Abstract
Cardiovascular disease (CVD) remains a leading cause of mortality globally, underscoring the need for robust predictive biomarkers to enhance risk stratification. Soluble lectin-like oxidized low-density lipoprotein receptor-1 (sLOX-1) has emerged as a promising biomarker linked to oxidative stress and endothelial dysfunction, both critical mechanisms in atherogenesis and cardiovascular events. Objectives: This study aimed to evaluate the prognostic value of sLOX-1 in predicting major adverse cardiovascular and cerebrovascular events (MACCEs), myocardial infarction (MI), heart failure (HF), and stroke outcomes through a systematic review and meta-analysis. Methods: A systematic literature search was conducted across PubMed, Scopus, Web of Science, and Ovid databases for studies published between 2014 and October 2024. Eligible studies assessed the association between sLOX-1 levels and future CVD outcomes in adult populations. Meta-analysis pooled hazard ratios (HRs) were assessed using random- and fixed-effects models. Heterogeneity was evaluated using the I(2) statistic, and study quality was assessed using the Newcastle-Ottawa Scale. Results: Fourteen studies were included, encompassing diverse populations with coronary artery disease (CAD), acute coronary syndrome (ACS), or stroke, with follow-up durations ranging from 30 days to 19.5 years. The meta-analysis of three studies on CAD patients demonstrated a significant association between elevated sLOX-1 levels and increased MACCE risk (HR: 2.3, 95% CI: 0.99-5.33, p = 0.05), albeit with high heterogeneity (I(2) = 83%). The fixed-effects analysis yielded a more consistent HR of 1.47 (95% CI: 1.19-1.81, p < 0.01). Conclusions: sLOX-1 shows promising potential as a prognostic biomarker for CVD and is associated with an increased risk of MACCEs in CAD patients. However, the high heterogeneity among the included studies highlights the need for standardized protocols and larger, well-designed prospective studies to validate its clinical utility. The integration of sLOX-1 into risk prediction models could improve CVD management by identifying high-risk individuals for targeted interventions.