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Your search keyword '"Guimarães, HC"' showing total 2 results
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2 results on '"Guimarães, HC"'

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

Author

de Azevedo Figueiredo F, Ramos LEF, Silva RT, Ponce D, de Carvalho RLR, Schwarzbold AV, de Oliveira Maurílio A, Scotton ALBA, Garbini AF, Farace BL, Garcia BM, da Silva CTCA, Cimini CCR, de Carvalho CA, Dos Santos Dias C, Silveira DV, Manenti ERF, de Almeida Cenci EP, Anschau F, Aranha FG, de Aguiar FC, Bartolazzi F, Vietta GG, Nascimento GF, Noal HC, Duani H, Vianna HR, Guimarães HC, de Alvarenga JC, Chatkin JM, de Morais JDP, Machado-Rugolo J, Ruschel KB, Martins KPMP, Menezes LSM, Couto LSF, de Castro LC, Nasi LA, de Souza Cabral MA, Floriani MA, Souza MD, Souza-Silva MVR, Carneiro M, de Godoy MF, Bicalho MAC, Lima MCPB, Aliberti MJR, Nogueira MCA, Martins MFL, Guimarães-Júnior MH, da Cunha Severino Sampaio N, de Oliveira NR, Ziegelmann PK, Andrade PGS, Assaf PL, de Lima Martelli PJ, Delfino-Pereira P, Castro Martins R, Menezes RM, Francisco SC, Araújo SF, Oliveira TF, de Oliveira TC, Souza Sales TL, Avelino-Silva TJ, Ramires YC, Pires MC, and Marcolino MS

Published
2023
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2. Development and validation of the MMCD score to predict kidney replacement therapy in COVID-19 patients.

Author

Figueiredo FA, Ramos LEF, Silva RT, Ponce D, de Carvalho RLR, Schwarzbold AV, Maurílio AO, Scotton ALBA, Garbini AF, Farace BL, Garcia BM, da Silva CTCA, Cimini CCR, de Carvalho CA, Dias CDS, Silveira DV, Manenti ERF, Cenci EPA, Anschau F, Aranha FG, de Aguiar FC, Bartolazzi F, Vietta GG, Nascimento GF, Noal HC, Duani H, Vianna HR, Guimarães HC, de Alvarenga JC, Chatkin JM, de Morais JDP, Machado-Rugolo J, Ruschel KB, Martins KPMP, Menezes LSM, Couto LSF, de Castro LC, Nasi LA, Cabral MAS, Floriani MA, Souza MD, Souza-Silva MVR, Carneiro M, de Godoy MF, Bicalho MAC, Lima MCPB, Aliberti MJR, Nogueira MCA, Martins MFL, Guimarães-Júnior MH, Sampaio NDCS, de Oliveira NR, Ziegelmann PK, Andrade PGS, Assaf PL, Martelli PJL, Delfino-Pereira P, Martins RC, Menezes RM, Francisco SC, Araújo SF, Oliveira TF, de Oliveira TC, Sales TLS, Avelino-Silva TJ, Ramires YC, Pires MC, and Marcolino MS

Subjects
Adult, Aged, Dextrans, Female, Humans, Male, Middle Aged, Mitomycin, ROC Curve, Renal Replacement Therapy adverse effects, Retrospective Studies, Risk Factors, Acute Kidney Injury diagnosis, Acute Kidney Injury epidemiology, Acute Kidney Injury therapy, COVID-19 therapy
Abstract

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., (© 2022. The Author(s).)

Published
2022
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