A New Natural Language Processing–Inspired Methodology (Detection, Initial Characterization, and Semantic Characterization) to Investigate Temporal Shifts (Drifts) in Health Care Data: Quantitative Study

Autor: Bruno Paiva, Marcos André Gonçalves, Leonardo Chaves Dutra da Rocha, Milena Soriano Marcolino, Fernanda Cristina Barbosa Lana, Maira Viana Rego Souza-Silva, Jussara M Almeida, Polianna Delfino Pereira, Claudio Moisés Valiense de Andrade, Angélica Gomides dos Reis Gomes, Maria Angélica Pires Ferreira, Frederico Bartolazzi, Manuela Furtado Sacioto, Ana Paula Boscato, Milton Henriques Guimarães-Júnior, Priscilla Pereira dos Reis, Felício Roberto Costa, Alzira de Oliveira Jorge, Laryssa Reis Coelho, Marcelo Carneiro, Thaís Lorenna Souza Sales, Silvia Ferreira Araújo, Daniel Vitório Silveira, Karen Brasil Ruschel, Fernanda Caldeira Veloso Santos, Evelin Paola de Almeida Cenci, Luanna Silva Monteiro Menezes, Fernando Anschau, Maria Aparecida Camargos Bicalho, Euler Roberto Fernandes Manenti, Renan Goulart Finger, Daniela Ponce, Filipe Carrilho de Aguiar, Luiza Margoto Marques, Luís César de Castro, Giovanna Grünewald Vietta, Mariana Frizzo de Godoy, Mariana do Nascimento Vilaça, Vivian Costa Morais

Publikováno v: JMIR Medical Informatics, Vol 12, p e54246 (2024)

BackgroundProper analysis and interpretation of health care data can significantly improve patient outcomes by enhancing services and revealing the impacts of new technologies and treatments. Understanding the substantial impact of temporal shifts in

Externí odkaz: https://doaj.org/article/b2c0e6bc40374f349b91cb8a5eb66433

Clinical characteristics and outcomes of COVID-19 patients with preexisting dementia: a large multicenter propensity-matched Brazilian cohort study

Autor: Maria Aparecida Camargos Bicalho, Márlon Juliano Romero Aliberti, Polianna Delfino-Pereira, Victor Schulthais Chagas, Patryk Marques da Silva Rosa, Magda Carvalho Pires, Lucas Emanuel Ferreira Ramos, Adriana Falangola Benjamin Bezerra, Ana Beatriz de Castro Feres, Angélica Gomides dos Reis Gomes, Angelinda Rezende Bhering, Bruno Porto Pessoa, Carla Thais Cândida Alves da Silva, Christiane Corrêa Rodrigues Cimini, Claudia Kimie Suemoto, Cristiana Andrade Coelho Dias, Daniela dos Reis Carazai, Daniela Ponce, Danyelle Romana Alves Rios, Euler Manenti, Fernando Anschau, Joanna d‘Arc Lyra Batista, Joice Coutinho de Alvarenga, Julia Avancini Viguini, Julia Mariot Zanellato, Juliana Machado Rugolo, Karen Brasil Ruschel, Leticia do Nascimento, Luanna Silva Monteiro Menezes, Lucas Moyses Carvalho de Oliveira, Luís César de Castro, Luiz Antônio Nasi, Marcelo Carneiro, Maria Angélica Pires Ferreira, Mariana Frizzo de Godoy, Milton Henriques Guimarães-Júnior, Neimy Ramos de Oliveira, Patricia Klarmann Ziegelmann, Paula Fonseca Porto, Paulo Mascarenhas Mendes, Pedro Gibson Paraíso, Priscilla Pereira dos Reis, Saionara Cristina Francisco, Silvia Ferreira Araújo, Thiago Junqueira Avelino-Silva, Milena Soriano Marcolino

Publikováno v: BMC Geriatrics, Vol 24, Iss 1, Pp 1-11 (2024)

Abstract Background Although dementia has emerged as an important risk factor for severe SARS-CoV-2 infection, results on COVID-19-related complications and mortality are not consistent. We examined the clinical presentations and outcomes of COVID-19

Externí odkaz: https://doaj.org/article/5a0424ccd2074da5a64c4197c022b8d1

Corrigendum: Assessment of risk scores to predict mortality of COVID-19 patients admitted to the intensive care unit

Autor: Matheus Carvalho Alves Nogueira, Vandack Nobre, Magda Carvalho Pires, Lucas Emanuel Ferreira Ramos, Yara Cristina Neves Marques Barbosa Ribeiro, Rubia Laura Oliveira Aguiar, Flavia Maria Borges Vigil, Virginia Mara Reis Gomes, Camila de Oliveira Santos, Davi Mesquita Miranda, Pamela Andrea Alves Durães, Josiane Moreira da Costa, Alexandre Vargas Schwarzbold, Angélica Gomides dos Reis Gomes, Bruno Porto Pessoa, Carolina Cunha Matos, Christiane Corrêa Rodrigues Cimini, Cíntia Alcântara de Carvalho, Daniela Ponce, Euler Roberto Fernandes Manenti, Evelin Paola de Almeida Cenci, Fernando Anschau, Flávia Carvalho Cardoso Costa, Francine Janaina Magalhães Nascimento, Frederico Bartolazzi, Genna Maira Santos Grizende, Heloisa Reniers Vianna, Jomar Cristeli Nepomuceno, Karen Brasil Ruschel, Liege Barella Zandoná, Luís César de Castro, Maíra Dias Souza, Marcelo Carneiro, Maria Aparecida Camargos Bicalho, Mariana do Nascimento Vilaça, Naiara Patrícia Fagundes Bonardi, Neimy Ramos de Oliveira, Raquel Lutkmeier, Saionara Cristina Francisco, Silvia Ferreira Araújo, Polianna Delfino-Pereira, Milena Soriano Marcolino

Publikováno v: Frontiers in Medicine, Vol 11 (2024)

Externí odkaz: https://doaj.org/article/0cf8596c6a8f4060b60f93c21ae72995

Potential and limitations of machine meta-learning (ensemble) methods for predicting COVID-19 mortality in a large inhospital Brazilian dataset

Autor: Bruno Barbosa Miranda de Paiva, Polianna Delfino Pereira, Claudio Moisés Valiense de Andrade, Virginia Mara Reis Gomes, Maira Viana Rego Souza-Silva, Karina Paula Medeiros Prado Martins, Thaís Lorenna Souza Sales, Rafael Lima Rodrigues de Carvalho, Magda Carvalho Pires, Lucas Emanuel Ferreira Ramos, Rafael Tavares Silva, Alessandra de Freitas Martins Vieira, Aline Gabrielle Sousa Nunes, Alzira de Oliveira Jorge, Amanda de Oliveira Maurílio, Ana Luiza Bahia Alves Scotton, Carla Thais Candida Alves da Silva, Christiane Corrêa Rodrigues Cimini, Daniela Ponce, Elayne Crestani Pereira, Euler Roberto Fernandes Manenti, Fernanda d’Athayde Rodrigues, Fernando Anschau, Fernando Antônio Botoni, Frederico Bartolazzi, Genna Maira Santos Grizende, Helena Carolina Noal, Helena Duani, Isabela Moraes Gomes, Jamille Hemétrio Salles Martins Costa, Júlia di Sabatino Santos Guimarães, Julia Teixeira Tupinambás, Juliana Machado Rugolo, Joanna d’Arc Lyra Batista, Joice Coutinho de Alvarenga, José Miguel Chatkin, Karen Brasil Ruschel, Liege Barella Zandoná, Lílian Santos Pinheiro, Luanna Silva Monteiro Menezes, Lucas Moyses Carvalho de Oliveira, Luciane Kopittke, Luisa Argolo Assis, Luiza Margoto Marques, Magda Cesar Raposo, Maiara Anschau Floriani, Maria Aparecida Camargos Bicalho, Matheus Carvalho Alves Nogueira, Neimy Ramos de Oliveira, Patricia Klarmann Ziegelmann, Pedro Gibson Paraiso, Petrônio José de Lima Martelli, Roberta Senger, Rochele Mosmann Menezes, Saionara Cristina Francisco, Silvia Ferreira Araújo, Tatiana Kurtz, Tatiani Oliveira Fereguetti, Thainara Conceição de Oliveira, Yara Cristina Neves Marques Barbosa Ribeiro, Yuri Carlotto Ramires, Maria Clara Pontello Barbosa Lima, Marcelo Carneiro, Adriana Falangola Benjamin Bezerra, Alexandre Vargas Schwarzbold, André Soares de Moura Costa, Barbara Lopes Farace, Daniel Vitorio Silveira, Evelin Paola de Almeida Cenci, Fernanda Barbosa Lucas, Fernando Graça Aranha, Gisele Alsina Nader Bastos, Giovanna Grunewald Vietta, Guilherme Fagundes Nascimento, Heloisa Reniers Vianna, Henrique Cerqueira Guimarães, Julia Drumond Parreiras de Morais, Leila Beltrami Moreira, Leonardo Seixas de Oliveira, Lucas de Deus Sousa, Luciano de Souza Viana, Máderson Alvares de Souza Cabral, Maria Angélica Pires Ferreira, Mariana Frizzo de Godoy, Meire Pereira de Figueiredo, Milton Henriques Guimarães-Junior, Mônica Aparecida de Paula de Sordi, Natália da Cunha Severino Sampaio, Pedro Ledic Assaf, Raquel Lutkmeier, Reginaldo Aparecido Valacio, Renan Goulart Finger, Rufino de Freitas, Silvana Mangeon Meirelles Guimarães, Talita Fischer Oliveira, Thulio Henrique Oliveira Diniz, Marcos André Gonçalves, Milena Soriano Marcolino

Publikováno v: Scientific Reports, Vol 13, Iss 1, Pp 1-18 (2023)

Abstract The majority of early prediction scores and methods to predict COVID-19 mortality are bound by methodological flaws and technological limitations (e.g., the use of a single prediction model). Our aim is to provide a thorough comparative stud

Externí odkaz: https://doaj.org/article/1e9a5a30d36940cab636f04ceac67f26

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

Autor: Flávio de Azevedo Figueiredo, Lucas Emanuel Ferreira Ramos, Rafael Tavares Silva, Daniela Ponce, Rafael Lima Rodrigues de Carvalho, Alexandre Vargas Schwarzbold, Amanda de Oliveira Maurílio, Ana Luiza Bahia Alves Scotton, Andresa Fontoura Garbini, Bárbara Lopes Farace, Bárbara Machado Garcia, Carla Thais Cândida Alves da Silva, Christiane Corrêa Rodrigues Cimini, Cíntia Alcantara de Carvalho, Cristiane dos Santos Dias, Daniel Vitório Silveira, Euler Roberto Fernandes Manenti, Evelin Paola de Almeida Cenci, Fernando Anschau, Fernando Graça Aranha, Filipe Carrilho de Aguiar, Frederico Bartolazzi, Giovanna Grunewald Vietta, Guilherme Fagundes Nascimento, Helena Carolina Noal, Helena Duani, Heloisa Reniers Vianna, Henrique Cerqueira Guimarães, Joice Coutinho de Alvarenga, José Miguel Chatkin, Júlia Drumond Parreiras de Morais, Juliana Machado-Rugolo, Karen Brasil Ruschel, Karina Paula Medeiros Prado Martins, Luanna Silva Monteiro Menezes, Luciana Siuves Ferreira Couto, Luís César de Castro, Luiz Antônio Nasi, Máderson Alvares de Souza Cabral, Maiara Anschau Floriani, Maíra Dias Souza, Maira Viana Rego Souza-Silva, Marcelo Carneiro, Mariana Frizzo de Godoy, Maria Aparecida Camargos Bicalho, Maria Clara Pontello Barbosa Lima, Márlon Juliano Romero Aliberti, Matheus Carvalho Alves Nogueira, Matheus Fernandes Lopes Martins, Milton Henriques Guimarães-Júnior, Natália da Cunha Severino Sampaio, Neimy Ramos de Oliveira, Patricia Klarmann Ziegelmann, Pedro Guido Soares Andrade, Pedro Ledic Assaf, Petrônio José de Lima Martelli, Polianna Delfino-Pereira, Raphael Castro Martins, Rochele Mosmann Menezes, Saionara Cristina Francisco, Silvia Ferreira Araújo, Talita Fischer Oliveira, Thainara Conceição de Oliveira, Thaís Lorenna Souza Sales, Thiago Junqueira Avelino-Silva, Yuri Carlotto Ramires, Magda Carvalho Pires, Milena Soriano Marcolino

Publikováno v: BMC Medicine, Vol 20, Iss 1, Pp 1-13 (2022)

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

Externí odkaz: https://doaj.org/article/f0e4836c3df3467e884b96b861f1c259