A diagnostic model for NTM disease in HIV-positive patients: a machine learning-based analysis with novel inflammatory markers
We have found that WBC, NLR, PLR, CAR, and CALLY can assist in the early identification of HIV-positive patients with NTM disease. Based on established parameters, we have successfully developed two early diagnostic prediction models for HIV-positive patients coexisting with NTM disease. Both models demonstrate strong discrimination, calibration, clinical applicability and stability. In clinical practice, for HIV patients with suspected concurrent mycobacterial infection, after excluding TB, these two models can be used for screening and early identification of HIV concurrent NTM disease.
Authors
- Xing Liu (ORCID: https://orcid.org/0009-0004-5567-4675)
- Ge Wang (ORCID: https://orcid.org/0000-0003-0513-0050)
- Chunjing Shi
- Li Li (ORCID: https://orcid.org/0000-0003-0945-2946)
- Shumin Li (ORCID: https://orcid.org/0000-0002-3691-1098)
- Juan Yang (ORCID: https://orcid.org/0000-0003-4077-920X)
- Jiao Yang
- Wenming Li (ORCID: https://orcid.org/0000-0002-7638-9978)
- Yun Luo (ORCID: https://orcid.org/0000-0002-9928-1898)
- Yanhong Zhao
- Lingjun Shen
- Yuanqing Huang
- Huajie Zhang
Institutions
- Kunming Medical University (CN)
- Kunming Third People's Hospital (CN)
- Heilongjiang Center for Tuberculosis Control and Prevention (CN)
- Yunnan Provincial Infectious Disease Hospital (CN)
Publication Details
- Journal
- Frontiers in Immunology
- Published
- 2025-11-14
- DOI
- https://doi.org/10.3389/fimmu.2025.1652747
- Primary Topic
- Infectious Diseases and Tuberculosis
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China