Digital Twins in Orthopedics and Trauma: Concepts, Emerging Evidence, and Barriers to Clinical Translation

Background/Objectives: Digital twin technology has attracted growing attention in orthopedics for its potential to support patient-specific modeling, simulation, and data-driven clinical decision-making. However, despite the rapid growth in the literature, clinical adoption remains limited, and the term "digital twin" is often applied inconsistently to fundamentally different technological approaches. To establish a clear, function-oriented definition and taxonomy of digital twins in orthopedics, to map current applications across subspecialties, and to critically assess the level of clinical evidence supporting their use. Methods: A structured narrative review was conducted using targeted searches of major bibliographic databases (PubMed, Web of Science, Scopus), publisher platforms, and complementary semantic search tools. The retrieved literature was interpreted using a functional analytical framework focusing on patient specificity, data integration, intended clinical role, and degree of clinical validation. Rather than conducting a formal, systematic appraisal, the aim was to provide a concept-driven synthesis of the field and identify patterns of use, maturity, and translational limitations. Results: Most reported orthopedic digital twin implementations appear to represent static patient-specific simulations supported primarily by preclinical or feasibility-level evidence. Monitoring-oriented digital twins have been more commonly reported in spine care, rehabilitation, and sports medicine, enabling longitudinal assessments but offering limited predictive or decision-support value. Decision-oriented digital twins are uncommon, yet they seem to be the most clinically mature type described in the current literature; so far, only one randomized controlled trial has demonstrated improved decision quality in arthroplasty care. Fully integrated hybrid or closed-loop digital twins remain largely experimental. Conclusions: Digital twin technology in orthopedics is characterized by substantial conceptual heterogeneity and limited clinical validation. Near-term clinical impact is most likely to arise from narrowly focused, decision-oriented, and monitoring-based digital twins, although this projection remains dependent on further clinical validation. Greater definitional clarity, functional transparency, and rigorous clinical evaluation are essential to support meaningful translation into routine orthopedic practice.