在HIV阴性宿主中,使用临床数据和机器学习的thalaromycosis和结核病早期差异诊断模型
Ye Qiu1, Zheng-Tu Li2, Shi-Xiong Yang3
1State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong 510120, China; Department of Respiratory and Critical Medicine, The Affiliated Tumour Hospital of Guangxi Medical University, Nanning, Guangxi 530021, China.
艾滋病毒阴性个体的Talaromyces marneffei感染正在增加,并且经常被误诊为结核病. 新的临床模型准确地区分了塔拉罗米科斯和肺结核病,有助于诊断.
科学领域:
- 医学真菌学 医学真菌学
- 传染性疾病 传染性疾病
- 临床诊断 临床诊断 临床诊断
背景情况:
- 塔拉罗米切斯马尔内菲 (Talaromyces marneffei) 是一种新兴的真菌病原体,导致塔拉罗米切斯.
- 艾滋病毒阴性个体的塔拉罗米科斯经常被误诊为结核病 (TB).
- talaromycosis 的发病率越来越高,需要改进诊断策略.
研究的目的:
- 分析艾滋病毒阴性患者的塔拉罗美菌和肺结核 (PTB) 之间的临床差异.
- 开发和验证差异诊断的临床预测模型.
- 为了提高 talaromycosis 和 PTB 的诊断准确度.
主要方法:
- 从718名HIV阴性患者 (2018-2023) 的临床数据的回顾性分析.
- 使用多变量分析识别结核病和 talaromycosis 的独立预测因子.
- 基于后勤回归的临床差异诊断模型的开发和验证.
- 使用接收器操作特征 (ROC) 曲线分析评估模型性能.
主要成果:
- 年龄>65,排吐和血小板计数预测了结核病.
- 发烧,胸部疼痛,喘不过气,皮疹,淋巴结裂,骨质溶解,中性粒细胞数量,乙酸蛋白细胞数量,以及阿尔伯明预测的 talaromycosis.
- 不同诊断模型在训练组中达到0.918的曲线下面面积 (AUC),在验证组中达到0.900.
结论:
- 新的临床预测模型有效地区分了艾滋病毒阴性患者的塔拉罗美菌病与PTB.
- 这些模型可以计算任何一种疾病的概率,帮助临床决策.
- 经过验证的模型为诊断新出现的真菌感染提供了有价值的工具.
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