4 research outputs found

    FujiLAM for the diagnosis of childhood tuberculosis: a systematic review

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    Background: Childhood tuberculosis (TB) remains underdiagnosed. The novel lateral flow FujiLAM assay detects lipoarabinomannan (LAM) in urine, but data on performance in children remain limited. Methods: We conducted a systematic review assessing the diagnostic performance of FujiLAM for diagnosing paediatric TB. The last search was conducted in November 2021. Results: We included three studies with data from 698 children for FujiLAM. For FujiLAM, sensitivity using a microbiological reference standard were 60% (95% CI 15 to 95), 42% (95% CI 31 to 53) and 63% (95% CI 50 to 75), respectively. Specificity was 93% (95% CI 85 to 98), 92% (95% CI 85 to 96) and 84% (95% CI 80 to 88). Using a composite reference standard, sensitivity was 11% (95% CI 4 to 22), 27% (95% CI 20 to 34) and 33% (95% CI 26 to 40), and specificity was 92% (95% CI 73 to 99), 97% (95% CI 87 to 100) and 85% (95% CI 79 to 89). Subgroup analyses for sensitivity of FujiLAM in children living with HIV (CLHIV) compared with those who were negative for HIV infection were inconsistent across studies. Among CLHIV, sensitivity appeared higher in those with greater immunosuppression, although wide CIs limit the interpretation of observed differences. Meta-analysis was not performed due to considerable study heterogeneity. Conclusion: The high specificity of FujiLAM demonstrates its potential as a point-of-care (POC) rule-in test for diagnosing paediatric TB. As an instrument-free POC test that uses an easy-to-obtain specimen, FujiLAM could significantly improve TB diagnosis in children in low-resource settings, however the small number of studies available highlight that further data are needed. Key priorities to be addressed in forthcoming paediatric evaluations include prospective head-to-head comparisons with AlereLAM using fresh specimens, specific subgroup analysis in CLHIV and extrapulmonary disease and studies in different geographical locations
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