A Systematic Review on Approaches for Evaluating the Effectiveness of the Ponseti Method in Clubfoot Treatment

Abstract

Congenital talipes equinovarus (CTEV), commonly known as clubfoot, remains one of the most prevalent congenital orthopedic deformities affecting newborns worldwide and necessitates effective management strategies. The Ponseti method, comprising serial casting, percutaneous tenotomy, and bracing, continues to serve as the standard for non surgical correction; however, its success is influenced by factors such as the severity of the deformity, timing of intervention, clinician expertise, and patient adherence. This systematic review examines the integration of techniques, including statistical models, machine learning (ML), and Interval Type-3 Fuzzy Logic (IT3FL) methods, alongside ontology-based frameworks that enhance knowledge representation and interoperability for improved clinical decision-making. Drawing insights from 225 studies published between 1963 and 2025, the review identifies a paradigm shift from empirical to data-driven methodologies, with a notable increase in AI-focused research since 2020. Despite these advancements, challenges persist, particularly regarding limited dataset diversity, small sample sizes, and insufficient clinical validation. Future investigations should emphasize large-scale, multi-center collaborations and the development of clinician-oriented intelligent systems to advance personalized and interpretable management of clubfoot