UMASS-Baystate, 759 Chestnut St, Springfield, MA, 01144, USA.
Department of Healthcare Delivery and Population Science, Baystate Medical Center, 759 Chestnut St, Springfield, MA, 01144, USA.
BMC Med Imaging. 2022 Aug 24;22(1):148. doi: 10.1186/s12880-022-00878-3.
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.
非囊性纤维化性支气管扩张症是一种具有重要临床意义的疾病，估计有 34 万至 52.2 万人患有该病，每年有 7 万人被诊断出来。由于其临床表现多样，放射诊断仍然是识别该病的关键部分。随着医生对该病的认识提高，越来越多的患者被诊断为轻度至中度支气管扩张症。尽管 CT 胸部检查已被确立为支气管扩张症放射学诊断的主要工具，但支持该诊断过程的文献却有些缺乏。同时，由于其便利性、学习者能够设定学习速度以及与面对面学习相比成本降低，基于网络的放射学教程的趋势有所增加。COVID-19 大流行加速了这一趋势。我们想仔细观察基于网络的培训课程对评分者间可靠性的影响。我们以百分比和kappa 和调整后的kappa 计算来计算一致性。我们发现，单次基于网络的培训课程对支气管扩张症的诊断变异性和准确性几乎没有影响。在这个领域需要进行更多的研究，包括多次培训课程。
