| Autor: |
O'Neil, Green, Alexander, Knee, Angelica, Patino, Lucy, Modahl, Sybille, Liautaud |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
BMC Medical Imaging. 22 |
| ISSN: |
1471-2342 |
| DOI: |
10.1186/s12880-022-00878-3 |
| Popis: |
Non-cystic fibrosis bronchiectasis is a clinically important disease with an estimated 340,000–522,000 persons living with the disease and 70,000 being diagnosed annually. The radiographic diagnosis remains a pivotal part of recognizing the disease due to its protean clinical manifestations. As physicians are sensitized to this disease, a greater proportion of patients are being diagnosed with mild to moderate bronchiectasis. Despite the established use of CT chest as the main tool for making a radiologic diagnosis of bronchiectasis, the literature supporting the process of making that diagnosis is somewhat sparse. Concurrently, there has been an increased trend to have Web-based radiologic tutorials due to its convenience, the ability of the learner to set the pace of learning and the reduced cost compared to in-person learning. The COVID-19 pandemic has accelerated this trend. We wanted to look carefully at the effect of a Web-based training session on interrater reliability. Agreement was calculated as percentages and kappa and prevalence adjusted kappa calculated. We found that a single Web-based training session had little effect on the variability and accuracy of diagnosis of bronchiectasis. Larger studies are needed in this area with multiple training sessions. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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