The value of nomogram model combined with contrast-enhanced ultrasound in the differential diagnosis of cervical tuberculosis lymphadenitis and metastatic lymph node.

Peijun Chen, Ying Zhang, Ting Lin, Jiahui Tong, Ying Wang, Yuehui Yu, Gaoyi Yang
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Abstract

Background: This study aimed to construct an effective Nomogram for the differential diagnosis of cervical tuberculosis lymphadenitis (CTBL) and cervical metastatic lymph node (CMLN) based on ultrasound (US).

Methods: Retrospectively analyzed 227 patients with CTBL and CMLN who attended Hangzhou Red Cross Hospital from January 2020 to October 2022, and were divided into a training set (n = 163) and a validation set (n = 64) according to the clinical data, US, and CEUS qualitative and quantitative analysis data were recorded to establish the prediction model and perform validation. The area under curve (AUC) of the receiver operating characteristic curve (ROC) was used to assess the discrimination of the model; the calibration curve and brier coefficient were used to assess the calibration of the model; and a Nomogram prediction model was constructed to visualize the results nomogram prediction model was constructed to visualize the results.

Results: Gender (OR = 0.200, 95% CI:0.090-0.470, P < 0.001), age (OR = 0.170, 95% CI:0.070-0.410, P < 0.001), liquefaction necrosis (OR = 2.560, 95% CI:1.080-6.040, P = 0.033), perfusion defect (OR = 2.570, 95% CI:1.010-6.580, P = 0.048), and standard deviation (StdDev) (OR = 3.040, 95% CI:1.220-7.570, P = 0.017) were the independent predictors of the constructed model. The AUCs of the constructed predictive model in the training set and validation set were 0.844 and 0.927, respectively; from the calibration curves, it was observed that the predicted values of the model and the actual observed values fell near the 45° diagonal, and the brier scores were 0.145 and 0.109 in the training set and validation set, respectively.

Conclusion: StdDev combined with gender, age, and the presence of liquefaction necrosis and perfusion defects are important features to identify CTBL and CMLN, and the constructed visual nomogram is intuitive and convenient to improve the efficiency of clinical work.

结合对比增强超声的提名图模型在宫颈结核淋巴结炎和转移性淋巴结鉴别诊断中的价值。
背景:方法:回顾性分析杭州市红十字会医院2020年1月至2022年10月收治的227例宫颈结核淋巴结炎(CTBL)和宫颈转移性淋巴结(CMLN)患者,将其分为训练集(n = 163)和验证集(n = 163):回顾性分析2020年1月至2022年10月在杭州市红十字会医院就诊的227例CTBL和CMLN患者,根据临床资料、US、CEUS定性定量分析数据分为训练集(n=163)和验证集(n=64),建立预测模型并进行验证。用接收者操作特征曲线(ROC)的曲线下面积(AUC)来评估模型的区分度;用校准曲线和布赖尔系数来评估模型的校准度;并构建了一个提名图预测模型来直观显示结果:性别(OR = 0.200,95% CI:0.090-0.470,PStdDev结合性别、年龄、有无液化坏死和灌注缺损是鉴别CTBL和CMLN的重要特征,构建的可视化提名图直观、方便,可提高临床工作效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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