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Details

Autor(en) / Beteiligte
Titel
Serum cytokine biosignatures for identification of tuberculosis among HIV-positive inpatients
Ist Teil von
  • Thorax, 2024-05, Vol.79 (5), p.465-471
Ort / Verlag
England
Erscheinungsjahr
2024
Quelle
MEDLINE
Beschreibungen/Notizen
  • Serum cytokines correlate with tuberculosis (TB) progression and are predictors of TB recurrence in people living with HIV. We investigated whether serum cytokine biosignatures could diagnose TB among HIV-positive inpatients. We recruited HIV-positive inpatients with symptoms of TB and measured serum levels of inflammation biomarkers including IL-2, IL-4, IL-6, IL-10, tumour necrosis factor-alpha (TNF-α) and interferon-gamma (IFN-γ). We then built and tested our TB prediction model. 236 HIV-positive inpatients were enrolled in the first cohort and all the inflammation biomarkers were significantly higher in participants with microbiologically confirmed TB than those without TB. A binary support vector machine (SVM) model was built, incorporating the data of four biomarkers (IL-6, IL-10, TNF-α and IFN-γ). Efficacy of the SVM model was assessed in training (n=189) and validation (n=47) sets with area under the curve (AUC) of 0.92 (95% CI 0.88 to 0.96) and 0.85 (95% CI 0.72 to 0.97), respectively. In an independent test set (n=110), the SVM model yielded an AUC of 0.85 (95% CI 0.76 to 0.94) with 78% (95% CI 68% to 87%) specificity and 85% (95% CI 66% to 96%) sensitivity. Moreover, the SVM model outperformed interferon-gamma release assay (IGRA) among advanced HIV-positive inpatients irrespective of CD4 T-cell counts, which may be an alternative approach for identifying infection among HIV-positive inpatients with negative IGRA. The four-cytokine biosignature model successfully identified TB among HIV-positive inpatients. This diagnostic model may be an alternative approach to diagnose TB in advanced HIV-positive inpatients with low CD4 T-cell counts.
Sprache
Englisch
Identifikatoren
ISSN: 0040-6376
eISSN: 1468-3296
DOI: 10.1136/thorax-2023-220782
Titel-ID: cdi_pubmed_primary_38490721

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