Growth-Based Decision-Making in Congenital Scoliosis with Multiple Vertebral Anomalies.

Background: Congenital scoliosis (CS) associated with multiple vertebral anomalies (MVAs) represents a biologically dynamic deformity in which cumulative segmental asymmetry, residual growth potential, and mechanobiological modulation interact to drive progression. Unlike isolated congenital lesions, MVAs exhibit growth-dependent and configuration-specific behavior, complicating risk stratification and timing of intervention. Despite extensive literature on congenital deformities, an integrated growth-oriented decision framework for this subgroup remains lacking. Methods: This narrative review synthesizes embryological, biomechanical, and clinical evidence related to vertebral growth potential, anomaly configuration, progression patterns, and age-dependent treatment strategies in CS with MVAs. A structured literature search of major databases was performed, and findings were analyzed thematically to propose a biologically grounded growth-based decision framework. Results: Across the literature, three interdependent determinants of progression consistently emerge: anomaly configuration, residual segmental growth capacity, and mechanobiological amplification during growth. High-risk configurations-particularly mixed formation-segmentation defects and fully segmented hemivertebrae with contralateral growth arrest-demonstrate rapid and often non-linear progression. Thoracic involvement further modifies clinical urgency due to its impact on pulmonary development. Integration of developmental biology and mechanobiological principles supports a structured, growth-informed approach to surveillance and intervention timing. Conclusions: MVAs should be conceptualized as dynamic growth systems rather than static structural defects. A shift from angle-driven to growth-informed decision-making may enhance early identification of high-risk patterns while minimizing unnecessary premature fusion in lower-risk cases. Adoption of a structured growth-based framework provides a biologically coherent foundation for individualized management and long-term optimization of spinal and thoracic development.