Who
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Study population: 1,583 elderly individuals aged ≥65 years
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Setting: Community-dwelling older adults attending routine health check-ups
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Subgroup for agreement analysis: 108 participants aged ≥65 years
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Sex distribution: Male-to-female ratio ≈ 0.95:1 in the main study
What
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Primary outcomes:
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The prevalence of latent tuberculosis infection (LTBI) among elderly adults was 26.78%.
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Risk factors positively associated with LTBI included:
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Male sex (Adjusted OR = 1.64; 95% CI: 1.25–2.15)
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Former smoking (Adjusted OR = 1.42; 95% CI: 1.01–2.01)
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Exercising at least once per week (Adjusted OR = 2.21; 95% CI: 1.03–4.75)
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Diagnostic agreement findings:
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The domestic AIMTB Rapid Test Assay showed high agreement with QFT-Plus:
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Overall agreement: 92.59%
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AUC for AIMTB: 0.952
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Optimal AIMTB cutoff: 24.02 pg/mL IFN-γ
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Authors’ conclusion: LTBI burden among the elderly is substantial and warrants targeted screening. AIMTB demonstrates strong diagnostic performance and may reduce screening costs in high-TB-burden, resource-limited settings.
When
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Data collection period: Not specified
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Conducted during recent years following implementation of the Tuberculosis-Free Community project.
Where
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Location: Lanxi City
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Region: Central Zhejiang Province (Jinhua area), China
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Context: Rural/suburban setting with high pulmonary TB notification rates among the elderly
Why
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To address the high burden of TB and LTBI in older adults in aging populations.
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To identify factors associated with LTBI in the elderly.
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To evaluate agreement between a domestic LTBI assay (AIMTB) and a conventional interferon-gamma release assay (IGRA), supporting scalable screening strategies in developing countries.
How
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Study design: Community-based cross-sectional study with an embedded diagnostic agreement analysis
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Sampling: Random selection of two subdistricts; daily recruitment of eligible elderly residents
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Sample size: Calculated minimum 1,261; final enrollment 1,583
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Data collection:
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Structured questionnaire (demographics, BMI, smoking, alcohol use, exercise, diabetes)
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LTBI testing using:
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QFT-Plus
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AIMTB Rapid Test Assay
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Statistical analysis:
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Multivariable logistic regression for risk factors
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Agreement analysis (kappa, correlation, Bland–Altman)
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ROC curve to optimize AIMTB cutoff values
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