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Artificial intelligence to predict the need for mechanical ventilation in cases of severe COVID-19 COVID19 COVID 19 COVID-1 COVID1 1 COVID-
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Godoy, Mariana Frizzo de
; Chatkin, José Miguel
; Rodrigues, Rosana Souza
; Forte, Gabriele Carra
; Marchiori, Edson
; Gavenski, Nathan
; Barros, Rodrigo Coelho
; Hochhegger, Bruno
.
Resumo Objetivo: Determinar a acurácia da tomografia computadorizada (TC), avaliada por redes neurais profundas, na ventilação mecânica, de pacientes hospitalizados por síndrome respiratória aguda grave por COVID-19. Materiais e Métodos: Trata-se de estudo de coorte retrospectivo, realizado em dois hospitais brasileiros. Foram incluídas TCs de pacientes hospitalizados por síndrome respiratória aguda grave e COVID-19 confirmada por RT-PCR. O treinamento consistiu em TC de tórax de 823 pacientes com COVID-19, dos quais 93 foram submetidos a ventilação mecânica na hospitalização. Nós desenvolvemos um modelo de inteligência artificial baseado em redes de convoluções neurais. A avaliação do desempenho do uso da inteligência artificial foi baseada no cálculo de acurácia, sensibilidade, especificidade e área sob a curva ROC. Resultados: A sensibilidade do modelo foi de 0,417 e a especificidade foi de 0,860. A área sob a curva ROC para o conjunto de teste foi de 0,68. Conclusão: Criamos um modelo de aprendizado de máquina com elevada especificidade, capaz de prever de forma confiável pacientes que não precisarão de ventilação mecânica. Isso significa que essa abordagem é ideal para prever com antecedência pacientes de alto risco e um número mínimo de equipamentos de ventilação e de leitos críticos. Objetivo TC, , (TC) profundas COVID19. COVID19 COVID 19. 19 Métodos Tratase Trata se retrospectivo brasileiros COVID-1 RTPCR. RTPCR RT PCR. PCR RT-PCR 82 COVID19, 19, 9 hospitalização Resultados 0417 0 417 0,41 0860 860 0,860 068 68 0,68 Conclusão críticos (TC COVID1 1 COVID- 8 041 41 0,4 086 86 0,86 06 6 0,6 04 4 0, 08 0,8
Abstract Objective: To determinate the accuracy of computed tomography (CT) imaging assessed by deep neural networks for predicting the need for mechanical ventilation (MV) in patients hospitalized with severe acute respiratory syndrome due to coronavirus disease 2019 (COVID-19). Materials and Methods: This was a retrospective cohort study carried out at two hospitals in Brazil. We included CT scans from patients who were hospitalized due to severe acute respiratory syndrome and had COVID-19 confirmed by reverse transcriptionpolymerase chain reaction (RT-PCR). The training set consisted of chest CT examinations from 823 patients with COVID-19, of whom 93 required MV during hospitalization. We developed an artificial intelligence (AI) model based on convolutional neural networks. The performance of the AI model was evaluated by calculating its accuracy, sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve. Results: For predicting the need for MV, the AI model had a sensitivity of 0.417 and a specificity of 0.860. The corresponding area under the ROC curve for the test set was 0.68. Conclusion: The high specificity of our AI model makes it able to reliably predict which patients will and will not need invasive ventilation. That makes this approach ideal for identifying high-risk patients and predicting the minimum number of ventilators and critical care beds that will be required. Objective (CT (MV 201 COVID19. COVID19 COVID 19 . (COVID-19) Methods Brazil COVID-1 RTPCR. RTPCR RT PCR (RT-PCR) 82 COVID19, 19, 9 hospitalization (AI (ROC Results 0417 0 417 0.41 0860 860 0.860 068 68 0.68 Conclusion highrisk risk 20 COVID1 1 (COVID-19 COVID- (RT-PCR 8 041 41 0.4 086 86 0.86 06 6 0.6 2 (COVID-1 04 4 0. 08 0.8 (COVID- (COVID
2.
Lesão Miocárdica e Prognóstico em Pacientes Hospitalizados com COVID-19 no Brasil: Resultados do Registro Nacional de COVID-19 COVID19 COVID 19 COVID-1 Brasil COVID1 1 COVID-
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Barbosa, Hannah Cardoso
; Martins, Maria Auxiliadora Parreiras
; Jesus, Jordana Cristina de
; Meira, Karina Cardoso
; Passaglia, Luiz Guilherme
; Sacioto, Manuela Furtado
; Bezerra, Adriana Falangola Benjamin
; Schwarzbold, Alexandre Vargas
; Maurílio, Amanda de Oliveira
; Farace, Barbara Lopes
; Silva, Carla Thais Cândida Alves da
; Cimini, Christiane Corrêa Rodrigues
; Silveira, Daniel Vitorio
; Carazai, Daniela do Reis
; Ponce, Daniela
; Costa, Emanuel Victor Alves
; Manenti, Euler Roberto Fernandes
; Cenci, Evelin Paola de Almeida
; Bartolazzi, Frederico
; Madeira, Glícia Cristina de Castro
; Nascimento, Guilherme Fagundes
; Velloso, Isabela Vasconcellos Pires
; Batista, Joanna d’Arc Lyra
; Morais, Júlia Drumond Parreiras de
; Carvalho, Juliana da Silva Nogueira
; Ruschel, Karen Brasil
; Martins, Karina Paula Medeiros Prado
; Zandoná, Liege Barella
; Menezes, Luanna Silva Monteiro
; Kopittke, Luciane
; Castro, Luís César de
; Nasi, Luiz Antônio
; Floriani, Maiara Anschau
; Souza, Maíra Dias
; Carneiro, Marcelo
; Bicalho, Maria Aparecida Camargos
; Lima, Maria Clara Pontello Barbosa
; Godoy, Mariana Frizzo de
; Guimarães-Júnior, Milton Henriques
; Mendes, Paulo Mascarenhas
; Delfino-Pereira, Polianna
; Ribeiro, Raquel Jaqueline Eder
; Finger, Renan Goulart
; Menezes, Rochele Mosmann
; Francisco, Saionara Cristina
; Araújo, Silvia Ferreira
; Oliveira, Talita Fischer
; Oliveira, Thainara Conceição de
; Polanczyk, Carisi Anne
; Marcolino, Milena Soriano
.
Resumo Fundamento As complicações cardiovasculares da COVID-19 são aspectos importantes da patogênese e do prognóstico da doença. Evidências do papel prognóstico da troponina e da lesão miocárdica em pacientes hospitalizados com COVID-19 na América Latina são ainda escassos. Objetivos Avaliar a lesão miocárdica como preditor independente de mortalidade hospitalar e suporte ventilatório mecânico em pacientes hospitalizados, do registro brasileiro de COVID-19. Métodos Este estudo coorte é um subestudo do registro brasileiro de COVID-19, conduzido em 31 hospitais brasileiros de 17 cidades, de março a setembro de 2020. Os desfechos primários incluíram mortalidade hospitalar e suporte ventilatório mecânico invasivo. Os modelos para os desfechos primários foram estimados por regressão de Poisson com variância robusta, com significância estatística de p<0,05. Resultados Dos 2925 pacientes [idade mediana de 60 anos (48-71), 57,1%], 27,3% apresentaram lesão miocárdica. A proporção de pacientes com comorbidades foi maior nos pacientes com lesão miocárdica [mediana 2 (1-2) vs. 1 (0-20)]. Os pacientes com lesão miocárdica apresentaram maiores valores medianos de peptídeo natriurético cerebral, lactato desidrogenase, creatina fosfoquinase, N-terminal do pró-peptídeo natriurético tipo B e proteína C reativa em comparação a pacientes sem lesão miocárdica. Como fatores independentes, proteína C reativa e contagem de plaquetas foram relacionados com o risco de morte, e neutrófilos e contagem de plaquetas foram relacionados ao risco de suporte ventilatório mecânico invasivo. Os pacientes com níveis elevados de troponina apresentaram um maior risco de morte (RR 2,03, IC95% 1,60-2,58) e suporte ventilatório mecânico (RR 1,87;IC95% 1,57-2,23), em comparação àqueles com níveis de troponina normais. Conclusão Lesão cardíaca foi um preditor independente de mortalidade hospitalar e necessidade de suporte ventilatório mecânico em pacientes hospitalizados com COVID-19. COVID19 COVID 19 COVID-1 doença escassos COVID19. 19. COVID19, 19, 3 cidades 2020 invasivo robusta p005 p 0 05 p<0,05 292 idade 6 4871, 4871 48 71 , (48-71) 57,1%, 571 57,1% 57 57,1%] 273 27 27,3 12 (1-2 vs 020. 020 20 . (0-20)] cerebral desidrogenase fosfoquinase Nterminal N terminal própeptídeo pró independentes RR 203 03 2,03 IC95 IC 1,602,58 160258 1,60 2,58 58 1,60-2,58 1,87IC95% 187IC95 1,87 87 1,87;IC95 1,572,23, 157223 1,57 2,23 23 1,57-2,23) normais COVID1 COVID- 202 p00 p<0,0 29 487 4 7 (48-71 57,1 5 27, (1- 02 (0-20) 2,0 IC9 602 1,602,5 16025 160 1,6 258 2,5 1,60-2,5 87IC95 1,87IC95 187IC9 187 1,8 8 1,87;IC9 572 1,572,23 15722 157 1,5 223 2,2 1,57-2,23 p0 p<0, (48-7 57, (1 (0-20 2, 1,602, 1602 16 1, 25 1,60-2, 87IC9 1,87IC9 187IC 18 1,87;IC 1,572,2 1572 15 22 1,57-2,2 p<0 (48- ( (0-2 1,602 1,60-2 87IC 1,87IC 1,572, 1,57-2, p< (48 (0- 1,60- 1,572 1,57-2 (4 (0 1,57-
Abstract Background Cardiovascular complications of COVID-19 are important aspects of the disease’s pathogenesis and prognosis. Evidence on the prognostic role of troponin and myocardial injury in Latin American hospitalized COVID-19 patients is still scarce. Objectives To evaluate myocardial injury as independent predictor of in-hospital mortality and invasive mechanical ventilation support in hospitalized patients, from the Brazilian COVID-19 Registry. Methods This cohort study is a substudy of the Brazilian COVID-19 Registry, conducted in 31 Brazilian hospitals of 17 cities, March-September 2020. Primary outcomes included in-hospital mortality and invasive mechanical ventilation support. Models for the primary outcomes were estimated by Poisson regression with robust variance, with statistical significance of p<0.05. Results Of 2,925 patients (median age of 60 years [48-71], 57.1% men), 27.3% presented myocardial injury. The proportion of patients with comorbidities was higher among patients with cardiac injury (median 2 [1-2] vs. 1 [0-2]). Patients with myocardial injury had higher median levels of brain natriuretic peptide, lactate dehydrogenase, creatine phosphokinase, N-terminal pro-brain natriuretic peptide, and C-reactive protein than patients without myocardial injury. As independent predictors, C-reactive protein and platelet counts were related to the risk of death, and neutrophils and platelet counts were related to the risk of invasive mechanical ventilation support. Patients with high troponin levels presented a higher risk of death (RR 2.03, 95% CI 1.60-2.58) and invasive mechanical ventilation support (RR 1.87, 95% CI 1.57-2.23), when compared to those with normal troponin levels. Conclusion Cardiac injury was an independent predictor of in-hospital mortality and the need for invasive mechanical ventilation support in hospitalized COVID-19 patients. COVID19 COVID 19 COVID-1 diseases disease s prognosis scarce inhospital hospital Registry 3 cities MarchSeptember March September 2020 variance p005 p 0 05 p<0.05 2925 925 2,92 6 4871, 4871 48 71 , [48-71] 571 57 57.1 men, men men) 273 27 27.3 12 [1-2 vs 02. 02 . [0-2]) peptide dehydrogenase phosphokinase Nterminal N terminal probrain pro Creactive C reactive predictors RR 203 03 2.03 95 1.602.58 160258 1.60 2.58 58 1.60-2.58 187 87 1.87 1.572.23, 157223 1.57 2.23 23 1.57-2.23) COVID1 COVID- 202 p00 p<0.0 292 92 2,9 487 4 7 [48-71 5 57. 27. [1- [0-2] 20 2.0 9 602 1.602.5 16025 160 1.6 258 2.5 1.60-2.5 18 8 1.8 572 1.572.23 15722 157 1.5 223 2.2 1.57-2.23 p0 p<0. 29 2, [48-7 [1 [0-2 2. 1.602. 1602 16 1. 25 1.60-2. 1.572.2 1572 15 22 1.57-2.2 p<0 [48- [ [0- 1.602 1.60-2 1.572. 1.57-2. p< [48 [0 1.60- 1.572 1.57-2 [4 1.57-
3.
COVID-19 outcomes in people living with HIV: Peering through the waves COVID19 COVID 19 COVID-1 HIV COVID1 1 COVID-
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Sales, Thaís Lorenna Souza
; Souza-Silva, Maíra Viana Rego
; Delfino-Pereira, Polianna
; Neves, João Victor Baroni
; Sacioto, Manuela Furtado
; Assis, Vivian Costa Morais de
; Duani, Helena
; Oliveira, Neimy Ramos de
; Sampaio, Natália da Cunha Severino
; Ramos, Lucas Emanuel Ferreira
; Schwarzbold, Alexandre Vargas
; Jorge, Alzira de Oliveira
; Scotton, Ana Luiza Bahia Alves
; Castro, Bruno Mateus de
; Silva, Carla Thais Cândida Alves da
; Ramos, Carolina Marques
; Anschau, Fernando
; Botoni, Fernando Antonio
; Grizende, Genna Maira Santos
; Nascimento, Guilherme Fagundes
; Ruschel, Karen Brasil
; Menezes, Luanna Silva Monteiro
; Castro, Luís César de
; Nasi, Luiz Antônio
; Carneiro, Marcelo
; Godoy, Mariana Frizzo de
; Nogueira, Matheus Carvalho Alves
; Guimarães Júnior, Milton Henriques
; Ziegelmann, Patricia Klarmann
; Almeida, Rafaela Charão de
; Francisco, Saionara Cristina
; Silveira Neto, Sidney Teodoro
; Araújo, Silvia Ferreira
; Avelino-Silva, Thiago Junqueira
; Aliberti, Márlon Juliano Romero
; Pires, Magda Carvalho
; Silva, Eduardo Sérgio da
; Marcolino, Milena Soriano
.
Abstract Objective To evaluate clinical characteristics and outcomes of COVID-19 patients infected with HIV, and to compare with a paired sample without HIV infection. Methods This is a substudy of a Brazilian multicentric cohort that comprised two periods (2020 and 2021). Data was obtained through the retrospective review of medical records. Primary outcomes were admission to the intensive care unit, invasive mechanical ventilation, and death. Patients with HIV and controls were matched for age, sex, number of comorbidities, and hospital of origin using the technique of propensity score matching (up to 4:1). They were compared using the Chi-Square or Fisher's Exact tests for categorical variables and the Wilcoxon for numerical variables. Results Throughout the study, 17,101 COVID-19 patients were hospitalized, and 130 (0.76%) of those were infected with HIV. The median age was 54 (IQR: 43.0;64.0) years in 2020 and 53 (IQR: 46.0;63.5) years in 2021, with a predominance of females in both periods. People Living with HIV (PLHIV) and their controls showed similar prevalence for admission to the ICU and invasive mechanical ventilation requirement in the two periods, with no significant differences. In 2020, in-hospital mortality was higher in the PLHIV compared to the controls (27.9% vs. 17.7%; p = 0.049), but there was no difference in mortality between groups in 2021 (25.0% vs. 25.1%; p > 0.999). Conclusions Our results reiterate that PLHIV were at higher risk of COVID-19 mortality in the early stages of the pandemic, however, this finding did not sustain in 2021, when the mortality rate is similar to the control group. COVID19 COVID 19 COVID-1 infection (202 2021. . 2021) records unit death sex comorbidities up 41. 41 4 1 4:1) ChiSquare Chi Square Fishers Fisher s study 17101 17 101 17,10 hospitalized 13 0.76% 076 0 76 (0.76% 5 IQR (IQR 43.064.0 430640 43.0 64.0 43 64 43.0;64.0 202 46.063.5 460635 46.0 63.5 46 63 46.0;63.5 (PLHIV differences inhospital 27.9% 279 27 9 (27.9 vs 17.7% 177 7 0.049, 0049 0.049 , 049 0.049) 25.0% 250 25 (25.0 25.1% 251 0.999. 0999 0.999 999 0.999) pandemic however group COVID1 COVID- (20 4:1 1710 10 17,1 0.76 07 (0.76 064 43.064. 43064 430 43. 640 64. 6 43.0;64. 20 063 46.063. 46063 460 46. 635 63. 46.0;63. 27.9 2 (27. 17.7 004 0.04 04 25.0 (25. 25.1 099 0.99 99 (2 4: 171 17, 0.7 (0.7 06 43.064 4306 43.0;64 46.063 4606 46.0;63 27. (27 17. 00 0.0 25. (25 09 0.9 ( 0. (0. 43.06 43.0;6 46.06 46.0;6 (0 43.0; 46.0;
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