Development and validation of the MMCD score to predict kidney replacement therapy in COVID-19 patients

• Autor(a) principal: Figueiredo, Flávio de Azevedo
• Data de Publicação: 2022
• Outros Autores: Ramos, Lucas Emanuel Ferreira, Silva, Rafael Tavares, Ponce, Daniela [UNESP], de Carvalho, Rafael Lima Rodrigues, Schwarzbold, Alexandre Vargas, Maurílio, Amanda de Oliveira, Scotton, Ana Luiza Bahia Alves, Garbini, Andresa Fontoura, Farace, Bárbara Lopes, Garcia, Bárbara Machado, da Silva, Carla Thais Cândida Alves, Cimini, Christiane Corrêa Rodrigues, de Carvalho, Cíntia Alcantara, Dias, Cristiane dos Santos, Silveira, Daniel Vitório, Manenti, Euler Roberto Fernandes, Cenci, Evelin Paola de Almeida, Anschau, Fernando, Aranha, Fernando Graça, de Aguiar, Filipe Carrilho, Bartolazzi, Frederico, Vietta, Giovanna Grunewald, Nascimento, Guilherme Fagundes, Noal, Helena Carolina, Duani, Helena, Vianna, Heloisa Reniers, Guimarães, Henrique Cerqueira, de Alvarenga, Joice Coutinho, Chatkin, José Miguel, de Morais, Júlia Drumond Parreiras, Machado-Rugolo, Juliana [UNESP], Ruschel, Karen Brasil, Martins, Karina Paula Medeiros Prado, Menezes, Luanna Silva Monteiro, Couto, Luciana Siuves Ferreira, de Castro, Luís César, Nasi, Luiz Antônio, Cabral, Máderson Alvares de Souza, Floriani, Maiara Anschau, Souza, Maíra Dias, Souza-Silva, Maira Viana Rego, Carneiro, Marcelo, de Godoy, Mariana Frizzo, Bicalho, Maria Aparecida Camargos, Lima, Maria Clara Pontello Barbosa, Aliberti, Márlon Juliano Romero, Nogueira, Matheus Carvalho Alves, Martins, Matheus Fernandes Lopes, Guimarães-Júnior, Milton Henriques, Sampaio, Natália da Cunha Severino, de Oliveira, Neimy Ramos, Ziegelmann, Patricia Klarmann, Andrade, Pedro Guido Soares, Assaf, Pedro Ledic, Martelli, Petrônio José de Lima, Delfino-Pereira, Polianna, Martins, Raphael Castro, Menezes, Rochele Mosmann, Francisco, Saionara Cristina, Araújo, Silvia Ferreira, Oliveira, Talita Fischer, de Oliveira, Thainara Conceição, Sales, Thaís Lorenna Souza, Avelino-Silva, Thiago Junqueira, Ramires, Yuri Carlotto, Pires, Magda Carvalho, Marcolino, Milena Soriano
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1186/s12916-022-02503-0; http://hdl.handle.net/11449/241704
• topic: Acute kidney injury; COVID-19; Kidney replacement therapy; Risk factors; Risk prediction; Score

Background: Acute kidney injury (AKI) is frequently associated with COVID-19, and the need for kidney replacement therapy (KRT) is considered an indicator of disease severity. This study aimed to develop a prognostic score for predicting the need for KRT in hospitalised COVID-19 patients, and to assess the incidence of AKI and KRT requirement. Methods: This study is part of a multicentre cohort, the Brazilian COVID-19 Registry. A total of 5212 adult COVID-19 patients were included between March/2020 and September/2020. Variable selection was performed using generalised additive models (GAM), and least absolute shrinkage and selection operator (LASSO) regression was used for score derivation. Accuracy was assessed using the area under the receiver operating characteristic curve (AUC-ROC). Results: The median age of the model-derivation cohort was 59 (IQR 47–70) years, 54.5% were men, 34.3% required ICU admission, 20.9% evolved with AKI, 9.3% required KRT, and 15.1% died during hospitalisation. The temporal validation cohort had similar age, sex, ICU admission, AKI, required KRT distribution and in-hospital mortality. The geographic validation cohort had similar age and sex; however, this cohort had higher rates of ICU admission, AKI, need for KRT and in-hospital mortality. Four predictors of the need for KRT were identified using GAM: need for mechanical ventilation, male sex, higher creatinine at hospital presentation and diabetes. The MMCD score had excellent discrimination in derivation (AUROC 0.929, 95% CI 0.918–0.939) and validation (temporal AUROC 0.927, 95% CI 0.911–0.941; geographic AUROC 0.819, 95% CI 0.792–0.845) cohorts and good overall performance (Brier score: 0.057, 0.056 and 0.122, respectively). The score is implemented in a freely available online risk calculator (https://www.mmcdscore.com/). Conclusions: The use of the MMCD score to predict the need for KRT may assist healthcare workers in identifying hospitalised COVID-19 patients who may require more intensive monitoring, and can be useful for resource allocation.