Department of Respiratory Medicine, Middlemore Hospital, Counties Manukau District Health Board, Auckland, New Zealand.
Department of Statistics, The University of Auckland, Auckland, New Zealand.
Respiration. 2022;101(11):990-1005. doi: 10.1159/000526011. Epub 2022 Sep 9.
Competency using radiologic images for bronchoscopic navigation is presumed during subspecialty training, but no assessments objectively measure combined knowledge of radiologic interpretation and ability to maneuver a bronchoscope into peripheral airways.
The objectives of this study were (i) to determine whether the Bronchoscopy-Radiology Skills and Tasks Assessment Tool (BRadSTAT) discriminates between bronchoscopists of various levels of experience and (ii) to improve construct validity using study findings.
BRadSTAT contains 10 questions that assess chest X-ray and CT scan interpretation using multiple images per question and 2 technical skill assessments. After administration to 33 bronchoscopists (5 Beginners, 9 Intermediates, 10 Experienced, and 9 Experts), discriminative power was strengthened using differential weighting on CT-related questions, producing the BRadSTAT-CT score. Cut points for both scores were determined via cross-validation.
Mean BRadSTAT scores for Beginner, Intermediate, Experienced, and Expert were 74 (±13 SD), 78 (±14), 86 (±9), and 88 (±8), respectively. Statistically significant differences were noted between Expert and Beginner, Expert and Intermediate, and Experienced and Beginner (all p ≤ 0.05). Mean BRadSTAT-CT scores for Beginner, Intermediate, Experienced, and Expert were 63 (±14), 74 (±15), 82 (±13), and 90 (±9), respectively, all statistically significant (p ≤ 0.03). Cut points for BRadSTAT-CT had lower sensitivity but greater specificity and accuracy than for BRadSTAT.
BRadSTAT represents the first validated assessment tool measuring knowledge and skills for bronchoscopic access to peripheral airways, which discriminates between bronchoscopists of various experience levels. Refining BRadSTAT produced the BRadSTAT-CT, which had higher discriminative power. Future studies should focus on their usefulness in competency-based bronchoscopy programs.
支气管镜导航的放射学图像使用能力被认为是在亚专科培训期间获得的，但没有评估客观地衡量放射学解释知识和操纵支气管镜进入外周气道的能力。
本研究的目的是（i）确定 Bronchoscopy-Radiology Skills and Tasks Assessment Tool（BRadSTAT）是否可以区分不同经验水平的支气管镜医师，（ii）使用研究结果提高其结构效度。
BRadSTAT 包含 10 个问题，每个问题使用多个图像评估胸部 X 光和 CT 扫描的解释，并评估 2 项技术技能。在对 33 名支气管镜医师（5 名初学者、9 名中级、10 名经验丰富者和 9 名专家）进行管理后，通过对 CT 相关问题进行差异化加权，增强了区分能力，从而产生了 BRadSTAT-CT 分数。通过交叉验证确定了这两个分数的截止值。
初学者、中级、经验丰富者和专家的平均 BRadSTAT 分数分别为 74（±13 SD）、78（±14）、86（±9）和 88（±8）。专家与初学者、专家与中级以及经验丰富者与初学者之间的差异具有统计学意义（均 p ≤ 0.05）。初学者、中级、经验丰富者和专家的平均 BRadSTAT-CT 分数分别为 63（±14）、74（±15）、82（±13）和 90（±9），差异均具有统计学意义（p ≤ 0.03）。BRadSTAT-CT 的截止值具有较低的敏感性，但特异性和准确性较高。
BRadSTAT 代表了第一个经过验证的评估工具，可用于测量支气管镜进入外周气道的知识和技能，可区分不同经验水平的支气管镜医师。对 BRadSTAT 进行细化后产生了 BRadSTAT-CT，其具有更高的区分能力。未来的研究应集中在它们在基于能力的支气管镜检查计划中的有用性上。
