Development and validation of the MMCD score to predict kidney replacement therapy in COVID-19 patients
Authors: Figueiredo Flávio de Azevedo , Ramos Lucas Emanuel Ferreira , Silva Rafael Tavares , Ponce Daniela , 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 , 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 
Published: September 2022

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.