BMC Nephrology (Oct 2023)
Temporal validation of the MMCD score to predict kidney replacement therapy and in-hospital mortality in COVID-19 patients
- Vanessa das Graças José Ventura,
- Polianna Delfino Pereira,
- Magda Carvalho Pires,
- Alisson Alves Asevedo,
- Alzira de Oliveira Jorge,
- Ana Carolina Pitanga dos Santos,
- André Soares de Moura Costa,
- Angélica Gomides dos Reis Gomes,
- Beatriz Figueiredo Lima,
- Bruno Porto Pessoa,
- Christiane Corrêa Rodrigues Cimini,
- Claudio Moisés Valiense de Andrade,
- Daniela Ponce,
- Danyelle Romana Alves Rios,
- Elayne Crestani Pereira,
- Euler Roberto Fernandes Manenti,
- Evelin Paola de Almeida Cenci,
- Felício Roberto Costa,
- Fernando Anschau,
- Fernando Graça Aranha,
- Flavia Maria Borges Vigil,
- Frederico Bartolazzi,
- Gabriella Genta Aguiar,
- Genna Maira Santos Grizende,
- Joanna d’Arc Lyra Batista,
- João Victor Baroni Neves,
- Karen Brasil Ruschel,
- Letícia do Nascimento,
- Lucas Moyses Carvalho de Oliveira,
- Luciane Kopittke,
- Luís César de Castro,
- Manuela Furtado Sacioto,
- Marcelo Carneiro,
- Marcos André Gonçalves,
- Maria Aparecida Camargos Bicalho,
- Mônica Aparecida da Paula Sordi,
- Natália da Cunha Severino Sampaio,
- Pedro Gibson Paraíso,
- Rochele Mosmann Menezes,
- Silvia Ferreira Araújo,
- Vivian Costa Morais de Assis,
- Katia de Paula Farah,
- Milena Soriano Marcolino
Affiliations
- Vanessa das Graças José Ventura
- Medical School and University Hospital, Universidade Federal de Minas Gerais
- Polianna Delfino Pereira
- Department of Internal Medicine, Medical School, Universidade Federal de Minas Gerais
- Magda Carvalho Pires
- Department of Statistics, Universidade Federal de Minas Gerais
- Alisson Alves Asevedo
- Universidade Federal Dos Vales Do Jequitinhonha E Mucuri (UFVJM)
- Alzira de Oliveira Jorge
- Medical School and University Hospital, Universidade Federal de Minas Gerais
- Ana Carolina Pitanga dos Santos
- Faculdade de Ciências Médicas de Minas Gerais
- André Soares de Moura Costa
- Hospitais da Rede Mater Dei
- Angélica Gomides dos Reis Gomes
- Hospitais da Rede Mater Dei
- Beatriz Figueiredo Lima
- Medical School and University Hospital, Universidade Federal de Minas Gerais
- Bruno Porto Pessoa
- Hospital Júlia Kubitschek
- Christiane Corrêa Rodrigues Cimini
- Universidade Federal Dos Vales Do Jequitinhonha E Mucuri (UFVJM)
- Claudio Moisés Valiense de Andrade
- Computer Science Department, Universidade Federal de Minas Gerais
- Daniela Ponce
- Botucatu Medical School, Universidade Estadual Paulista “Júlio de Mesquita Filho”
- Danyelle Romana Alves Rios
- Hospital São João de Deus (Fundação Geraldo Correa)
- Elayne Crestani Pereira
- Hospital SOS Cárdio
- Euler Roberto Fernandes Manenti
- Hospital Mãe de Deus
- Evelin Paola de Almeida Cenci
- Hospital Universitário Canoas
- Felício Roberto Costa
- Hospital Metropolitano Odilon Behrens
- Fernando Anschau
- Hospital Nossa Senhora da Conceição
- Fernando Graça Aranha
- Hospital SOS Cárdio
- Flavia Maria Borges Vigil
- Hospital Metropolitano Doutor Célio de Castro
- Frederico Bartolazzi
- Hospital Santo Antônio
- Gabriella Genta Aguiar
- Universidade José Do Rosário Vellano (UNIFENAS)
- Genna Maira Santos Grizende
- Santa Casa de Misericórdia de Belo Horizonte
- Joanna d’Arc Lyra Batista
- Institute for Health Technology Assessment (IATS/ CNPq)
- João Victor Baroni Neves
- Faculdade de Ciências Médicas de Minas Gerais
- Karen Brasil Ruschel
- Hospital Universitário Canoas
- Letícia do Nascimento
- Hospital Universitário de Santa Maria
- Lucas Moyses Carvalho de Oliveira
- Hospital Universitário Ciências Médicas de Minas Gerais
- Luciane Kopittke
- Hospital Nossa Senhora da Conceição
- Luís César de Castro
- Hospital Bruno Born
- Manuela Furtado Sacioto
- Faculdade de Ciências Médicas de Minas Gerais
- Marcelo Carneiro
- Hospital Santa Cruz
- Marcos André Gonçalves
- Computer Science Department, Universidade Federal de Minas Gerais
- Maria Aparecida Camargos Bicalho
- Medical School and University Hospital, Universidade Federal de Minas Gerais
- Mônica Aparecida da Paula Sordi
- Botucatu Medical School, Universidade Estadual Paulista “Júlio de Mesquita Filho”
- Natália da Cunha Severino Sampaio
- Hospital Eduardo de Menezes
- Pedro Gibson Paraíso
- Orizonti Instituto de Saúde E Longevidade
- Rochele Mosmann Menezes
- Hospital Santa Cruz
- Silvia Ferreira Araújo
- Hospital Semper
- Vivian Costa Morais de Assis
- Faculdade de Ciências Médicas de Minas Gerais
- Katia de Paula Farah
- Medical School and University Hospital, Universidade Federal de Minas Gerais
- Milena Soriano Marcolino
- Medical School and University Hospital, Universidade Federal de Minas Gerais
- DOI
- https://doi.org/10.1186/s12882-023-03341-9
- Journal volume & issue
-
Vol. 24,
no. 1
pp. 1 – 12
Abstract
Abstract Background Acute kidney injury has been described as a common complication in patients hospitalized with COVID-19, which may lead to the need for kidney replacement therapy (KRT) in its most severe forms. Our group developed and validated the MMCD score in Brazilian COVID-19 patients to predict KRT, which showed excellent performance using data from 2020. This study aimed to validate the MMCD score in a large cohort of patients hospitalized with COVID-19 in a different pandemic phase and assess its performance to predict in-hospital mortality. Methods This study is part of the “Brazilian COVID-19 Registry”, a retrospective observational cohort of consecutive patients hospitalized for laboratory-confirmed COVID-19 in 25 Brazilian hospitals between March 2021 and August 2022. The primary outcome was KRT during hospitalization and the secondary was in-hospital mortality. We also searched literature for other prediction models for KRT, to assess the results in our database. Performance was assessed using area under the receiving operator characteristic curve (AUROC) and the Brier score. Results A total of 9422 patients were included, 53.8% were men, with a median age of 59 (IQR 48–70) years old. The incidence of KRT was 8.8% and in-hospital mortality was 18.1%. The MMCD score had excellent discrimination and overall performance to predict KRT (AUROC: 0.916 [95% CI 0.909–0.924]; Brier score = 0.057). Despite the excellent discrimination and overall performance (AUROC: 0.922 [95% CI 0.914–0.929]; Brier score = 0.100), the calibration was not satisfactory concerning in-hospital mortality. A random forest model was applied in the database, with inferior performance to predict KRT requirement (AUROC: 0.71 [95% CI 0.69–0.73]). Conclusion The MMCD score is not appropriate for in-hospital mortality but demonstrates an excellent predictive ability to predict KRT in COVID-19 patients. The instrument is low cost, objective, fast and accurate, and can contribute to supporting clinical decisions in the efficient allocation of assistance resources in patients with COVID-19.
Keywords