann
Amanda de Oliveira Maurilio
Carisi Anne Polanczyk
Raquel Lutkmeier
Christiane Correa Rodrigues cimini
Bruno Mateus de Castro
Giovanna Grunewald Vietta
José Miguel Chatkin
Neimy Ramos de Oliveira
Thaís Lorenna Souza Sales
Lilian Santos Pinheiro
Angelica Aparecida Coelho Madureira
Gisele Alsina Nader Bastos
Elayne Crestani Pereira
Fernanda Barbosa Lucas
Karen Cristina Jung Rech Pontes
Maria Angelica Pires Ferreira
Liliane Souto Pacheco
Raphael Castro Martins
Andre Soares de Moura Costa
Helena Duani
Roberta Xavier Campos
Andre Pinheiro Weber
Matheus Carvalho Alves Nogueira
Rodolfo Lucas Silva Mourato
Silvia Ferreira Araujo
Renan Goulart Finger
Adrian Sanchez Montalva
Reginaldo Aparecido Valacio
Daniel Vitorio Silveira
Magda Carvalho Pires
Maíra Viana Rego Souza e Silva
Marcela Goncalves Trindade Tofani
Milena Soriano Marcolino
Saionara Cristina Francisco
Karen Brasil Ruschel
Tatiani Oliveira Fereguetti
L. E. F. Ramos
Israel Júnior Borges do Nascimento
Thaiza Simonia Marinho Albino de Araujo
Silvana Mangeon Mereilles Guimaraes
Rafaela dos Santos Charao de Almeida
Marcus Vinicius de Melo Andrade
Joanna d'Arc Lyra Batista
Andressa Barreto Glaeser
Veridiana Baldon dos Santos Santos
Henrique Cerqueira Guimaraes
Vitor Augusto Lima do Vale
Joice Coutinho de Alvarenga
Heloisa Reniers Vianna
Ricardo Bertoglio Cardoso
Petrônio José de Lima Martelli
Glicia Cristina de Castro Madeira
Fernando Anschau
Tatiana Kurtz
Milton Henriques Guimaraes Junior
Maria Clara Pontello Barbosa Lima
Mariana Frizzo de Godoy
Luana Martins Oliveira
Kauane Aline Maciel dos Santos
Gabriela Petry Crestani
Luisa Elem Almeida Santos
Fernando Antônio Botoni
Carla Thais Candida Alves da Silva
Felipe Barbosa Vallt
Rufino de Freitas Silva
Cintia Alcantara de Carvalho
Barbara Lopes Farace
Diego Henrique de Vasconcelos
Luis Cesar Souto de Moura
Alexandre Vargas Schwarbold
Karina Paula Medeiros Prado Martins
Julia Drumond Parreiras de Morais
Luís César de Castro
Pedro Ledic Assaf
Maiara Anschau Floriani
Roberta Pozza
Maira Dias Souza
Isabela Moraes Gomes
Susany Anastacia Pereira
Thainara Conceicao de Oliveira
Yuri Carlotto Ramires
Carolina Marques Ramos
Israel Molina Romero
Caroline Danubia Gomes
Rafael Guimarães Tavares da Silva
Marilia Mastrocolla de Almeida Cardoso
Berta Raventós
Leonardo Seixas de Oliveira
Virginia Mara Reis Gomes
Talita Fischer Oliveira
Thulio Henrique Oliveira Diniz
Julia Di Sabatino Santos Guimaraes
Ana Paula Beck da Silva Etges
Helena Carolina Noal
Marcelo Carneiro
Edilson Cezar
Publication Year :
2021
Publisher :
Cold Spring Harbor Laboratory, 2021.

Abstract

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 studySettingThe 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 mortalityResultsMedian (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/FiO2ratio, 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?Rapid scoring systems may be very useful for fast and effective assessment of COVID-19 patients in the emergency department.The majority of available scores have high risk of bias and lack benefit to clinical decision making.Derivation and validation studies in low- and middle-income countries, including Latin America, are scarce.What this study addsABC2-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.This 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.A free web-based calculator is available and may help healthcare practitioners to estimate the expected risk of mortality for patients at hospital presentation.

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........00205d9e12af4c693d4f165f1c43a72d
Full Text :
https://doi.org/10.1101/2021.02.01.21250306