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

对 MMCD 评分预测 COVID-19 患者肾脏替代治疗和住院死亡率的时间验证

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作者: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 Ci

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.

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.

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

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]).

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