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Sensitivity of Portable Chest X-ray and CT for COVID-19 Patients (in Low-Resource Settings)

Authors: Dr. Malakhat J. Sultanova; Dr. Kamal S. Akbarov;

Sensitivity of Portable Chest X-ray and CT for COVID-19 Patients (in Low-Resource Settings)

Abstract

The aim of this research was to evaluate the capabilities of chest x-ray and Computed Tomography (CT) equipment in the diagnosis and monitoring of changes in the lungs in patients diagnosed with COVID-19 by reverse transcriptase-polymerase chain reaction (RT-PCR). In this study we analyzed radiological investigation (chest x-ray and CT) results of 50 RT-PCR positive COVID-19 patients, treated in Azerbaijan Medical University clinic between 01 April 2020 and 20 April 2020. Chest x-ray was performed according to standard protocols in digital mode by mobile x-ray unit. CT was performed according to standard local protocols in native mode, images were acquired by 1 mm slices both in lung and soft tissue windows. Sensitivity of both radiological methods was calculated compared to RT-PCR results. The most common finding in chest X-ray were ground-glass opacities (64%) and consolidation (24%). Sensitivity of chest x-ray for COVID-19 infection was 88% (44/50, 95% CI 75.7% - 95.5%). The most common finding in chest CT also were ground-glass opacities (72%) and consolidation (24%). Sensitivity of chest CT for COVID-19 infection was 96% (48/50, 95% CI 86.3% to 99.5%). Despite the lower sensitivity of portable x-ray examination (88%) in comparison with CT (96%), it is recommended to be performed in each patient and is suitable for use in dynamic observations, particularly considering it’s accessibility, transportability and ease of use.

Keywords

COVID-19, portable X-ray, pneumonia, chest CT, chest x-ray

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
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