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1.
Radiologia (Engl Ed) ; 64(6): 533-541, 2022.
Article in English | MEDLINE | ID: mdl-36402539

ABSTRACT

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.


Subject(s)
COVID-19 , Coinfection , Mycoses , Pneumonia , Humans , COVID-19/complications , Coinfection/diagnostic imaging , Coinfection/complications , Mycoses/etiology , Mycoses/microbiology , Lung/diagnostic imaging , Radiologists
2.
Radiología (Madr., Ed. impr.) ; 64(6): 533-541, Nov-Dic. 2022. ilus
Article in Spanish | IBECS | ID: ibc-211650

ABSTRACT

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)


Subject(s)
Humans , Severe acute respiratory syndrome-related coronavirus , Coronavirus Infections , Betacoronavirus , Pandemics , Radiologists , Lung Diseases, Fungal , Pneumocystis , Cryptococcus , Candida , Aspergillosis , Radiology , Diagnostic Imaging , Radiology Department, Hospital
3.
Radiologia ; 64(6): 533-541, 2022.
Article in Spanish | MEDLINE | ID: mdl-35874908

ABSTRACT

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.
Article in English | MEDLINE | ID: mdl-30765109

ABSTRACT

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.


Subject(s)
Computed Tomography Angiography/methods , Coronary Artery Disease/diagnostic imaging , Radiology Information Systems , Humans , Reproducibility of Results
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