16 research outputs found
COVID-19 pneumonia assessed at a private hospital, a field hospital, and a public-referral hospital: population analysis, chest computed tomography findings, and outcomes
ObjectiveTo compare a private quaternary referral hospital, a public tertiary hospital, and a field hospital dedicated to patients with COVID-19, regarding patients’ characteristics, clinical parameters, laboratory, imaging findings, and outcomes of patients with confirmed diagnosis of COVID-19.MethodsRetrospective multicenter observational study that assessed the association of clinical, laboratory and CT data of 453 patients with COVID-19, and also their outcomes (hospital discharge or admission, intensive care unit admission, need for mechanical ventilation, and mortality caused by COVID-19).ResultsThe mean age of patients was 55 years (±16 years), 58.1% of them were male, and 41.9% were female. Considering stratification by the hospital of care, significant differences were observed in the dyspnea, fever, cough, hypertension, diabetes mellitus parameters, and CT score (p < 0.05). Significant differences were observed in ward admission rates, with a lower rate in the private hospital (40.0%), followed by the public hospital (74.1%), and a higher rate in the field hospital (89.4%). Regarding intensive care unit admission, there was a higher rate in the public hospital (25.2%), followed by the private hospital (15.5%), and a lower rate in the field hospital (9.9%). In the analysis of the discharge and death outcomes, it was found that there was a higher number of patients discharged from the private hospital (94.2%), compared to the field hospital (90.1%) and public hospital (82.3%) and a higher number of deaths in the public hospital (17.7%) compared to the private hospital and field hospital (5.8 and 0% respectively).ConclusionThe analysis of the data regarding the population treated with COVID-19 during the first wave in different levels of care in the public and private health systems in the city of São Paulo revealed statistically significant differences between the populations, reflecting distinct outcomes
Imaging findings in COVID-19 pneumonia
The coronavirus disease (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARSCoV-2), emerged in Wuhan city and was declared a pandemic in March 2020. Although the virus is not restricted to the lung parenchyma, the use of chest imaging in COVID-19 can be especially useful for patients with moderate to severe symptoms or comorbidities. This article aimed to demonstrate the chest imaging findings of COVID-19 on different modalities: chest radiography, computed tomography, and ultrasonography. In addition, it intended to review recommendations on imaging assessment of COVID-19 and to discuss the use of a structured chest computed tomography report. Chest radiography, despite being a low-cost and easily available method, has low sensitivity for screening patients. It can be useful in monitoring hospitalized patients, especially for the evaluation of complications such as pneumothorax and pleural effusion. Chest computed tomography, despite being highly sensitive, has a low specificity, and hence cannot replace the reference diagnostic test (reverse transcription polymerase chain reaction). To facilitate the confection and reduce the variability of radiological reports, some standardizations with structured reports have been proposed. Among the available classifications, it is possible to divide the radiological findings into typical, indeterminate, atypical, and negative findings. The structured report can also contain an estimate of the extent of lung involvement (e.g., more or less than 50% of the lung parenchyma). Pulmonary ultrasonography can also be an auxiliary method, especially for monitoring hospitalized patients in intensive care units, where transfer to a tomography scanner is difficult
Lung Lesion Burden found on Chest CT as a Prognostic Marker in Hospitalized Patients with High Clinical Suspicion of COVID-19 Pneumonia: a Brazilian experience
OBJECTIVE: 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 RT-PCR 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 (LOS), were assessed.
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 ≥50% 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 ≥50% 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 ≥50% 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 ≥50% might be associated with a higher risk of mortality
Correlation Between RT-PCR and Computed Tomography Findings in Patients with COVID-19
Introdução: A pandemia causada pelo novo coronavÃrus fez necessária que as diversas especialidades médicas se reinventassem como parte da polÃtica de enfretamento à uma doença altamente infecciosa e inicialmente desconhecida. Desta forma, a radiologia torácica participou ativamente do combate contra a COVID-19, participando do diagnóstico e da avaliação desses pacientes. Para isso, foi necessário um corpo de evidência crescente que respaldasse o uso dos métodos de imagem no contexto pandêmico. Objetivos: Avaliar a capacidade prognóstica da extensão de acometimento pulmonar pela tomografia computadorizada do tórax em pacientes com COVID-19 considerando a evolução temporal dos achados. Avaliar a utilização das classificações correntes (RSNA e CO-RADS) e a concordância interobservador, bem como a influência do tempo experiência com radiologia torácica na aplicação dessas classificações. Avaliar o papel da tomografia computadorizada de tórax por meio de classificação visual estruturada (RSNA) e de software automático de detecção em pacientes com resultado inicial da RT-PCR negativo, mas com diagnóstico final de COVID-19. Métodos: Este é um compilado de artigos compostos de três estudos: Primeiro estudo retrospectivo unicêntrico com pacientes hospitalizados por sÃndrome gripal atribuÃvel ao Sars-COV-2, em um centro dedicado ao atendimento de pacientes com COVID-19, que possuÃam ao menos um resultado de RT-PCR e uma TC compatÃvel com COVID-19. Os dados clÃnicos e laboratoriais da entrada foram avaliados e a tomografia de entrada foi avaliada quanto à extensão de acometimento do parênquima pulmonar por meio de análise visual. O desfecho avaliado foi mortalidade em 30 dias. O segundo foi um estudo retrospectivo unicêntrico com pacientes com RT-PCR positiva para COVID-19, que foram categorizados por meio das classificações do RSNA e CO-RADS por radiologistas com diferentes nÃveis de experiência e, que desconheciam o resultado da RT-PCR dos pacientes. Foram calculadas a concordância interobservador e intraobservador para cada uma das classificações, bem como a concordância entre essas classificações. O terceiro estudo foi um estudo retrospectivo unicêntrico que avaliou pacientes com RT-PCR inicial negativa para COVID-19, submetidos à tomografia computadorizada de tórax e que tiveram diagnóstico final clÃnico ou serológico de COVID-19. A classificação tomográfica visual foi avaliada de acordo com o consenso da Radiological Society of North America e por meio de software desenvolvido com inteligência artificial para detecção automática de achados e estimativa de probabilidade de COVID-19. Resultados: O primeiro estudo incluiu 457 pacientes, dos quais 58% apresentavam RT-PCR positiva para COVID-19. O tempo médio desde o inÃcio dos sintomas até a RT-PCR foi de 8 dias (IIQ 6- 11 dias). Uma extensão de acometimento pulmonar pela TC 50% foi encontrada em 201 pacientes (44%), o que foi associado com aumento da mortalidade em 30 dias (31% vs 15% em pacientes com extensão <50%, p <0,001). Ajustando as covariáveis basais e considerando os achados da TC como uma covariável modificável com o tempo, os pacientes com extensão 50% permaneceram em maior risco de mortalidade em 30 dias (razão de risco ajustada [HR] de 2,17, intervalo de confiança de 95% [IC]1,47- 3,18,p<0,001).O segundo estudo incluiu um total de 100 pacientes. A classificação RSNA mostrou uma concordância interobservador quase perfeita entre revisores com nÃveis de experiência semelhantes, com um coeficiente kappa de 0,892 (intervalo de confiança de 95% [IC], 0,788- 0,995). CO-RADS mostrou concordância substancial entre revisores com nÃveis de experiência semelhantes, com um coeficiente kappa de 0,642 (IC de 95%, 0,491-0,793). Houve variação interobservador ao comparar revisores menos experientes com revisores mais experientes, com o coeficiente kappa mais alto de 0,396 (IC de 95%, 0,255-0,588). Houve correlação significativa entre as duas classificações, com coeficiente de Kendall de 0,899 (p <0,001) e concordância intraobservador substancial para ambas as classificações. O terceiro estudo contou com 39 pacientes. Na análise tomográfica visual, somente um deles (3%) apresentou tomografia computadorizada classificada como tendo resultado negativo, 69% foram classificados como padrão tÃpico e 28% como padrão indeterminado. Na avaliação, com uso de software, somente quatro (cerca de 10%) tiveram probabilidade de COVID-19 <25%. Discussão e Conclusão: Esse compilado de artigos contribui para o melhor entendimento do papel da tomografia computadorizada na COVID-19. Pode-se comprovar a correlação entre a extensão do acometimento pulmonar com a mortalidade, utilizando um método prático de quantificação, adequado ao uso na prático diária e de acordo com a percepção clÃnica inicial de que um ponto de corte 50% seria uma ferramenta auxiliar à tomada da decisão. Esse achado permaneceu mesmo levando em contato a dependência dela do tempo de sintomas, dado inédito trazido pelo trabalho. Pode-se avaliar a utilização das classificações estruturadas que vem sendo utilizada, sendo o trabalho pioneiro a avaliar e os comparar, ambas neste meio, demonstrando boa concordância entre as duas classificações estruturadas mais usadas e de que forma a experiência pregressa com radiologia torácica pode influenciar nessas classificações. Por fim, ao revisarmos os casos de pacientes com diagnóstico final de COVID-19 e RT-PCR inicial negativa, constatou-se que a capacidade da TC em detectar compatÃveis com o diagnóstico de forma bastante precisa. Não somente isso, mostrou-se que a utilização do software de detecção automática conseguiu identificar boa parte dos casos, o que ocorre de forma quase instantânea, permitindo seu uso em locais onde não há radiologista prontamente disponÃvelIntroduction: A pandemic caused by the new coronavirus obliged the various medical specialties to reinvent themselves as part of a campaign to deal with a highly infectious and unknown disease. Thus, thoracic radiology engaged in the fight against COVID-19, aiding both in the diagnosis and evaluation of patients. This required a growing body of evidence to support the use of imaging methods in the pandemic context. Objectives: To assess the prognostic capacity of the lung lesion burden by chest computed tomography in patients with COVID-19, considering the temporal evolution of the findings. To evaluate the use of current classifications (RSNA and CO-RADS) and the interobserver agreement in our reality, as well as the influence of time experience with thoracic radiology in the application of these classifications. To evaluate the role of chest computed tomography through structured classification (RSNA) and automated software (Huawei) in patients with negative initial RT-PCR results but with a final diagnosis of COVID-19. Methods: This is a compilation of articles composed of three studies: first, a single-center retrospective study with patients hospitalized for flu-like syndrome attributable to Sars-COV-2 in a dedicated center, who had at least one RT-PCR result and chest CT findings consistent with COVID-19. Clinical and laboratory data at entry were evaluated and the entry tomography was visually assessed for lung lesion burden. The outcome evaluated was 30-day mortality. The second was a single-center retrospective study of patients with positive RT-PCR for COVID-19, who were categorized using the RSNA and CO-RADS classifications by radiologists with different levels of experience and who were unaware of the patients\' RT-PCR results. Inter and intra-observer agreement were calculated for each of the classifications, as well as the agreement between these classifications. The third study was a single-center retrospective study that evaluated patients with baseline negative RT-PCR for COVID-19, who underwent chest CT and who had a final clinical or serological diagnosis of COVID-19. Visual tomographic classification was evaluated according to the consensus of the Radiological Society of North America and using software developed with artificial intelligence for automatic detection of findings and estimation of the probability of COVID-19. Results: The first study included 457 patients, of whom 58% had positive RT-PCR for COVID-19. The median time from symptom onset to RT- PCR was 8 days (IQR 6-11 days). Initial LLB on CT 50% was found in 201 patients (44%), which was associated with increased 30-day mortality (31% vs 15% in patients with an extent <50%, p <0.001).Adjusting for baseline covariates and accounting for the CT findings as a time-varying covariate, patients with LLB 50% remained at a higher risk for 30-day mortality (adjusted hazard ratio [HR] of 2.17, 95% confidence interval [CI] 1.47 3.18, p < 0.001). The second study included a total of 100 patients. The RSNA classification showed near perfect interobserver agreement among reviewers with similar levels of experience, with a kappa coefficient of 0.892 (95% confidence interval [CI], 0.788-0.995). CO-RADS showed substantial agreement among reviewers with similar levels of experience, with a kappa coefficient of 0.642 (95% CI, 0.491-0.793). There was interobserver 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 the two classifications, with a Kendall coefficient of 0.899 (p<0.001) and substantial intraobserver agreement for both classifications. The third study included 39 patients. In the visual tomographic analysis, only one of them (3%) had computed tomography classified as having a negative result, 69% were classified as a typical pattern and 28% as an indeterminate pattern. In the assessment using software, only four (about 10%) had a probability of COVID- 19 <25%. Discussion and Conclusion: This compilation of articles contributes to a better understanding of the role of CT in COVID-19. We were able to demonstrate the correlation between the extent of pulmonary involvement and mortality, using a practical method of quantification, suitable for use in daily practice and according to the initial clinical perception that a cutoff point 50% would be an auxiliary tool for decision. This association persisted even when setting CT findings as a time-varying covariate. We were able to evaluate and compare the use of structured classifications in our reality, demonstrating good agreement between the two most used structured classifications and how experience with thoracic radiology could influence these classifications. Finally, when reviewing the cases of patients with a final diagnosis of COVID-19 and negative initial RT-PCR, we could verify CT capability to detect consistent findings with viral pneumonia accurately. Not only that, but we also showed that the use of automatic detection software managed to identify most of the cases, which occurs almost instantly, allowing its use in places where there is no radiologist readily availabl
Anastomosing hemangioma simulating renal cell carcinoma
ABSTRACT The anastomosing hemangioma is a recent described rare variant, which histologically simulates an angiosarcoma and occurs primarily in the genitourinary tract. We present a case of renal anastomosing hemangioma from a radiologic perspective, describing its imaging features and reviewing its presentation and management
Incidentally detected tuberculous prostatitis with microabscess
ABSTRACT Tuberculous prostatitis is a rare and often overlooked entity that may mimic prostatic adenocarcinoma on imaging exams, especially multiparametric magnetic resonance imaging (MRI) of the prostate. Detection of a prostatic abscess is a clue to the correct diagnosis