• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

诊断神经放射学中感知与解释错误的风险因素。

Risk Factors for Perceptual-versus-Interpretative Errors in Diagnostic Neuroradiology.

机构信息

From the Departments of Radiology and Medical Imaging (S.H.P.)

Department of Radiology (C.L.S., S.G.M., T.M.S.), New York University Langone Medical Center, New York, New York.

出版信息

AJNR Am J Neuroradiol. 2019 Aug;40(8):1252-1256. doi: 10.3174/ajnr.A6125. Epub 2019 Jul 11.

DOI:10.3174/ajnr.A6125
PMID:31296527
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7048464/
Abstract

BACKGROUND AND PURPOSE

Diagnostic errors in radiology are classified as perception or interpretation errors. This study determined whether specific conditions differed when perception or interpretation errors occurred during neuroradiology image interpretation.

MATERIALS AND METHODS

In a sample of 254 clinical error cases in diagnostic neuroradiology, we classified errors as perception or interpretation errors, then characterized imaging technique, interpreting radiologist's experience, anatomic location of the abnormality, disease etiology, time of day, and day of the week. Interpretation and perception errors were compared with hours worked per shift, cases read per shift, average cases read per shift hour, and the order of case during the shift when the error occurred.

RESULTS

Perception and interpretation errors were 74.8% ( = 190) and 25.2% ( = 64) of errors, respectively. Logistic regression analyses showed that the odds of an interpretation error were 2 times greater (OR, 2.09; 95% CI, 1.05-4.15; = .04) for neuroradiology attending physicians with ≤5 years of experience. Interpretation errors were more likely with MR imaging compared with CT (OR, 2.10; 95% CI, 1.09-4.01; = .03). Infectious/inflammatory/autoimmune diseases were more frequently associated with interpretation errors ( = .04). Perception errors were associated with faster reading rates (6.01 versus 5.03 cases read per hour; = .004) and occurred later during the shift (24th-versus-18th case; = .04).

CONCLUSIONS

Among diagnostic neuroradiology error cases, interpretation-versus-perception errors are affected by the neuroradiologist's experience, technique, and the volume and rate of cases read. Recognition of these risk factors may help guide programs for error reduction in clinical neuroradiology services.

摘要

背景与目的

放射诊断中的错误可分为感知错误或解释错误。本研究旨在确定在神经影像学图像解释过程中出现感知或解释错误时,是否存在特定的差异。

材料与方法

在 254 例诊断性神经放射学中的临床错误案例样本中,我们将错误分为感知或解释错误,然后对成像技术、解释放射科医生的经验、异常的解剖位置、疾病病因、一天中的时间和一周中的天数进行特征描述。我们将解释和感知错误与每次轮班工作的时间、每次轮班阅读的病例、每次轮班每小时平均阅读的病例以及在轮班期间发生错误的病例顺序进行比较。

结果

感知错误和解释错误分别占错误的 74.8%(=190)和 25.2%(=64)。逻辑回归分析显示,经验≤5 年的神经放射科主治医生发生解释错误的可能性是感知错误的 2 倍(比值比,2.09;95%置信区间,1.05-4.15;=0.04)。与 CT 相比,磁共振成像(MR 成像)更易导致解释错误(比值比,2.10;95%置信区间,1.09-4.01;=0.03)。感染/炎症/自身免疫性疾病与解释错误的相关性更高(=0.04)。感知错误与更快的阅读速度相关(每小时阅读的病例数为 6.01 例与 5.03 例;=0.004),并且更可能在轮班后期发生(第 24 例与第 18 例;=0.04)。

结论

在诊断性神经放射学错误案例中,解释错误与感知错误受放射科医生的经验、技术以及阅读的病例数量和速度的影响。认识到这些风险因素可能有助于指导临床神经放射学服务中的错误减少计划。

相似文献

1
Risk Factors for Perceptual-versus-Interpretative Errors in Diagnostic Neuroradiology.诊断神经放射学中感知与解释错误的风险因素。
AJNR Am J Neuroradiol. 2019 Aug;40(8):1252-1256. doi: 10.3174/ajnr.A6125. Epub 2019 Jul 11.
2
Factors Associated With Neuroradiologic Diagnostic Errors at a Large Tertiary-Care Academic Medical Center: A Case-Control Study.与大型三级教学医院神经放射学诊断错误相关的因素:一项病例对照研究。
AJR Am J Roentgenol. 2023 Sep;221(3):355-362. doi: 10.2214/AJR.22.28925. Epub 2023 Mar 29.
3
Radiologists Make More Errors Interpreting Off-Hours Body CT Studies during Overnight Assignments as Compared with Daytime Assignments.放射科医生在夜间轮班期间解读非工作时间的身体 CT 研究时比在白天轮班时更容易出错。
Radiology. 2020 Nov;297(2):374-379. doi: 10.1148/radiol.2020201558. Epub 2020 Aug 18.
4
Neuroradiology diagnostic errors at a tertiary academic centre: effect of participation in tumour boards and physician experience.三级学术中心神经放射学诊断错误:肿瘤委员会参与和医师经验的影响。
Clin Radiol. 2022 Aug;77(8):607-612. doi: 10.1016/j.crad.2022.04.006. Epub 2022 May 16.
5
Impact of Shift Volume on Neuroradiology Diagnostic Errors at a Large Tertiary Academic Center.大型三级学术中心轮班量对神经放射诊断错误的影响。
Acad Radiol. 2023 Aug;30(8):1584-1588. doi: 10.1016/j.acra.2022.08.035. Epub 2022 Sep 27.
6
Trainees May Add Value to Patient Care by Decreasing Addendum Utilization in Radiology Reports.实习生可通过减少放射学报告中的补遗使用为患者护理增添价值。
AJR Am J Roentgenol. 2017 Nov;209(5):976-981. doi: 10.2214/AJR.17.18339. Epub 2017 Aug 4.
7
Understanding and Confronting Our Mistakes: The Epidemiology of Error in Radiology and Strategies for Error Reduction.认识并直面我们的错误:放射学中的错误流行病学及减少错误的策略
Radiographics. 2015 Oct;35(6):1668-76. doi: 10.1148/rg.2015150023.
8
Identifying error types in visual diagnostic skill assessment.在视觉诊断技能评估中识别错误类型。
Diagnosis (Berl). 2017 Jun 27;4(2):93-99. doi: 10.1515/dx-2016-0033.
9
Perceptual errors in pediatric radiology.儿科放射学中的感知错误。
Diagnosis (Berl). 2017 Sep 26;4(3):141-147. doi: 10.1515/dx-2017-0001.
10
Perceptual and Interpretive Error in Diagnostic Radiology-Causes and Potential Solutions.诊断放射学中的感知和解释错误——原因与潜在解决方案。
Acad Radiol. 2019 Jun;26(6):833-845. doi: 10.1016/j.acra.2018.11.006. Epub 2018 Dec 14.

引用本文的文献

1
Improving ultrasound image classification accuracy of liver tumors using deep learning model with hepatitis virus infection information.利用包含肝炎病毒感染信息的深度学习模型提高肝脏肿瘤的超声图像分类准确率。
J Med Ultrason (2001). 2025 Apr 9. doi: 10.1007/s10396-025-01528-1.
2
A deep learning-based automated diagnosis system for SPECT myocardial perfusion imaging.基于深度学习的 SPECT 心肌灌注成像自动诊断系统。
Sci Rep. 2024 Jun 12;14(1):13583. doi: 10.1038/s41598-024-64445-2.
3
Comparing the Diagnostic Performance of GPT-4-based ChatGPT, GPT-4V-based ChatGPT, and Radiologists in Challenging Neuroradiology Cases.比较基于 GPT-4 的 ChatGPT、基于 GPT-4V 的 ChatGPT 和放射科医生在神经放射学挑战性病例中的诊断性能。
Clin Neuroradiol. 2024 Dec;34(4):779-787. doi: 10.1007/s00062-024-01426-y. Epub 2024 May 28.
4
Setting the Bar: The Japanese College of Radiology's Perspective on Safeguarding Quality in the Interpretation of Cross-Sectional Studies per Day.设定标准:日本放射学会对保障横断面研究每日解读质量的看法。
AJNR Am J Neuroradiol. 2024 Feb 7;45(2):E2. doi: 10.3174/ajnr.A8037.
5
Accuracy of ChatGPT generated diagnosis from patient's medical history and imaging findings in neuroradiology cases.ChatGPT根据患者病史和影像学检查结果对神经放射学病例进行诊断的准确性。
Neuroradiology. 2024 Jan;66(1):73-79. doi: 10.1007/s00234-023-03252-4. Epub 2023 Nov 23.
6
Patient safety in radiology: Our experience.放射学中的患者安全:我们的经验。
Med J Armed Forces India. 2023 Jul-Aug;79(4):373-377. doi: 10.1016/j.mjafi.2020.09.006. Epub 2020 Dec 2.
7
Understanding Reader Variability: A 25-Radiologist Study on Liver Metastasis Detection at CT.理解读者变异性:25 位放射科医生在 CT 检测肝转移中的研究。
Radiology. 2023 Feb;306(2):e220266. doi: 10.1148/radiol.220266. Epub 2022 Oct 4.
8
Analysis of "visible in retrospect" to monitor false-negative findings in radiological reports.回顾性分析在放射报告中监测假阴性结果的应用。
Jpn J Radiol. 2023 Feb;41(2):219-227. doi: 10.1007/s11604-022-01338-2. Epub 2022 Sep 19.
9
Analysis of perceptual errors in skull-base pathology.颅底病变中感知错误的分析。
Neuroradiol J. 2023 Oct;36(5):515-523. doi: 10.1177/19714009221108679. Epub 2022 Jun 18.
10
Am I Ready to Be an Independent Neuroradiologist? Objective Trends in Neuroradiology Fellows' Performance during the Fellowship Year.我是否已经准备好成为一名独立的神经放射科医生?神经放射学研究员在研究员年的表现的客观趋势。
AJNR Am J Neuroradiol. 2021 May;42(5):815-823. doi: 10.3174/ajnr.A7030. Epub 2021 Mar 4.

本文引用的文献

1
Fundamentals of Diagnostic Error in Imaging.医学影像学诊断错误基础
Radiographics. 2018 Oct;38(6):1845-1865. doi: 10.1148/rg.2018180021.
2
Features of diffuse gliomas that are misdiagnosed on initial neuroimaging: a case control study.初诊神经影像学误诊的弥漫性胶质瘤特征:病例对照研究。
J Neurooncol. 2018 Oct;140(1):107-113. doi: 10.1007/s11060-018-2939-9. Epub 2018 Jun 29.
3
Heuristics and Cognitive Error in Medical Imaging.医学影像学中的启发式和认知错误。
AJR Am J Roentgenol. 2018 May;210(5):1097-1105. doi: 10.2214/AJR.17.18907. Epub 2018 Mar 12.
4
Bias in Radiology: The How and Why of Misses and Misinterpretations.放射学中的偏倚:漏诊和误诊的原因与方式。
Radiographics. 2018 Jan-Feb;38(1):236-247. doi: 10.1148/rg.2018170107. Epub 2017 Dec 1.
5
Strategies for Improving the Value of the Radiology Report: A Retrospective Analysis of Errors in Formally Over-read Studies.提高放射学报告价值的策略:对正式复核研究中的错误进行回顾性分析
J Am Coll Radiol. 2017 Apr;14(4):459-466. doi: 10.1016/j.jacr.2016.08.033. Epub 2016 Nov 22.
6
Imaging acute ischemic stroke.急性缺血性脑卒中的影像学检查
Handb Clin Neurol. 2016;135:293-315. doi: 10.1016/B978-0-444-53485-9.00016-7.
7
Medical error-the third leading cause of death in the US.医疗差错——美国第三大死因。
BMJ. 2016 May 3;353:i2139. doi: 10.1136/bmj.i2139.
8
Radiologist-initiated double reading of abdominal CT: retrospective analysis of the clinical importance of changes to radiology reports.放射科医生发起的腹部CT双重阅片:对放射学报告变更的临床重要性的回顾性分析
BMJ Qual Saf. 2016 Aug;25(8):595-603. doi: 10.1136/bmjqs-2015-004536. Epub 2016 Mar 24.
9
Double reading of current chest CT examinations: Clinical importance of changes to radiology reports.当前胸部CT检查的双人阅片:放射学报告变更的临床重要性
Eur J Radiol. 2016 Jan;85(1):199-204. doi: 10.1016/j.ejrad.2015.11.012. Epub 2015 Nov 10.
10
Understanding and Confronting Our Mistakes: The Epidemiology of Error in Radiology and Strategies for Error Reduction.认识并直面我们的错误:放射学中的错误流行病学及减少错误的策略
Radiographics. 2015 Oct;35(6):1668-76. doi: 10.1148/rg.2015150023.