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Development and validation of a simple web-based tool for early prediction of COVID-19-associated death in kidney transplant recipients

American Journal of Transplantation, ISSN: 1600-6135, Vol: 22, Issue: 2, Page: 610-625
2022
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Assessing antiviral treatment efficacy and risk factors for severe COVID-19 in kidney transplant recipients during the Omicron subvariant-dominant period: a retrospective study

Abstract Background Kidney transplant recipients (KTRs) are at risk of severe coronavirus disease 2019 (COVID-19), and even now that Omicron subvariants have become dominant, cases

Article Description

This analysis, using data from the Brazilian kidney transplant (KT) COVID-19 study, seeks to develop a prediction score to assist in COVID-19 risk stratification in KT recipients. In this study, 1379 patients (35 sites) were enrolled, and a machine learning approach was used to fit models in a derivation cohort. A reduced Elastic Net model was selected, and the accuracy to predict the 28-day fatality after the COVID-19 diagnosis, assessed by the area under the ROC curve (AUC-ROC), was confirmed in a validation cohort. The better calibration values were used to build the applicable ImAgeS score. The 28-day fatality rate was 17% ( n = 235), which was associated with increasing age, hypertension and cardiovascular disease, higher body mass index, dyspnea, and use of mycophenolate acid or azathioprine. Higher kidney graft function, longer time of symptoms until COVID-19 diagnosis, presence of anosmia or coryza, and use of mTOR inhibitor were associated with reduced risk of death. The coefficients of the best model were used to build the predictive score, which achieved an AUC-ROC of 0.767 (95% CI 0.698–0.834) in the validation cohort. In conclusion, the easily applicable predictive model could assist health care practitioners in identifying non-hospitalized kidney transplant patients that may require more intensive monitoring. Trial registration: ClinicalTrials.gov NCT04494776.

Bibliographic Details

Luis Gustavo Modelli de Andrade; Tainá Veras de Sandes-Freitas; Aline Lima Cunha Alcântara; Ronaldo de Matos Esmeraldo; Lúcio R. Requião-Moura; Helio Tedesco-Silva; José Medina-Pestana; Laila Almeida Viana; Marina Pontello Cristelli; Alvaro Pacheco-Silva; Valter Duro Garcia; Mario Abbud Filho; Erika Cristina Ribeiro de Lima Carneiro; Roberto Ceratti Manfro; Kellen Micheline Alves Henrique Costa; Denise Rodrigues Simão; Marcos Vinicius de Sousa; Viviane Brandão Bandeira de Mello Santana; Irene L. Noronha; Elen Almeida Romão; Juliana Aparecida Zanocco; Gustavo Guilherme Queiroz Arimatea; Deise De Boni Monteiro de Carvalho; Elizete Keitel; Claudia Maria Costa de Oliveira; Beatriz de Oliveira Neri; Ida Maria Maximina Fernandes Charpiot; Teresa Cristina Alves Ferreira; Alessandra Rosa Vicari; Tomás Pereira; Maria Eduarda Heinzen de Almeida Coelho; Marilda Mazzali; Gustavo Fernandes Ferreira; Juliana Bastos Campos; Nicole Gomes Campos Rocha; Anita Leme da Rocha Saldanha; Tania Leme da Rocha Martinez; João Egídio Romão; Maria Regina Teixeira Araújo; Sibele Lessa Braga; Luciane Mônica Deboni; Franco Silveira da Mota Krüger; Miguel Moysés Neto; Auro Buffani Claudino; Lívia Cláudio de Oliveira; Tereza Azevedo Matuck; Alexandre Tortoza Bignelli; Silvia Regina Hokazono; José Hermógenes Rocco Suassuna; Suzimar da Silveira Rioja; Rafael Lage Madeira; Sandra Simone Vilaça; Carlos Alberto Chalabi Calazans; Daniel Costa Chalabi Calazans; Patrícia Malafronte; Antonio Miorin; Filipe Carrilho de Aguiar; Larissa Guedes da Fonte Andrade; Fabiana Loss de Carvalho; Karoline Sesiuk Martins; Hélady Sanders Pinheiro; Emiliana Spadarotto Sertório; André Barreto Pereira; David José Barros Machado; Carolina Maria Pozzi; Leonardo Viliano Kroth; Lauro Monteiro Vasconcellos Filho; Rafael Fabio Maciel; Amanda Maíra Damasceno Silva; Ana Paula Maia Baptista; Pedro Augusto Macedo de Souza; Marcus Faria Lasmar; Luciana Tanajura Santamaria Saber; Lilian Monteiro Pereira Palma; Ricardo Augusto Monteiro de Barros Almeida

Elsevier BV

Medicine

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