ArticleJournal of clinical laboratory analysis2021
Integrating serum microRNAs and electronic health records improved the diagnosis of tuberculosis.
Article in Journal of clinical laboratory analysis, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 9 citations in OpenAlex.
- Diagnostic performance of circulating microRNA signatures for differentiating tuberculosis disease from tuberculosis infection.Medical microbiology and immunology · 2025Article
- Has-miR-30c-1-3p inhibits macrophage autophagy and promotes Mycobacterium tuberculosis survival by targeting ATG4B and ATG9B.Scientific reports · 2025Article
- Recent progress in tuberculosis diagnosis: insights into blood-based biomarkers and emerging technologies.Frontiers in cellular and infection microbiology · 2025Review
- Development, assessment and validation of a novel prediction nomogram model for risk identification of tracheobronchial tuberculosis in patients with pulmonary tuberculosis.BMJ open respiratory research · 2023Article
- Identification of MicroRNAs as Potential Blood-Based Biomarkers for Diagnosis and Therapeutic Monitoring of Active Tuberculosis.Diagnostics (Basel, Switzerland) · 2022Article
- Immune regulation and emerging roles of noncoding RNAs inFrontiers in immunology · 2022Review
- Integrating serum microRNAs and electronic health records improved the diagnosis of tuberculosis.Journal of clinical laboratory analysis · 2021Article
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundTo verify the differential expression of miR-30c and miR-142-3p between tuberculosis patients and healthy controls and to investigate the performance of microRNA (miRNA) and subsequently models for the diagnosis of tuberculosis (TB).
methodsWe followed up 460 subjects suspected of TB, and finally enrolled 132 patients, including 60 TB patients, 24 non-TB disease controls (TB-DCs), and 48 healthy controls (HCs). The differential expression of miR-30c and miR-142-3p in serum samples of the TB patients, TB-DCs, and HCs were identified by reverse transcription-quantitative real-time PCR. Diagnostic models were developed by analyzing the characteristics of miRNA and electronic health records (EHRs). These models evaluated by the area under the curves (AUC) and calibration curves were presented as nomograms.
resultsThere were differential expression of miR-30c and miR-142-3p between TB patients and HCs (p < 0.05). Individual miRNA has a limited diagnostic value for TB. However, diagnostic performance has been both significantly improved when we integrated miR-142-3p and ordinary EHRs to develop two models for the diagnosis of tuberculosis. The AUC of the model for distinguishing tuberculosis patients from healthy controls has increased from 0.75 (95% CI: 0.66-0.84) to 0.96 (95% CI: 0.92-0.99) and the model for distinguishing tuberculosis patients from non-TB disease controls has increased from 0.67 (95% CI: 0.55-0.79) to 0.94 (95% CI: 0.89-0.99).
conclusionsIntegrating serum miR-142-3p and EHRs is a good strategy for improving TB diagnosis.
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