MARCIO VALENTE YAMADA SAWAMURA
Projetos de Pesquisa
Unidades Organizacionais
Instituto de Radiologia, Hospital das Clínicas, Faculdade de Medicina
14 resultados
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- Data-driven, cross-disciplinary collaboration: lessons learned at the largest academic health center in Latin America during the COVID-19 pandemic(2024) RITTO, Ana Paula; ARAUJO, Adriana Ladeira de; CARVALHO, Carlos Roberto Ribeiro de; SOUZA, Heraldo Possolo De; FAVARETTO, Patricia Manga e Silva; SABOYA, Vivian Renata Boldrim; GARCIA, Michelle Louvaes; KULIKOWSKI, Leslie Domenici; KALLAS, Esper Georges; PEREIRA, Antonio Jose Rodrigues; COBELLO JUNIOR, Vilson; SILVA, Katia Regina; ABDALLA, Eidi Raquel Franco; SEGURADO, Aluisio Augusto Cotrim; SABINO, Ester Cerdeira; RIBEIRO JUNIOR, Ulysses; FRANCISCO, Rossana Pulcineli Vieira; MIETHKE-MORAIS, Anna; LEVIN, Anna Sara Shafferman; SAWAMURA, Marcio Valente Yamada; FERREIRA, Juliana Carvalho; SILVA, Clovis Artur; MAUAD, Thais; GOUVEIA, Nelson da Cruz; LETAIF, Leila Suemi Harima; BEGO, Marco Antonio; BATTISTELLA, Linamara Rizzo; DUARTE, Alberto Jose da Silva; SEELAENDER, Marilia Cerqueira Leite; MARCHINI, Julio; FORLENZA, Orestes Vicente; ROCHA, Vanderson Geraldo; MENDES-CORREA, Maria Cassia; COSTA, Silvia Figueiredo; CERRI, Giovanni Guido; BONFA, Eloisa Silva Dutra de Oliveira; CHAMMAS, Roger; BARROS FILHO, Tarcisio Eloy Pessoa de; BUSATTO FILHO, GeraldoIntroduction The COVID-19 pandemic has prompted global research efforts to reduce infection impact, highlighting the potential of cross-disciplinary collaboration to enhance research quality and efficiency.Methods At the FMUSP-HC academic health system, we implemented innovative flow management routines for collecting, organizing and analyzing demographic data, COVID-related data and biological materials from over 4,500 patients with confirmed SARS-CoV-2 infection hospitalized from 2020 to 2022. This strategy was mainly planned in three areas: organizing a database with data from the hospitalizations; setting-up a multidisciplinary taskforce to conduct follow-up assessments after discharge; and organizing a biobank. Additionally, a COVID-19 curated collection was created within the institutional digital library of academic papers to map the research output.Results Over the course of the experience, the possible benefits and challenges of this type of research support approach were identified and discussed, leading to a set of recommended strategies to enhance collaboration within the research institution. Demographic and clinical data from COVID-19 hospitalizations were compiled in a database including adults and a minority of children and adolescents with laboratory confirmed COVID-19, covering 2020-2022, with approximately 350 fields per patient. To date, this database has been used in 16 published studies. Additionally, we assessed 700 adults 6 to 11 months after hospitalization through comprehensive, multidisciplinary in-person evaluations; this database, comprising around 2000 fields per subject, was used in 15 publications. Furthermore, thousands of blood samples collected during the acute phase and follow-up assessments remain stored for future investigations. To date, more than 3,700 aliquots have been used in ongoing research investigating various aspects of COVID-19. Lastly, the mapping of the overall research output revealed that between 2020 and 2022 our academic system produced 1,394 scientific articles on COVID-19.Discussion Research is a crucial component of an effective epidemic response, and the preparation process should include a well-defined plan for organizing and sharing resources. The initiatives described in the present paper were successful in our aim to foster large-scale research in our institution. Although a single model may not be appropriate for all contexts, cross-disciplinary collaboration and open data sharing should make health research systems more efficient to generate the best evidence.
- Post-COVID-19 tomographic abnormalities(2022) SAWAMURA, M. V. Y.; VERRASTRO, C. G. Y.; FERREIRA, E. V. M.; ALBUQUERQUE, A. L. P. de; RIBEIRO, S. M.; V, R. Auad; SPERANDIO, P. C. de Abreu; SOUZA, V. C.; LIMA, M. L.; PRUDENTE, R. A.; FRANCO, E. T.; FRANCO, A. C.; BALDI, B. G.; TANNI, S. E.BACKGROUND: The prevalence of persistent respiratory symptoms tends to be low in patients with a longer recovery time after COVID-19. However, some patients may present persistent pulmonary abnormalities. OBJECTIVE: To evaluate the prevalence of tomographic abnormalities 90 days after symptom onset in patients with COVID-19 and compare two chest high-resolution computed tomography (HRCT) analysis techniques. METHODS: A multicentre study of patients hospitalised with COVID-19 having oxygen saturation <93% on room air at hospital admission were evaluated using pulmonary function and HRCT scans 90 days after symptom onset. The images were evaluated by two thoracic radiologists, and were assessed using software that automatically quantified the extent of pulmonary abnormalities. RESULTS: Of the 91 patients included, 81% had at least one pulmonary lobe with abnormalities 90 days after discharge (84% were identified using the automated algorithm). Ground-glass opacities (76%) and parenchymal bands (65%) were the predominant abnormalities. Both chest HRCT technical assessments presented high sensitivity (95.9%) and positive predictive value (92%), with a statistically significant correlation at baseline (R = 0.80) and after 90 days (R = 0.36). CONCLUSION: The prevalence of pulmonary abnormalities on chest HRCT 90 days after symptom onset due to COVID-19 was high; both technical assessments can be used to analyse the images.
- Post-acute sequelae of SARS-CoV-2 infection: relationship of central nervous system manifestations with physical disability and systemic inflammation(2022) BUSATTO, Geraldo F.; ARAUJO, Adriana Ladeira de; CASTALDELLI-MAIA, Joao Mauricio; DAMIANO, Rodolfo Furlan; IMAMURA, Marta; GUEDES, Bruno F.; PINNA, Fabio de Rezende; SAWAMURA, Marcio Valente Yamada; MANCINI, Marcio C.; SILVA, Katia R. da; GARCIA, Michelle L.; SUMITA, Nairo; BRUNONI, Andre Russowsky; DUARTE, Alberto J. da Silva; BURDMANN, Emmanuel A.; KALLAS, Esper G.; CERRI, Giovanni G.; NITRINI, Ricardo; BENTO, Ricardo F.; ROCHA, Vanderson Geraldo; SOUZA, Heraldo Possolo de; MIGUEL, Euripedes C.; CARVALHO, Carlos R. R. de; FORLENZA, Orestes V.; BATISTELLA, Linamara RizzoBackground Despite the multitude of clinical manifestations of post-acute sequelae of SARS-CoV-2 infection (PASC), studies applying statistical methods to directly investigate patterns of symptom co-occurrence and their biological correlates are scarce. Methods We assessed 30 symptoms pertaining to different organ systems in 749 adults (age = 55 +/- 14 years; 47% female) during in-person visits conducted at 6-11 months after hospitalization due to coronavirus disease 2019 (COVID-19), including six psychiatric and cognitive manifestations. Symptom co-occurrence was initially investigated using exploratory factor analysis (EFA), and latent variable modeling was then conducted using Item Response Theory (IRT). We investigated associations of latent variable severity with objective indices of persistent physical disability, pulmonary and kidney dysfunction, and C-reactive protein and D-dimer blood levels, measured at the same follow-up assessment. Results The EFA extracted one factor, explaining 64.8% of variance; loadings were positive for all symptoms, and above 0.35 for 16 of them. The latent trait generated using IRT placed fatigue, psychiatric, and cognitive manifestations as the most discriminative symptoms (coefficients > 1.5, p < 0.001). Latent trait severity was associated with decreased body weight and poorer physical performance (coefficients > 0.240; p <= 0.003), and elevated blood levels of C-reactive protein (coefficient = 0.378; 95% CI 0.215-0.541; p < 0.001) and D-dimer (coefficient = 0.412; 95% CI 0.123-0.702; p = 0.005). Results were similar after excluding subjects with pro-inflammatory comorbidities. Conclusions Different symptoms that persist for several months after moderate or severe COVID-19 may unite within one latent trait of PASC. This trait is dominated by fatigue and psychiatric symptoms, and is associated with objective signs of physical disability and persistent systemic inflammation.
- Lung ultrasound versus chest computed tomography for pregnant inpatients with COVID-19(2023) BIANCOLIN, Sckarlet Ernandes; FERNANDES, Hermann dos Santos; SAWAMURA, Marcio Valente Yamada; QUEIROZ, Joelma; CENTOFANTI, Sandra Frankfurt; LIAO, Adolfo Wenjaw; LEITE, Claudia da Costa; FRANCISCO, Rossana Pulcineli Vieira; BRIZOT, Maria de Lourdes; BASSI, Aline Scalisse; FABRI, Amanda Wictky; SOUZA, Ana Claudia Rodrigues Lopes Amaral de; FARCHE, Ana Claudia Silva; IGAI, Ana Maria Kondo; OLIVEIRA, Ana Maria da Silva Sousa; WAISSMAN, Adriana Lippi; MARTINS, Carlos Eduardo do Nascimento; PAGANOTI, Cristiane de Freitas; DOMINGUES, Danielle Rodrigues; MIKAMI, Fernanda Cristina Ferreira; BAPTISTA, Fernanda Spadotto; CIPPICIANI, Jacqueline Kobayashi; ALBERTINI, Jessica Gorrao Lopes; NIIGAKI, Juliana Ikeda; GALLETTA, Marco Aurelio Knippel; MIYADAHIRA, Mariana Yumi; BARBOSA, Mariana Vieira; MAEDA, Mariane de Fatima Yukie; BARROS, Monica Fairbanks de; TAKIUTI, Nilton Hideto; MARTINELLI, Silvio; ARRYM, Tiago Pedromonico; GOMEZ, Ursula Trovato; FRANCO, Veridiana FreirePurpose To compare lung ultrasound (US) and computed tomography (CT) in the assessment of pregnant women with COVID-19. Methods Prospective study comprising 39 pregnant inpatients with COVID-19 who underwent pulmonary assessment with CT and US with a maximum span of 48 h between the exams. The thorax was divided into 12 regions and assessed in terms of the following: the presence of B-lines (>2), coalescent B-lines, consolidation on US; presence of interlobular thickening, ground glass, consolidation on CT. The two methods were scored by adding up the scores from each thoracic region. Results A significant correlation was found between the scores obtained by the two methods (rICC = 0.946; p < 0.001). They were moderately in agreement concerning the frequency of altered pulmonary regions (weighted kappa = 0.551). In US, a score over 15, coalescent B-lines, and consolidation were predictors of the need for oxygen, whereas the predictors in CT were a lung score over 16 and consolidation. The two methods, US (p < 0.001; AUC = 0.915) and CT (p < 0.001; AUC = 0.938), were fairly accurate in predicting the need for oxygen. Conclusion In pregnant women, lung US and chest CT are of similar accuracy in assessing lungs affected by COVID-19 and can predict the need for oxygen.
- Post-acute sequelae of SARS-CoV-2 infection (PASC): a protocol for a multidisciplinary prospective observational evaluation of a cohort of patients surviving hospitalisation in Sao Paulo, Brazil(2021) BUSATTO, Geraldo Filho; ARAUJO, Adriana Ladeira de; DUARTE, Alberto Jose da Silva; LEVIN, Anna Sara; GUEDES, Bruno Fukelmann; KALLAS, Esper Georges; PINNA, Fabio Rezende; SOUZA, Heraldo Possolo de; SILVA, Katia Regina da; SAWAMURA, Marcio Valente Yamada; SEELAENDER, Marilia; IMAMURA, Marta; GARCIA, Michelle Louvaes; FORLENZA, Orestes Vicente; NITRINI, Ricardo; DAMIANO, Rodolfo Furlan; ROCHA, Vanderson Geraldo; BATISTTELLA, Linamara Rizzo; CARVALHO, Carlos Roberto Ribeiro deIntroduction COVID-19 may lead to persistent and potentially incapacitating clinical manifestations (post-acute sequelae of SARS-CoV-2 infection (PASC)). Using easy-to-apply questionnaires and scales (often by telephone interviewing), several studies evaluated samples of COVID-19 inpatients from 4 weeks to several months after discharge. However, studies conducting systematic multidisciplinary assessments of PASC manifestations are scarce, with thorough in-person objective evaluations restricted to modestly sized subsamples presenting greatest disease severity. Methods and analyses We will conduct a prospective observational study of surviving individuals (above 18 years of age) from a cohort of over 3000 subjects with laboratory-confirmed COVID-19 who were treated as inpatients at the largest academic health centre in Sao Paulo, Brazil (Hospital das Clinicas, Faculdade de Medicina, Universidade de Sao Paulo). All eligible subjects will be consecutively invited to undergo a 1-2-day series of multidisciplinary assessments at 2 time-points, respectively, at 6-9 months and 12-15 months after discharge. Assessment schedules will include detailed multidomain questionnaires applied by medical research staff, self-report scales, objective evaluations of cardiopulmonary functioning, physical functionality and olfactory status, standardised neurological, psychiatric and cognitive examinations, as well as diagnostic laboratory, muscle ultrasound and chest imaging exams. Remaining material from blood tests will be incorporated by a local biobank for use in future investigations on inflammatory markers, genomics, transcriptomics, peptidomics and metabolomics. Ethics and dissemination All components of this programme have been approved by local research ethics committees. We aim to provide insights into the frequency and severity of chronic/post-COVID multiorgan symptoms, as well as their interrelationships and associations with acute disease features, sociodemographic variables and environmental exposures. Findings will be disseminated in peer-reviewed journals and at scientific meetings. Additionally, we aim to provide a data repository to allow future pathophysiological investigations relating clinical PASC features to biomarker data extracted from blood samples.
- Chronic lung lesions in COVID-19 survivors: predictive clinical model(2022) CARVALHO, Carlos Roberto Ribeiro; CHATE, Rodrigo Caruso; SAWAMURA, Marcio Valente Yamada; GARCIA, Michelle Louvaes; LAMAS, Celina Almeida; CARDENAS, Diego Armando Cardona; LIMA, Daniel Mario; SCUDELLER, Paula Gobi; SALGE, Joao Marcos; NOMURA, Cesar Higa; GUTIERREZ, Marco AntonioObjective This study aimed to propose a simple, accessible and low-cost predictive clinical model to detect lung lesions due to COVID-19 infection. Design This prospective cohort study included COVID-19 survivors hospitalised between 30 March 2020 and 31 August 2020 followed-up 6 months after hospital discharge. The pulmonary function was assessed using the modified Medical Research Council (mMRC) dyspnoea scale, oximetry (SpO(2)), spirometry (forced vital capacity (FVC)) and chest X-ray (CXR) during an in-person consultation. Patients with abnormalities in at least one of these parameters underwent chest CT. mMRC scale, SpO(2), FVC and CXR findings were used to build a machine learning model for lung lesion detection on CT. Setting A tertiary hospital in Sao Paulo, Brazil. Participants 749 eligible RT-PCR-confirmed SARS-CoV-2-infected patients aged >= 18 years. Primary outcome measure A predictive clinical model for lung lesion detection on chest CT. Results There were 470 patients (63%) that had at least one sign of pulmonary involvement and were eligible for CT. Almost half of them (48%) had significant pulmonary abnormalities, including ground-glass opacities, parenchymal bands, reticulation, traction bronchiectasis and architectural distortion. The machine learning model, including the results of 257 patients with complete data on mMRC, SpO(2), FVC, CXR and CT, accurately detected pulmonary lesions by the joint data of CXR, mMRC scale, SpO(2) and FVC (sensitivity, 0.85 +/- 0.08; specificity, 0.70 +/- 0.06; F1-score, 0.79 +/- 0.06 and area under the curve, 0.80 +/- 0.07). Conclusion A predictive clinical model based on CXR, mMRC, oximetry and spirometry data can accurately screen patients with lung lesions after SARS-CoV-2 infection. Given that these examinations are highly accessible and low cost, this protocol can be automated and implemented in different countries for early detection of COVID-19 sequelae.
- Thoracic tomographic manifestations in symptomatic respiratory patients with COVID-19(2020) FARIAS, Lucas de Pádua Gomes de; STRABELLI, Daniel Giunchetti; FONSECA, Eduardo Kaiser Ururahy Nunes; LOUREIRO, Bruna Melo Coelho; NOMURA, Cesar Higa; SAWAMURA, Márcio Valente YamadaAbstract China was the epicenter for the novel coronavirus disease (COVID-19), which quickly spread to other Asian countries and later to Western countries; subsequently, COVID-19 was categorized as a pandemic by the World Health Organization. Diagnosis primarily depends on viral detection in respiratory samples; however, available kits are limited, lack high sensitivity, and have a long turnaround time for providing results. In this scenario, computed tomography has emerged as an efficient and available high-sensitivity method, allowing radiologists to readily recognize findings related to COVID-19. The objective of this article is to demonstrate the main tomographic findings in symptomatic respiratory patients with COVID-19 to assist medical professionals during this critical moment.
- Pneumomediastinum in COVID-19 disease: Outcomes and relation to the Macklin effect(2021) BRITO, Joao; GREGORIO, Paulo; MARIANI, Alessandro; D'AMBROSIO, Paula; FILHO, Mauro; FERREIRA, Lorena; SAWAMURA, Marcio; PEGO-FERNANDES, Paulo ManuelAim Pneumomediastinum (PM) is associated with several etiologies and mechanisms. Although it has been described more than 100 years ago, the literature is limited to small retrospective studies. This study aimed to follow patients with coronavirus disease (COVID-19) that developed PM during hospitalization and describe their clinical and radiological evolution. Methods A prospective cohort was developed with patients with PM, excluding those with aerodigestive trauma, inside a hospital COVID-19 dedicated hospital. Clinical variables including onset of symptoms, hemodynamic instability, associated complications, the need of interventions, and disease course were all recorded. Also, radiological findings such as the presence of the Macklin effect, extension of lung involvement by COVID-19, and characteristics of the PM were analyzed. Results Twenty-one patients with non-traumatic PM were followed, resulting in an overall incidence of 0.5% during the study period. Seven (33%) patients had associated pneumothorax and malignant/tension PM was observed in three (14%) cases. The Macklin effect could be found in 11 patients (52%) and the majority of them had more than 50% of lung involvement due to COVID-19. The mortality rate was 49%; however, no deaths were directly related to the PM. Conclusions PM incidence is probably increased in the severe acute respiratory syndrome caused by COVID-19, especially in those with greater involvement of the lungs, and the Macklin effect may be an important underlying mechanism of this complication. Usually, PM has a benign course, but complications like tension/malignant PM may occur requiring prompt detection and intervention.
- Lung Lesion Burden found on Chest CT as a Prognostic Marker in Hospitalized Patients with High Clinical Suspicion of COVID-19 Pneumonia: a Brazil ian experience(2021) FONSECA, Eduardo Kaiser Ururahy Nunes; ASSUNCAO JUNIOR, Antonildes Nascimento; ARAUJO-FILHO, Jose De Arimateia Batista; FERREIRA, Lorena Carneiro; LOUREIRO, Bruna Melo Coelho; STRABELLI, Daniel Giunchetti; FARIAS, Lucas de Padua Gomes de; CHATE, Rodrigo Caruso; CERRI, Giovanni Guido; SAWAMURA, Marcio Valente Yamada; NOMURA, Cesar HigaOBJECTIVE: To investigate the relationship between lung lesion burden (LLB) found on chest computed tomography (CT) and 30-day mortality in hospitalized patients with high clinical suspicion of coronavirus disease 2019 (COVID-19), accounting for tomographic dynamic changes. METHODS: Patients hospitalized with high clinical suspicion of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in a dedicated and reference hospital for COVID-19, having undergone at least one RTPCR test, regardless of the result, and with one CT compatible with COVID-19, were retrospectively studied. Clinical and laboratory data upon admission were assessed, and LLB found on CT was semi-quantitatively evaluated through visual analysis. The primary outcome was 30-day mortality after admission. Secondary outcomes, including the intensive care unit (ICU) admission, mechanical ventilation used, and length of stay RESULTS: A total of 457 patients with a mean age of 57 +/- 15 years were included. Among these, 58% presented with positive RT-PCR result for COVID-19. The median time from symptom onset to RT-PCR was 8 days [interquartile range 6-11 days]. An initial LLB of X50% using CT was found in 201 patients (44%), which was associated with an increased crude at 30-day mortality (31% vs. 15% in patients with LLB of <50%, p<0.001). An LLB of X50% was also associated with an increase in the ICU admission, the need for mechanical ventilation, and a prolonged LOS after adjusting for baseline covariates and accounting for the CT findings as a time-varying covariate; hence, patients with an LLB of X50% remained at a higher risk at 30-day mortality (adjusted hazard ratio 2.17, 95% confidence interval 1.47-3.18, p<0.001). CONCLUSION: Even after accounting for dynamic CT changes in patients with both clinical and imaging findings consistent with COVID-19, an LLB of X50% might be associated with a higher risk of mortality.
- Evaluation of the RSNA and CORADS classifications for COVID-19 on chest computed tomography in the Brazilian population(2021) FONSECA, Eduardo Kaiser Ururahy Nunes; LOUREIRO, Bruna Melo Coelho; STRABELLI, Daniel Giunchetti; FARIAS, Lucas de Padua Gomes de; GARCIA, Jose Vitor Rassi; GAMA, Victor Arcanjo Almeida; FERREIRA, Lorena Carneiro; CHATE, Rodrigo Caruso; ASSUNCAO JUNIOR, Antonildes Nascimento; SAWAMURA, Marcio Valente Yamada; NOMURA, Cesar HigaOBJECTIVE: To determine the correlation between the two tomographic classifications for coronavirus disease (COVID-19), COVID-19 Reporting and Data System (CORADS) and Radiological Society of North America Expert Consensus Statement on Reporting Chest Computed Tomography (CT) Findings Related to COVID-19 (RSNA), in the Brazilian population and to assess the agreement between reviewers with different experience levels. METHODS: Chest CT images of patients with reverse transcriptase-polymerase chain reaction (RT-PCR)-positive COVID-19 were categorized according to the CORADS and RSNA classifications by radiologists with different levels of experience and who were initially unaware of the RT-PCR results. The inter- and intra-observer concordances for each of the classifications were calculated, as were the concordances between classifications. RESULTS: A total of 100 patients were included in this study. The RSNA classification showed an almost perfect inter-observer agreement between reviewers with similar experience levels, with a kappa coefficient of 0.892 (95% confidence interval [CI], 0.788-0.995). CORADS showed substantial agreement among reviewers with similar experience levels, with a kappa coefficient of 0.642 (95% CI, 0.491-0.793). There was inter-observer variation when comparing less experienced reviewers with more experienced reviewers, with the highest kappa coefficient of 0.396 (95% CI, 0.255-0.588). There was a significant correlation between both classifications, with a Kendall coefficient of 0.899 (p<0.001) and substantial intra-observer agreement for both classifications. CONCLUSION: The RSNA and CORADS classifications showed excellent inter-observer agreement for reviewers with the same level of experience, although the agreement between less experience reviewers and the reviewer with the most experience was only reasonable. Combined analysis of both classifications with the first RT-PCR results did not reveal any false-negative results for detecting COVID-19 in patients.