Department of Gastroenterology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People's Republic of China.
Department of Gastroenterology, Xiangya Hospital Central South University, Changsha, Hunan, People's Republic of China.
Dig Dis Sci. 2019 Jul;64(7):1967-1975. doi: 10.1007/s10620-019-05491-z. Epub 2019 Feb 6.
The differentiation between untypical intestinal tuberculosis (UITB) and untypical Crohn's disease (UCD) is a challenge.
To analyze phenotypic variables and propose a novel prediction model for differential diagnosis of two conditions.
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.
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.
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.
不典型肠结核（UITB）与不典型克罗恩病（UCD）的鉴别具有挑战性。
分析表型变量，提出一种新的预测模型用于两种疾病的鉴别诊断。
前瞻性纳入 192 例患者。研究了临床、实验室、内镜和影像学特征，并进行了单变量和多变量分析。采用逻辑回归分析和 Fisher 判别分析对训练集进行最终预测模型的建立，在验证集上测试相同的判别函数。
从 TCD、UCD 和 UITB 患者的 52 个典型克罗恩病（TCD）表型变量中选择了 25 个候选变量。UCD 的变量与 TCD 和 UITB 均有重叠。UCD 患者的结核病史、PPD 阳性和 T-SPOT 阳性率均明显高于 TCD（11.6%比 0.0%，27.9%比 0.0%，25.6%比 4.5%，均 P<0.05）。建立了鉴别 UCD 和 UITB 的回归方程和 Fisher 判别函数。在训练数据中，方程的受试者工作特征曲线下面积在临床-实验室、内镜和影像学模型中分别为 0.834、0.69 和 0.648。在验证数据中，Fisher 判别函数鉴别 UCD 的准确率为 86%，鉴别 UITB 的准确率为 73%。
在结核病流行国家，UCD 患者的表型可能与结核感染史有关。Fisher 判别分析是鉴别 UCD 和 UITB 的一种较好选择，值得在临床实践中验证。
