Development and assessment of the AE-RADS standardized grid for specifically evaluating adverse events in diagnostic radiology and teleradiology.

IF 2.9 3区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Jean-François Bergerot, Amandine Crombé, Mylène Seux, Basile Porta, Vanessa Fyon, Samuel Le Nivet, Nicolas Lippa, Rémi Peyre, Paul Etchart, Frédérique Gay, Guillaume Gorincour
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引用次数: 0

Abstract

Background: A specific grid for analyzing and grading adverse events in diagnostic radiology is lacking. In France, the standard HAS grid, a generic 5-point scale adapted from the Common Terminology Criteria for Adverse Events (CTCAEs), is criticized for limited applicability in radiology. Our aim was to develop and evaluate a radiology-specific AE grid (AE-RADS) tailored to diagnostic and teleradiological practices and to compare its performance against the CTCAEs-based HAS grid regarding inter-observer reproducibility and agreement with expert consensus.

Methods: AE-RADS, structured as a decision tree with 90 items, was developed by four senior radiologists with extensive AE experience. To assess it, 100 AE cases from early 2022 were reviewed by two radiologists and two non-physician support members, all blinded to the initial AE grading. Observers rated AEs using both the HAS and AE-RADS grids, comparing severity, AE frequency per patient, sources, and types for inter-observer reproducibility and expert agreement. Tests included intra-class correlation coefficient (ICC), Fleiss Kappa and Krippendorff alpha for reproducibility and McNemar test for comparing agreement with consensus.

Results: Among 100 patients (49 women, median age 66.9 years), 104 AEs were identified. AE-RADS achieved higher inter-observer reproducibility for AE frequency (ICC = 0.690 vs. 0.642 with HAS) and for grading the most serious AE (Krippendorff alpha = 0.519 vs. 0.506 with HAS). Agreement with expert consensus was significantly greater with AE-RADS (63-81%) than with HAS (25-47%; P-value range: 0.0001-0.0051).

Conclusion: AE-RADS shows improved, though still imperfect, agreement between evaluators and experts, supporting its potential for more precise AE assessment in diagnostic imaging.

开发和评估AE-RADS标准化网格,专门评估诊断放射学和远程放射学中的不良事件。
背景:诊断放射学不良事件分析和分级的具体网格是缺乏的。在法国,标准HAS网格是一种从不良事件通用术语标准(CTCAEs)改编的通用5分制量表,因在放射学中的适用性有限而受到批评。我们的目的是开发和评估针对诊断和远程放射学实践的放射学特异性声发射网格(AE- rads),并将其与基于ctcaess的HAS网格在观察者之间的可重复性和与专家共识的一致性方面的性能进行比较。方法:AE- rads由4名具有丰富AE经验的资深放射科医师开发,采用决策树结构,共90项。为了评估它,两名放射科医生和两名非医师支持成员审查了2022年初的100例AE病例,所有患者都对最初的AE分级不知情。观察者使用HAS和AE- rads网格对AE进行评分,比较严重程度、每位患者AE频率、来源和类型,以实现观察者之间的可重复性和专家的一致性。检验采用类内相关系数(ICC)、可重复性检验采用Fleiss Kappa和Krippendorff alpha,一致性检验采用McNemar检验。结果:100例患者(女性49例,中位年龄66.9岁)中,发现104例ae。AE- rads在AE频率(ICC = 0.690 vs. 0.642)和最严重AE分级(Krippendorff alpha = 0.519 vs. 0.506)方面具有更高的观察者间再现性。AE-RADS与专家共识的一致性显著高于HAS (25-47%) (63-81%);p值范围:0.0001-0.0051)。结论:AE- rads显示了评估者和专家之间的共识,尽管仍不完善,支持其在诊断成像中更精确的AE评估潜力。
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来源期刊
BMC Medical Imaging
BMC Medical Imaging RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
CiteScore
4.60
自引率
3.70%
发文量
198
审稿时长
27 weeks
期刊介绍: BMC Medical Imaging is an open access journal publishing original peer-reviewed research articles in the development, evaluation, and use of imaging techniques and image processing tools to diagnose and manage disease.
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