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NICE分类用于结直肠肿瘤性及非肿瘤性息肉的实时诊断价值 被引量:9

The real-time diagnosis value of NICE classification on neoplastic and non-neoplastic colorectal polyps
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摘要 目的探讨NICE分型对结直肠息肉样病变性质的实时诊断能力。方法2015年2月至2015年6月,4位内镜医师(主任医师和主治医师各1位、副主任医师2位)对50例患者结肠镜检查过程中发现的107枚息肉样病变的组织学类型进行了NICE分类预测,以病理结果为金标准对NICE分类实时诊断结直肠肿瘤性息肉的准确性进行评估,并使用卡方检验探讨4位医师在诊断准确性方面的差异。结果107枚息肉经病理确诊肿瘤性息肉49枚、非肿瘤性息肉58枚,NICE分类实时诊断结直肠肿瘤性息肉的总体敏感度、特异度、准确率、阳性预测值和阴性预测值分别为81.6%(40/49)、70.0%(40/58)、74.8%(80/107)、70.0%(40/58)和81.6%(40/49),且不同医师判断卡方检验未发现差异具有统计学意义(P〉0.05)。结论NICE分类用于结直肠肿瘤性与非肿瘤性息肉的实时鉴别具有较好的临床应用价值,对于医师的资质要求不是很高,值得临床进一步研究和推广应用。 Objective To investigate the value of NICE classification on real-time diagnosis for neoplastic and non-neoplastic coloreetal polyps. Methods The histological type of 107 polypoid lesions from 50 patients detected by colonoscopy was predicted by 4 endoscopic physicians using NICE classification, including 1 chief physician, 2 associate chief physician, and 1 attending physician. Taking pathological result as gold standard, the real-time diagnostic accuracy of NICE classification for neoplastic colorectal polyps was evaluated, and the differences of diagnostic accuracy between the 4 endoscopic physicians were compared. Results Among the 107 polypoid lesions, 49 were neoplastic polyps and 58 were non-neoplastic polyps. The sensitivity, specificity, accuracy, positive predictive value and negative predictive value of NICE classification on determination of the histological type of polyps were 81.6% (40/49), 70.0% (40/58), 74. 8% (80/107), 70. 0% (40/58), and 81.6% (40/49), respectively. There was no statistical difference on the prediction ability between the 4 physicians using NICE classification. Conclusion NICE classification is a feasible method for real-time prediction of histology type of eolorectal polyps, and it is undemanding to the qualifications of physicians.
出处 《中华消化内镜杂志》 CSCD 北大核心 2017年第8期573-577,共5页 Chinese Journal of Digestive Endoscopy
基金 北京市医院管理局临床技术创新项目(XMLX201414)
关键词 息肉 结肠 直肠 NICE分类 实时诊断 Polyps Colon Rectum NICE classification Real-time diagnosis
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