Bridging diagnostic gaps in anterior ocular inflammatory surface diseases

Anterior ocular inflammatory surface diseases (AOISDs), including dry eye disease (DED), allergic conjunctivitis (AC), and infectious conjunctivitis (IC), are highly prevalent, but frequently underdiagnosed. This review examined the current landscape of AOISD diagnostics, emphasizing emerging technologies, diagnostic disparities, and implementation challenges across global health systems.

While conventional diagnosis relies heavily on clinical judgment, newer approaches - such as tear-based biomarkers (e.g., tear IgE, MMP-9), artificial intelligence (AI)-assisted imaging, and telemedicine - offer improved diagnostic precision. Despite their promise, their clinical application faces barriers to adoption, including limited cost-effectiveness data, a lack of reimbursement, and insufficient integration into primary care. Diagnostic capacity remains particularly constrained in low-resource settings owing to workforce shortages and equipment limitations. Public awareness and patient education also affect care-seeking behaviors and appropriate treatment use.

AOISD diagnostics are evolving, but many remain inaccessible due to systemic, economic, and infrastructural barriers. Future progress depends on policy integration, cross-sector collaboration, and the context-specific implementation of diagnostic innovations. Strengthening primary care engagement and aligning investments with the disease burden will be critical to advancing equitable AOISD detection and improving patient outcomes globally.