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Analysis of Phenotypic Variables and Differentiation Between Untypical Crohn's Disease and Untypical Intestinal Tuberculosis

机译:无典型克罗恩病与无典型肠结核中的表型变量分析及分解

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Background The differentiation between untypical intestinal tuberculosis (UITB) and untypical Crohn's disease (UCD) is a challenge. Aims To analyze phenotypic variables and propose a novel prediction model for differential diagnosis of two conditions. Methods A total of 192 patients were prospectively enrolled. The clinical, laboratory, endoscopic, and radiological features were investigated and subjected to univariable and multivariable analyses. The final prediction model for differentiation between UCD and UITB was developed by logistic regression analysis and Fisher discriminant analysis on the training set. The same discriminant function was tested on the validation set. Results Twenty-five candidates were selected from 52 phenotypic variables of typical Crohn's disease (TCD), UCD, and UITB patients. UCD's variables overlapped with both TCD and UITB. The percentages of tuberculosis history, positive PPD, and positive T-SPOT result in UCD were all significantly higher than that in TCD (11.6% vs. 0.0%, 27.9% vs. 0.0%, 25.6% vs. 4.5%, respectively, P < 0.05). The regression equations and Fisher discriminant function for discrimination between UCD and UITB were developed. In the training data, the area under the receiver operating characteristic of equations was 0.834, 0.69, and 0.648 in the clinical-laboratory, endoscopic, and radiological model, respectively. The accuracy of Fisher discriminant function for discrimination was 86% in UCD and 73% in UITB in the validation data. Conclusions Phenotypes of UCD patients in TB-endemic countries may be associated with TB infection history. Fisher discriminant analysis is a good choice to differentiate UCD from UITB, which is worthy of verification in clinical practice.
机译:背景技术无典型肠结核结核(UITB)和无典型克罗恩病(UCD)之间的差异是挑战。旨在分析表型变量,并提出一种新的预测模型,用于两个条件的鉴别诊断。方法共于注册192例患者。研究了临床,实验室,内窥镜和放射性特征,并进行了不可变量和多变量的分析。通过对训练集的逻辑回归分析和Fisher判别分析,开发了UCD和UITB之间的差异化的最终预测模型。在验证集上测试了相同的判别功能。结果二十五名候选者选自典型的Crohn病(TCD),UCD和UITB患者的52个表型变量。 UCD的变量与TCD和UITB都重叠。结核病历史,阳性PPD和UCD阳性T-斑块结果的百分比均显着高于TCD(11.6%与0.0%,27.9%,0.0%,25.6%与4.5%,P) <0.05)。开发了对UCD和UITB之间的歧视的回归方程和Fisher判别函数。在训练数据中,在临床实验室,内窥镜和放射模型中,接收器操作特性下的接收器的区域分别为0.834,0.69和0.648。 Fisher判别函数的准确性在UCD中为86%,验证数据中的UITB中为73%。结论UCD患者在TB流行病学中的表型可能与TB感染史有关。 Fisher判别分析是从UITB区分UCD的一种不错选择,这是值得在临床实践中进行验证的。

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