利用临床数据和机器学习建立艾滋病毒阴性宿主的滑液菌病和结核病早期鉴别诊断模型

IF 4.7 3区医学 Q1 INFECTIOUS DISEASES

Journal of Infection and Public Health Pub Date : 2025-03-11 DOI:10.1016/j.jiph.2025.102740

Ye Qiu , Zheng-tu Li , Shi-xiong Yang , Wu-shu Chen , Yong Zhang , Qun-yu Kong , Ling-rui Chen , Jie Huang , Lü Lin , Kan Xie , Wen Zeng , Shao-qiang Li , Yang-qing Zhan , Yan Wang , Jian-quan Zhang , Feng Ye

{"title":"利用临床数据和机器学习建立艾滋病毒阴性宿主的滑液菌病和结核病早期鉴别诊断模型","authors":"Ye Qiu , Zheng-tu Li , Shi-xiong Yang , Wu-shu Chen , Yong Zhang , Qun-yu Kong , Ling-rui Chen , Jie Huang , Lü Lin , Kan Xie , Wen Zeng , Shao-qiang Li , Yang-qing Zhan , Yan Wang , Jian-quan Zhang , Feng Ye","doi":"10.1016/j.jiph.2025.102740","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div><em>Talaromyces marneffei</em> is an emerging pathogen, and the number of infections in HIV-negative individuals is increasing. In HIV-negative individuals, talaromycosis is usually misdiagnosed as another disease, especially tuberculosis (TB).</div></div><div><h3>Methods</h3><div>We retrospectively extracted the clinical data of HIV-negative patients with <em>Talaromyces marneffei</em> infection from 2018 to 2023, analyzed the differences between TB patients and talaromycosis patients and attempted to establish differential diagnosis models utilizing clinical prediction models for these two diseases.</div></div><div><h3>Results</h3><div>Overall, 718 patients, including 137 patients with talaromycosis and 581 patients with pulmonary tuberculosis (PTB), were enrolled in this study. According to the multivariate analysis, age > 65 years, expectoration, and PLT count were independent predictors for TB. Fever, chest pain, gasping, rash, lymphadenectasis, osteolysis, Neu count, EOS count, and ALB were independent predictors for talaromycosis. Receiver operating characteristic (ROC) curve analysis of the training set showed that the area under the curve (AUC) (95 % CI) of the clinical differential model based on logistic regression analysis was 0.918 (0.884–0.953). The model was verified in the validation set. ROC curve analysis of the validation set showed that the AUC (95 % CI) was 0.900 (0.841–0.959).</div></div><div><h3>Conclusion</h3><div>These new differential diagnosis models can calculate the probability of either talaromycosis or tuberculosis.</div></div>","PeriodicalId":16087,"journal":{"name":"Journal of Infection and Public Health","volume":"18 6","pages":"Article 102740"},"PeriodicalIF":4.7000,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Early differential diagnosis models of Talaromycosis and Tuberculosis in HIV-negative hosts using clinical data and machine learning\",\"authors\":\"Ye Qiu , Zheng-tu Li , Shi-xiong Yang , Wu-shu Chen , Yong Zhang , Qun-yu Kong , Ling-rui Chen , Jie Huang , Lü Lin , Kan Xie , Wen Zeng , Shao-qiang Li , Yang-qing Zhan , Yan Wang , Jian-quan Zhang , Feng Ye\",\"doi\":\"10.1016/j.jiph.2025.102740\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div><em>Talaromyces marneffei</em> is an emerging pathogen, and the number of infections in HIV-negative individuals is increasing. In HIV-negative individuals, talaromycosis is usually misdiagnosed as another disease, especially tuberculosis (TB).</div></div><div><h3>Methods</h3><div>We retrospectively extracted the clinical data of HIV-negative patients with <em>Talaromyces marneffei</em> infection from 2018 to 2023, analyzed the differences between TB patients and talaromycosis patients and attempted to establish differential diagnosis models utilizing clinical prediction models for these two diseases.</div></div><div><h3>Results</h3><div>Overall, 718 patients, including 137 patients with talaromycosis and 581 patients with pulmonary tuberculosis (PTB), were enrolled in this study. According to the multivariate analysis, age > 65 years, expectoration, and PLT count were independent predictors for TB. Fever, chest pain, gasping, rash, lymphadenectasis, osteolysis, Neu count, EOS count, and ALB were independent predictors for talaromycosis. Receiver operating characteristic (ROC) curve analysis of the training set showed that the area under the curve (AUC) (95 % CI) of the clinical differential model based on logistic regression analysis was 0.918 (0.884–0.953). The model was verified in the validation set. ROC curve analysis of the validation set showed that the AUC (95 % CI) was 0.900 (0.841–0.959).</div></div><div><h3>Conclusion</h3><div>These new differential diagnosis models can calculate the probability of either talaromycosis or tuberculosis.</div></div>\",\"PeriodicalId\":16087,\"journal\":{\"name\":\"Journal of Infection and Public Health\",\"volume\":\"18 6\",\"pages\":\"Article 102740\"},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2025-03-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Infection and Public Health\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1876034125000899\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"INFECTIOUS DISEASES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Infection and Public Health","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1876034125000899","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}

引用次数: 0

摘要

背景马尔尼菲talaromyces marneffei是一种新兴的病原体，hiv阴性个体的感染人数正在增加。在hiv阴性的个体中，塔兰菌病通常被误诊为另一种疾病，特别是结核病（TB）。方法回顾性提取2018 - 2023年hiv阴性患者马尔尼菲塔芳香菌感染的临床资料，分析结核病患者与马尔尼菲塔芳香菌病患者的差异，并试图利用两种疾病的临床预测模型建立鉴别诊断模型。结果共纳入718例患者，其中talaromyosis患者137例，肺结核（PTB）患者581例。根据多变量分析，年龄>； 65岁、咳痰和PLT计数是结核病的独立预测因子。发热、胸痛、喘息、皮疹、淋巴结肿大、骨溶解、Neu计数、EOS计数和ALB是talaromyosis的独立预测因子。训练集的受试者工作特征（ROC）曲线分析显示，基于logistic回归分析的临床差异模型的曲线下面积（AUC）（95 % CI）为0.918（0.884 ~ 0.953）。在验证集中对模型进行了验证。验证集的ROC曲线分析显示，AUC（95 % CI）为0.900（0.841 ~ 0.959）。结论这些新的鉴别诊断模型可以计算出塔氏菌病和肺结核的概率。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Early differential diagnosis models of Talaromycosis and Tuberculosis in HIV-negative hosts using clinical data and machine learning

Background

Talaromyces marneffei is an emerging pathogen, and the number of infections in HIV-negative individuals is increasing. In HIV-negative individuals, talaromycosis is usually misdiagnosed as another disease, especially tuberculosis (TB).

Methods

We retrospectively extracted the clinical data of HIV-negative patients with Talaromyces marneffei infection from 2018 to 2023, analyzed the differences between TB patients and talaromycosis patients and attempted to establish differential diagnosis models utilizing clinical prediction models for these two diseases.

Results

Overall, 718 patients, including 137 patients with talaromycosis and 581 patients with pulmonary tuberculosis (PTB), were enrolled in this study. According to the multivariate analysis, age > 65 years, expectoration, and PLT count were independent predictors for TB. Fever, chest pain, gasping, rash, lymphadenectasis, osteolysis, Neu count, EOS count, and ALB were independent predictors for talaromycosis. Receiver operating characteristic (ROC) curve analysis of the training set showed that the area under the curve (AUC) (95 % CI) of the clinical differential model based on logistic regression analysis was 0.918 (0.884–0.953). The model was verified in the validation set. ROC curve analysis of the validation set showed that the AUC (95 % CI) was 0.900 (0.841–0.959).

Conclusion

These new differential diagnosis models can calculate the probability of either talaromycosis or tuberculosis.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Journal of Infection and Public Health PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH -INFECTIOUS DISEASES

CiteScore

13.10

自引率

1.50%

发文量

203

审稿时长

96 days

期刊介绍： The Journal of Infection and Public Health, first official journal of the Saudi Arabian Ministry of National Guard Health Affairs, King Saud Bin Abdulaziz University for Health Sciences and the Saudi Association for Public Health, aims to be the foremost scientific, peer-reviewed journal encompassing infection prevention and control, microbiology, infectious diseases, public health and the application of healthcare epidemiology to the evaluation of health outcomes. The point of view of the journal is that infection and public health are closely intertwined and that advances in one area will have positive consequences on the other. The journal will be useful to all health professionals who are partners in the management of patients with communicable diseases, keeping them up to date. The journal is proud to have an international and diverse editorial board that will assist and facilitate the publication of articles that reflect a global view on infection control and public health, as well as emphasizing our focus on supporting the needs of public health practitioners. It is our aim to improve healthcare by reducing risk of infection and related adverse outcomes by critical review, selection, and dissemination of new and relevant information in the field of infection control, public health and infectious diseases in all healthcare settings and the community.