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

被引：5

作者：

Figueiredo, Flavio de Azevedo ^{[1
,2
]}

Ramos, Lucas Emanuel Ferreira ^{[3
]}

Silva, Rafael Tavares ^{[3
]}

Ponce, Daniela ^{[4
]}

de Carvalho, Rafael Lima Rodrigues ^{[5
]}

Schwarzbold, Alexandre Vargas ^{[6
]}

Maurilio, Amanda de Oliveira ^{[7
]}

Scotton, Ana Luiza Bahia Alves ^{[8
]}

Garbini, Andresa Fontoura ^{[9
]}

Farace, Barbara Lopes ^{[10
]}

Garcia, Barbara Machado ^{[11
]}

da Silva, Carla Thais Candida Alves ^{[12
]}

Cimini, Christiane Correa Rodrigues ^{[13
,14
]}

de Carvalho, Cintia Alcantara ^{[15
]}

Dias, Cristiane dos Santos ^{[16
]}

Silveira, Daniel Vitorio ^{[17
]}

Manenti, Euler Roberto Fernandes ^{[18
]}

Cenci, Evelin Paola de Almeida ^{[19
]}

Anschau, Fernando ^{[9
]}

Aranha, Fernando Graca ^{[20
]}

de Aguiar, Filipe Carrilho ^{[21
]}

Bartolazzi, Frederico ^{[12
]}

Vietta, Giovanna Grunewald ^{[20
]}

Nascimento, Guilherme Fagundes ^{[17
]}

Noal, Helena Carolina ^{[6
]}

Duani, Helena ^{[22
]}

Vianna, Heloisa Reniers ^{[23
]}

Guimaraes, Henrique Cerqueira ^{[10
]}

de Alvarenga, Joice Coutinho ^{[15
]}

Chatkin, Jose Miguel ^{[24
]}

de Morais, Julia Drumond Parreiras ^{[23
]}

Machado-Rugolo, Juliana ^{[4
]}

Ruschel, Karen Brasil ^{[5
,18
]}

Martins, Karina Paula Medeiros Prado ^{[5
,22
]}

Menezes, Luanna Silva Monteiro ^{[25
,26
]}

Couto, Luciana Siuves Ferreira ^{[27
]}

de Castro, Luis Cesar ^{[28
]}

Nasi, Luiz Antonio ^{[29
]}

Cabral, Maderson Alvares de Souza ^{[22
]}

Floriani, Maiara Anschau ^{[29
]}

Souza, Maira Dias ^{[26
]}

Souza-Silva, Maira Viana Rego ^{[1
]}

Carneiro, Marcelo ^{[30
]}

de Godoy, Mariana Frizzo ^{[24
]}

Bicalho, Maria Aparecida Camargos ^{[1
,11
]}

Lima, Maria Clara Pontello Barbosa ^{[27
]}

Aliberti, Marlon Juliano Romero ^{[31
,32
]}

Nogueira, Matheus Carvalho Alves ^{[33
]}

Martins, Matheus Fernandes Lopes ^{[34
]}

Guimaraes-Junior, Milton Henriques ^{[34
]}

机构：

[1] Univ Fed Minas Gerais, Med Sch, Dept Internal Med, Av Prof Alfredo Balena, BR-190 Belo Horizonte, MG, Brazil

[2] Univ Fed Lavras, Dept Med, R Tomas Antonio Gonzaga 277, Gonzaga, Lavras, Brazil

[3] Univ Fed Minas Gerais, Dept Stat, Av Presidente Antonio Carlos 6627, Belo Horizonte, MG, Brazil

[4] Univ Estadual Paulista, Botucatu Med Sch, Prof Mario Rubens Guimaraes Montenegro,S N, Botucatu, SP, Brazil

[5] CNPq, Inst Hlth Technol Assessment, IATS, R Ramiro Barcelos 2359, Porto Alegre, RS, Brazil

[6] Hosp Univ Univ Fed Santa Maria, Av Roraima 1000, Santa Maria, Roraima, Brazil

[7] Hosp Sao Joao Deus, R Cobre 800, Divinopolis, Brazil

[8] Hosp Reg Antonio Dias, R Maj Gote 1231, Patos De Minas, Brazil

[9] Hosp Nossa Senhora Conceicao, Hosp Cristo Redentor, Av Francisco Trein 326, Porto Alegre, Brazil

[10] Hosp Risoleta Tolentino Neves, R Gabirobas 01, Belo Horizonte, MG, Brazil

[11] Hosp Julia Kubitschek, R Dr Cristiano Rezende 2745, Belo Horizonte, MG, Brazil

[12] Hosp Santo Antonio, Praca DRr Marcio Carvalho Lopes Filho 501, Curvelo, Brazil

[13] Hosp Santa Rosalia, R Cruzeiro 01, Teofilo Otoni, Brazil

[14] Univ Fed Vales Jequitinhonha Mucuri, Mucuri Med Sch, R Cruzeiro 01, Teofilo Otoni, Brazil

[15] Hosp Joao XXIII, Av Prof Alfredo Balena 400, Belo Horizonte, MG, Brazil

[16] Univ Fed Minas Gerais, Med Sch, Dept Pediat, Av Prof Alfredo Balena, BR-190 Belo Horizonte, MG, Brazil

[17] Hosp UNIMED BH, Av Contorno, BR-3097 Belo Horizonte, MG, Brazil

[18] Hosp Mae Deus, R Jose Alencar, BR-286 Porto Alegre, RS, Brazil

[19] Hosp Univ Canoas, Av Farroupilha, BR-8001 Canoas, Brazil

[20] Hosp SOS Cardio, Rodovia,SC-401, BR-121 Florianopolis, SC, Brazil

[21] Hosp Clin Univ Fed Pernambuco, Av Prof Moraes Rego, BR-1235 Recife, PE, Brazil

[22] Univ Fed Minas Gerais, Univ Hosp, Med Sch, Ave Prof Alfredo Balena, BR-190 Belo Horizonte, MG, Brazil

[23] Hosp Univ Ciencias Med, R Dos Aimores, BR-2896 Belo Horizonte, MG, Brazil

[24] Hosp Sao Lucas PUCRS, Av Ipiranga, BR-6690 Porto Alegre, Brazil

[25] Hosp Luxemburgo, R Gentios, BR-1350 Belo Horizonte, MG, Brazil

[26] Hosp Metropolitano Odilon Behrens, R Formiga, BR-50 Belo Horizonte, MG, Brazil

[27] Univ Fed Ouro Preto, Med Sch, R Diogo Vasconcelos, BR-122 Ouro Preto, Brazil

[28] Hosp Bruno Born, Av Benjamin Constant, BR-881 Lajeado, Brazil

[29] Hosp Moinhos Vento, R Ramiro Barcelos, BR-910 Porto Alegre, Brazil

[30] Hosp Santa Cruz, R Fernando Abott, BR-174 Santa Cruz Do Sul, Brazil

[31] Univ Sao Paulo, Lab Invest Med Envelhecimento LIM 66, Serv Geriatria, Hosp Clin HCFMUSP,Fac Med, Sao Paulo, Brazil

[32] Hosp Sirio Libanes, Res Inst, Sao Paulo, SP, Brazil

[33] Hosp Rede Mater, Av Contorno, BR-9000 Belo Horizonte, MG, Brazil

[34] Hosp Marcio Cunha, Av Kiyoshi Tsunawaki, BR-48 Ipatinga, Brazil

[35] Hosp Eduardo Menezes, R Dr Cristiano Rezende, BR-2213 Belo Horizonte, Brazil

[36] Hosp Tacchini, Jose Mario Monaco, BR-358 Bento Goncalves, Brazil

[37] Hosp Semper, Alameda Ezequiel Dias, BR-389 Belo Horizonte, Brazil

[38] Hosp Metropolitano Doutor Celio Castro, R Dona Luiza, BR-311 Belo Horizonte, MG, Brazil

[39] Univ Fed Sao Joao, R Sebastiao Goncalves Coelho, BR-400 Divinopolis, Brazil

[40] Hosp Israelita Albert Einstein, Fac Israelita Ciencias Saude Albert Einstei, Sao Paulo, Brazil

[41] Univ Fed Minas Gerais, Univ Hosp, Telehlth Ctr, Av Prof Alfredo Balena, BR-110 Belo Horizonte, Brazil

来源：

BMC MEDICINE | 2022年 / 20卷 / 01期

关键词：

Acute kidney injury; COVID-19; Kidney replacement therapy; Score; Risk factors; Risk prediction; INJURY; RISK; MORTALITY; SEVERITY; DISEASE; AKI;

D O I：

10.1186/s12916-022-02503-0

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

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.

引用

页数：13

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