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免疫状态改变有助于诊断骨关节结核。

Immune status changing helps diagnose osteoarticular tuberculosis.

机构信息

Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China.

Guangxi Medical University, Nanning, Guangxi, People's Republic of China.

出版信息

PLoS One. 2021 Jun 15;16(6):e0252875. doi: 10.1371/journal.pone.0252875. eCollection 2021.

Abstract

OBJECTIVE

This study is aimed to develop a new nomogram for the clinical diagnosis of osteoarticular tuberculosis (TB).

METHODS

xCell score estimation to obtained the immune cell type abundance scores. We downloaded the expression profile of GSE83456 from GEO and proceed xCell score estimation. The routine blood examinations of 326 patients were collected for further validation. We analyzed univariate and multivariate logistic regression to identified independent predicted factor for developing the nomogram. The performance of the nomogram was assessed using the receiver operating characteristic (ROC) curves. The correlation of ESR with lymphocytes, monocytes, and ML ratio was performed and visualized in osteoarticular TB patients.

RESULTS

Compared with the healthy control group in the dataset GSE83456, the xCell score of basophils, monocytes, neutrophils, and platelets was higher, while lymphoid was lower in the EPTB group. The clinical data showed that the cell count of monocytes were much higher, while the cell counts of lymphocytes were lower in the osteoarticular TB group. AUCs of the nomogram was 0.798 for the dataset GSE83456, and 0.737 for the clinical data. We identified the ML ratio, BMI, and ESR as the independent predictive factors for osteoarticular TB diagnosis and constructed a nomogram for the clinical diagnosis of osteoarticular TB. AUCs of this nomogram was 0.843.

CONCLUSIONS

We demonstrated a significant change between the ML ratio of the EPTB and non-TB patients. Moreover, we constructed a nomogram for the clinical diagnosis of the osteoarticular TB diagnosis, which works satisfactorily.

摘要

目的

本研究旨在开发一种新的用于骨关节结核(TB)临床诊断的列线图。

方法

通过 xCell 评分估计获得免疫细胞类型丰度评分。我们从 GEO 下载了 GSE83456 的表达谱,并进行了 xCell 评分估计。进一步验证收集了 326 例患者的常规血液检查。我们进行了单变量和多变量逻辑回归分析,以确定建立列线图的独立预测因素。使用接收者操作特征(ROC)曲线评估列线图的性能。在骨关节结核患者中,进行了 ESR 与淋巴细胞、单核细胞和 ML 比值的相关性分析,并可视化。

结果

与数据集 GSE83456 中的健康对照组相比,EPTB 组的嗜碱性粒细胞、单核细胞、中性粒细胞和血小板的 xCell 评分较高,而淋巴细胞较低。临床数据显示,单核细胞计数在骨关节结核组中明显更高,而淋巴细胞计数则较低。该列线图在数据集 GSE83456 中的 AUC 为 0.798,在临床数据中的 AUC 为 0.737。我们确定了 ML 比值、BMI 和 ESR 作为骨关节结核诊断的独立预测因素,并构建了用于骨关节结核临床诊断的列线图。该列线图的 AUC 为 0.843。

结论

我们证明了 EPTB 患者与非 TB 患者的 ML 比值之间存在显著差异。此外,我们构建了用于骨关节结核临床诊断的列线图,其性能令人满意。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4a0/8205131/69a49e274337/pone.0252875.g001.jpg

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