Management, Outcome, Risk, and Expectation classification for structural fetal anomalies to aid antenatal counseling:...

Antenatal detection of structural fetal anomalies is rising with advancements in prenatal imaging, necessitating robust frameworks for risk stratification and counseling. Traditional binary approaches often fail to encompass the multifactorial decision-making process involved. To address this gap, the MORE classification system-encompassing Management (M), Outcome (O), Risk (R), and Expectation (E)-was developed to guide structured antenatal counseling.

This prospective study evaluated the inter-rater reliability and construct validity of the MORE classification when applied independently by three senior pediatric surgeons to 55 antenatally diagnosed fetal anomalies. Ratings were performed using the M, O, and R components, with E excluded from statistical analysis due to its subjectivity. Intraclass correlation coefficients (ICC), Fleiss' kappa, Cronbach's alpha, and Spearman's correlation were computed.

The study cohort had a median gestational age of 19 weeks, with 42% primigravidas. Isolated anomalies were predominant (80%), and 16.4% had suspected chromosomal associations. Internal consistency was acceptable to good (Cronbach's α: 0.757-0.812), and construct validity was high (Spearman's ρ overall = 0.812). ICCs indicated fair-to-moderate inter-rater agreement (0.398-0.584). Fleiss' kappa showed variable agreement: slight for Management (κ = 0.163), fair for Outcome (κ = 0.293), and moderate for Rsk (κ = 0.409). Test-retest reliability was excellent across all domains.

The MORE classification demonstrated good reliability and strong validity in antenatal counseling when used by experienced pediatric surgeons. While the Outcome domain showed highest consistency, the Management and Risk domains warrant refinement for broader adoption. The classification provides a pragmatic, structured framework for multidisciplinary decision-making and can aid in standardizing antenatal counseling practices, especially in resource-limited settings.