In Sub-Saharan Africa, lower respiratory tract infections (LRTIs) and tuberculosis (TB) jointly are the leading cause of overall mortality. There is a need to integrate sustainable triage and management strategies into standard care. The TrUST study investigates the utility of point-of-care ultrasound (POCUS) for diagnosis and prognosis of LRTIs in TB endemic regions in the outpatient triage setting. Automated interpretation of POCUS by artificial intelligence (AI) may further standardize and improve its predictive utility as well as facilitate its implementation into usual practice.
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Sensitivity of LUS for the detection of TB
Timeframe: 18 to 24 months
Specificity of LUS for the detection of TB
Timeframe: 18 to 24 months
Sensitivity of FASH PLUS for the detection of TB
Timeframe: 24 to 36 months
Specificity of FASH PLUS for the detection of TB
Timeframe: 24 to 36 months
Sensitivity of combined LUS and FASH PLUS features for the detection of TB
Timeframe: 24 to 36 months
Specificity of combined LUS and FASH PLUS features for the detection of TB
Timeframe: 24 to 36 months
Sensitivity of AI-interpreted LUS for the detection of TB
Timeframe: 24 to 36 months
Specificity of AI-interpreted LUS for the detection of TB
Timeframe: 24 to 36 months
Sensitivity of AI-interpreted FASH PLUS for the detection of TB
Timeframe: 24 to 36 months
Specificity of AI-interpreted FASH PLUS for the detection of TB
Timeframe: 24 to 36 months