RESUMEN
We report two cases of corneal graft rejection following immunization with COVID-19-inactivated vaccine Sinopharm and describe the practical implications of this phenomenon in the clinical setting. A 36-year-old woman with a history of unilateral repeated PKP received the first dose of inactivated Sinopharm vaccine. Seven days later, she presented with symptoms and signs of unilateral corneal graft rejection on slit-lamp examination. A 54-year-old woman with a history of unilateral PKP secondary to herpes simplex keratitis (HSK) developed signs of unilateral corneal graft rejection just a week after injection of the first dose of the similar vaccine. Rejection in both patients was treated successfully with topical steroids. To the best of our knowledge, this is the first report of corneal graft rejection following the COVID-19-inactivated Sinopharm vaccine which occurred through the short period after the injection. We hypothesized that the rejection is the result of an allogenic reaction and the immunogenic role of aluminum hydroxide as an adjuvant of this type of vaccine. However, as the second case had a history of rejection following the HSK, a reactivation could not be definitely ruled out. Ophthalmologists should consider these types of adverse reactions after COVID-19 immunization and also monitor a close follow-up of graft health postimmunization. Patients should be informed about the signs and symptoms of rejection, urgent referral, and treatment.
RESUMEN
The Coronavirus disease 2019 (COVID-19) presents open questions in how we clinically diagnose and assess disease course. Recently, chest computed tomography (CT) has shown utility for COVID-19 diagnosis. In this study, we developed Deep COVID DeteCT (DCD), a deep learning convolutional neural network (CNN) that uses the entire chest CT volume to automatically predict COVID-19 (COVID+) from non-COVID-19 (COVID-) pneumonia and normal controls. We discuss training strategies and differences in performance across 13 international institutions and 8 countries. The inclusion of non-China sites in training significantly improved classification performance with area under the curve (AUCs) and accuracies above 0.8 on most test sites. Furthermore, using available follow-up scans, we investigate methods to track patient disease course and predict prognosis.
RESUMEN
BACKGROUND: Chest computed tomography (CT) scan has been used widely to diagnose COVID-19 in Iran. OBJECTIVES: To trace the footsteps of COVID-19 in Iran by exploring the trend in using chest CT scans and its economic impact on radiology departments. Methods: In this cross-sectional study, the number of imaging examinations from 33 tertiary radiology departments in 9 large cities of Iran was collected from September 23, 2019 to March 20, 2020 (Months 1 to 6) and the corresponding months in 2018-2019. RESULTS: A 50.2% increase was noted in the chest CT scan utilization in 2019-2020 compared to 2018-2019. This increase was +15%, +15%, +27%, +2%, +1% in Months 1-5 of 2019-2020, respectively. In Month 6 of 2019-2020, a 251% increase in the acquisition of chest CT scans was observed compared to the Month 6 of 2018-2019. Following negative balance of revenue from Month 1 to 5 with respect to the inflation rate, the total income in Month 6 was further 1.5% less than the same Month in 2018-19. CONCLUSION: The observed peak in chest CT utilization in Month 3 prior to the surge in Month 6 could be explained by the seasonal influenza. However, unawareness about an emerging viral disease, i.e. COVID-19, might have underutilized chest CT in Months 4 and 5 before the official announcement in Month 6. The unbalanced increase in the workload of radiology departments in the shortage of cardiothoracic radiologists with the simultaneous decrease in income initiated a vicious cycle that worsened the economic repercussions of the pandemic.