<![CDATA[Background: Rapid and accurate diagnosis of dengue virus (DENV) infection remains a challenge in endemic areas. Current gold standard methods have several limitations and are often unsuitable for resource-limited settings. Loop-mediated isothermal amplification (LAMP) offers a rapid, cost-effective, and field-adaptable alternative. This meta-analysis aimed to evaluate the diagnostic accuracy of LAMP for detecting DENV infection in human serum samples. Methods: A comprehensive literature search was conducted in PubMed, Scopus, Taylor & Francis, and Wiley databases up to July 2025. Pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC) were calculated to assess the diagnostic performance of LAMP. Meta-DiSC 1.4 was used for analysis, and methodological quality was evaluated using the QUADAS-2 tool. Meta-regression was performed to explore potential sources of heterogeneity. Findings: Five studies involving 807 samples were included in this meta-analysis. The pooled meta-analysis results were as follows: sensitivity 0.83 (95% CI: 0.80–0.85), specificity 0.95 (95% CI: 0.91–0.98), PLR 14.31 (95% CI: 7.82–26.20), NLR 0.15 (95% CI: 0.07–0.31), and DOR 103.30 (95% CI: 23.13–461.42). The summary of AUC was 0.9633, indicating good diagnostic accuracy. Meta-regression showed no significant effect of study design, sample size, geographic region, cross-reactivity testing, or reference standard on diagnostic accuracy. Conclusion: LAMP provides a highly accurate and reliable method for DENV detection in human serum, suitable for both clinical and field use. Its routine implementation may improve dengue outbreak management and surveillance in endemic areas. Novelty/Originality of this article: This is the first meta-analysis to comprehensively evaluate the diagnostic accuracy of LAMP for DENV detection in human serum. By synthesizing evidence from multiple studies, it provides stronger statistical power than individual reports and highlights the robustness of LAMP across diverse settings.]]>
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