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1.
Radiologia (Engl Ed) ; 64(6): 533-541, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36402539

RESUMO

Fungal lung co-infections associated with COVID-19 may occur in severely ill patients or those with underlying co-morbidities, and immunosuppression. The most common invasive fungal infections are caused by aspergillosis, mucormycosis, pneumocystis, cryptococcus, and candida. Radiologists integrate the clinical disease features with the CT pattern-based approach and play a crucial role in identifying these co-infections in COVID-19 to assist clinicians to make a confident diagnosis, initiate treatment and prevent complications.


Assuntos
COVID-19 , Coinfecção , Micoses , Pneumonia , Humanos , COVID-19/complicações , Coinfecção/diagnóstico por imagem , Coinfecção/complicações , Micoses/etiologia , Micoses/microbiologia , Pulmão/diagnóstico por imagem , Radiologistas
2.
Radiología (Madr., Ed. impr.) ; 64(6): 533-541, Nov-Dic. 2022. ilus
Artigo em Espanhol | IBECS | ID: ibc-211650

RESUMO

Las coinfecciones pulmonares fúngicas asociadas a la COVID-19 pueden ocurrir en pacientes gravemente enfermos o con comorbilidades subyacentes e inmunosupresión. Las infecciones fúngicas invasivas más comunes son causadas por aspergilosis, mucormicosis, y las debidas a Pneumocystis, criptococo y cándida. Los radiólogos integran las características clínicas de la enfermedad con el enfoque basado en patrones de TAC y desempeñan un papel crucial en la identificación de estas coinfecciones en la COVID-19 para ayudar a los médicos a realizar un diagnóstico seguro, iniciar el tratamiento y prevenir complicaciones.(AU)


Fungal lung co-infections associated with COVID-19 may occur in severely ill patients or those with underlying co-morbidities, and immunosuppression. The most common invasive fungal infections are caused by aspergillosis, mucormycosis, pneumocystis, cryptococcus, and candida. Radiologists integrate the clinical disease features with the CT pattern-based approach and play a crucial role in identifying these co-infections in COVID-19 to assist clinicians to make a confident diagnosis, initiate treatment and prevent complications.(AU)


Assuntos
Humanos , Coronavírus Relacionado à Síndrome Respiratória Aguda Grave , Infecções por Coronavirus , Betacoronavirus , Pandemias , Radiologistas , Pneumopatias Fúngicas , Pneumocystis , Cryptococcus , Candida , Aspergilose , Radiologia , Diagnóstico por Imagem , Serviço Hospitalar de Radiologia
3.
Radiologia ; 64(6): 533-541, 2022.
Artigo em Espanhol | MEDLINE | ID: mdl-35874908

RESUMO

Fungal lung co-infections associated with COVID-19 may occur in severely ill patients or those with underlying co-morbidities, and immunosuppression. The most common invasive fungal infections are caused by aspergillosis, mucormycosis, pneumocystis, cryptococcus, and candida. Radiologists integrate the clinical disease features with the CT pattern-based approach and play a crucial role in identifying these co-infections in COVID-19 to assist clinicians to make a confident diagnosis, initiate treatment and prevent complications.

4.
Clin Radiol ; 74(6): 411-417, 2019 06.
Artigo em Inglês | MEDLINE | ID: mdl-30765109

RESUMO

A new standardised reporting system was introduced recently for coronary computed tomography (CT) angiography interpretation called CAD-RADS (Coronary Artery Disease-Reporting and Data System). Like any other new reporting platform, CAD-RADS has both advantages and disadvantages. Consistency in reporting, better clarity of communication, and more streamlined clinical recommendations are the major strengths of CAD-RADS. It has many limitations such as misinterpretation of CT angiography findings inherent to any CT angiography examination and unique disadvantages like misclassification of abnormalities, potential to misguide the referring physicians by suggesting management based on a single score. In addition, CAD-RADS does not include the details on location and extent of disease in the coronary arteries, coronary anomalies and other cardiac and extra cardiac findings.


Assuntos
Angiografia por Tomografia Computadorizada/métodos , Doença da Artéria Coronariana/diagnóstico por imagem , Sistemas de Informação em Radiologia , Humanos , Reprodutibilidade dos Testes
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