Suppr超能文献

妇产科住院医师可使用国际卵巢肿瘤分析规则准确分类良性卵巢肿瘤。

Obstetrics and Gynecology Residents Can Accurately Classify Benign Ovarian Tumors Using the International Ovarian Tumor Analysis Rules.

作者信息

Sebajuri Jean Marie Vianney, Magriples Urania, Small Maria, Ntasumbumuyange Diomede, Rulisa Stephen, Bazzett-Matabele Lisa

机构信息

College of Medicine and Health Sciences, University of Rwanda, Kigali, Rwanda.

Department of Obstetrics and Gynecology, Yale University School of Medicine, New Haven, Connecticut, USA.

出版信息

J Ultrasound Med. 2020 Jul;39(7):1389-1393. doi: 10.1002/jum.15234. Epub 2020 Feb 3.

Abstract

OBJECTIVES

Recognition of benign versus malignant tumors is essential in gynecologic ultrasound (US). The International Ovarian Tumor Analysis (IOTA) rules have been proposed as part of resident US training. The objective of this study was to examine whether they could be accurately used by obstetrics and gynecology residents in Rwanda.

METHODS

Patients undergoing explorative laparotomy for adnexal masses at the University Teaching Hospital of Kigali were included. Before the study, a didactic lecture on the IOTA rules for classifying adnexal masses was performed. Preoperative transabdominal US examinations were performed by residents at different levels of training, who were blinded to the results of prior US examinations. The IOTA classification was compared to the final pathologic diagnosis.

RESULTS

There were 72 patients who underwent 116 US examinations. Only 15.5% of US examinations were considered inconclusive. First-year residents (12) correctly diagnosed 18 of 20 masses (90%) as benign and 4 of 4 as malignant. Second-year residents (9) classified 29 of 29 masses correctly. Third-year residents (10) accurately identified 21 of 22 (95.5%) as benign and 5 of 5 as malignant. Fourth-year residents (13) accurately identified 11 of 12 (91.7%) as benign and 6 of 6 as malignant. Therefore, 74 of 78 tumors (94.9%) considered benign by IOTA rules were confirmed by histologic results. Similarly, all 20 tumors classified as malignant were confirmed. Overall, the sensitivities to diagnose benign and malignant tumors by the IOTA rules were 83.3% and 100%, respectively. The positive and negative predictive values were 100% and 94.9%. There were no significant differences noted between residency years.

CONCLUSIONS

All levels of Rwandan obstetrics and gynecology residents were able to use the IOTA rules to accurately distinguish benign from malignant tumors.

摘要

目的

在妇科超声检查中,识别良性肿瘤与恶性肿瘤至关重要。国际卵巢肿瘤分析(IOTA)规则已被提议作为住院医师超声培训的一部分。本研究的目的是检验卢旺达的妇产科住院医师能否准确应用这些规则。

方法

纳入在基加利大学教学医院因附件包块接受剖腹探查术的患者。在研究前,就IOTA规则对附件包块进行分类开展了一次教学讲座。由处于不同培训水平的住院医师进行术前经腹超声检查,他们对之前超声检查的结果不知情。将IOTA分类与最终病理诊断进行比较。

结果

72例患者接受了116次超声检查。只有15.5%的超声检查结果被认为不确定。一年级住院医师(12名)正确诊断出20个包块中的18个(90%)为良性,4个中的4个为恶性。二年级住院医师(9名)对29个包块全部分类正确。三年级住院医师(10名)准确识别出22个中的21个(95.5%)为良性,5个中的5个为恶性。四年级住院医师(13名)准确识别出12个中的11个(91.7%)为良性,6个中的6个为恶性。因此,IOTA规则判定为良性的78个肿瘤中有74个(94.9%)经组织学结果证实。同样,所有分类为恶性的20个肿瘤均得到证实。总体而言,IOTA规则诊断良性和恶性肿瘤的敏感性分别为83.3%和100%。阳性和阴性预测值分别为100%和94.9%。不同住院年限之间未发现显著差异。

结论

卢旺达各级妇产科住院医师都能够使用IOTA规则准确区分良性肿瘤与恶性肿瘤。

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