Biomarker-Guided Prediction of Pregnancy Viability, Current Evidence and Emerging Insights: A Narrative Review

Early detection of pregnancy viability is crucial for timely intervention and optimal maternal-fetal outcomes. Biomarkers represent a promising advancement for improving diagnostic accuracy and customized patient management. Four databases were searched based on MeSH keywords; extracted data were synthesized and categorized into cytokines, adipokines, and emerging non-classical biomarkers. For each, the mechanism of action, advantages, and limitations were discussed. Cytokines were key players in immune modulation and facilitating early embryonic growth. Adipokines mirrored the maternal metabolic-inflammatory cross-talk in early pregnancy. The non-classical biomarkers offered enhanced sensitivity by capturing subtle molecular changes that surpass those observed in clinical signs. Biomarkers give the advantage of non-invasive risk stratification and personalized monitoring; however, they are hindered by a lack of standardization and limited integration in practice. Integrated multiomic research and leveraging machine learning are recommended as future research areas to enhance diagnostic precision and clinical translation from laboratory insights into clinical practice.